ElevenLabs Agents vs telli

Agent ops

1. ai-native userMy coding agent can provision a complete voice agent end to end — create the agent, attach a number, and place a call — through the API, CLI, or MCP without touching the dashboard

   weight 3 · round to ElevenLabs Agents
   ElevenLabs Agents~partialprobed6/10

   Docs and runtime probes confirm agents can be created and managed via API, a real CLI (@elevenlabs/cli, verified live on npm), and a hosted MCP server (verified live with OAuth), all without the dashboard (docs-1,3,4,27,28,38; probe-rt-1,2). Phone-number attachment is also supported via SIP trunking to route calls to agents (docs-12,36), but there is no explicit documentation or evidence of actually placing/initiating an outbound call end-to-end through the API/CLI/MCP — only routing inbound infrastructure integration is described. Missing for 10: explicit API/CLI/MCP call to place an outbound call, and a concrete end-to-end walkthrough combining create+attach+call in one non-dashboard flow.

   • [claimed-docs] “ElevenLabs Agents are managed either through the ElevenAgents dashboard, the ElevenLabs API, the Agents CLI or the hosted MCP server.”
   • [claimed-docs] “Use the ElevenLabs agents skill to build and manage voice agents from your AI coding assistant: npx skills add elevenlabs/skills --skill age…”
   • [claimed-docs] “an assistant such as Claude can create, configure, and manage the agents in your workspace through natural language, with nothing to install…”
   • [claimed-docs] “This integration enables all customers to use their existing phone systems while leveraging ElevenLabs' advanced voice AI capabilities.”
   • [claimed-docs] “Route calls to AI agents without changing your existing phone infrastructure”
   • [claimed-docs] “connect the hosted MCP server to Claude or any other MCP client to create and manage agents through natural language”
   • [probe] “PROBE runtime (recorded 2026-09-05): `npx -y @elevenlabs/cli --version` printed `elevenlabs 1.1.0` keylessly — the official ElevenLabs CLI (…”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://api.elevenlabs.io/v1/mcp returned HTT…”

   proof ↗⚑ flag

   telli~partialprobed5/10

   telli's REST API documents endpoints for scheduling calls and importing/attaching phone numbers (telli-docs-17, telli-docs-19), and the MCP server lets AI tools talk to Charlie, who can 'build and refine agents' (telli-docs-11, telli-docs-22), suggesting agent creation is possible without the dashboard. However, there is no explicit API/CLI 'create agent' endpoint documented, no CLI tool is mentioned at all, and the MCP-driven agent creation is only described as an assistant chat capability rather than a deterministic API call — so a full end-to-end create→attach-number→place-call pipeline via one consistent interface is not clearly evidenced. Missing for 10: a documented create-agent API/CLI endpoint, confirmation MCP/Charlie can fully provision agents without any dashboard step, and an example combining all three steps in one flow.

   • [claimed-docs] “Charlie: Build and refine agents, automate workflows, and analyze your calls with telli's built-in AI assistant.”
   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”
   • [claimed-docs] “Schedules a call at the earliest opportunity within the dialer window. May occur immediately or on the next business day depending on settin…”
   • [claimed-docs] “Imports a phone number from your own SIP trunk provider. This allows you to use existing phone numbers with telli by configuring custom SIP …”
   • [claimed-docs] “The telli MCP server lets AI tools like Claude, ChatGPT, and Codex talk to Charlie, telli's AI assistant, over the Model Context Protocol.”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.telli.com/openapi.json — contains "openapi" key”
   • [probe] “official MCP server documented at https://docs.telli.com/integrations/mcp”

   proof ↗⚑ flag

2. ai-native userThe platform's own AI helps me author agents — generating or improving prompts, flows, and test cases from a description

   weight 1 · round drawn
   ElevenLabs Agents~partialprobed5/10

   ElevenLabs documents that an external AI assistant (e.g., Claude) can create, configure, and manage agents through natural language via the hosted MCP server, and agent-testing docs describe turning real conversations into test cases for regression testing — both are AI-assisted authoring flows. However, this relies on a third-party AI client (Claude) rather than a built-in, platform-native 'describe your agent and we generate it' copilot for prompts/flows within the dashboard itself. Missing for 10: evidence of a first-party generative wizard that authors prompts/flows purely from a natural-language description inside the ElevenLabs UI, and evidence of AI-generated (not just conversation-derived) test-case authoring.

   • [claimed-docs] “an assistant such as Claude can create, configure, and manage the agents in your workspace through natural language, with nothing to install…”
   • [claimed-docs] “connect the hosted MCP server to Claude or any other MCP client to create and manage agents through natural language”
   • [claimed-docs] “Transform real conversations into test cases when you find an interaction where the agent underperformed.”
   • [claimed-docs] “Agent testing lets you verify conversational responses, tool usage, and full multi-turn outcomes before you deploy.”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://api.elevenlabs.io/v1/mcp returned HTT…”

   proof ↗⚑ flag

   telli~partialprobed5/10

   Charlie, telli's built-in AI assistant, is documented as helping to 'build and refine agents, automate workflows, and analyze your calls,' which supports the core idea of AI-assisted agent authoring, and the MCP server lets external AI tools interact with Charlie too. However there's no concrete evidence of generating test cases from a description, or detailed examples of prompt/flow generation output. missing for 10: documented examples of Charlie generating/improving prompts or flows from a natural-language description, evidence of AI-generated test case creation, and independent/hands-on confirmation of these capabilities in practice.

   • [claimed-docs] “Charlie: Build and refine agents, automate workflows, and analyze your calls with telli's built-in AI assistant.”
   • [claimed-docs] “The telli MCP server lets AI tools like Claude, ChatGPT, and Codex talk to Charlie, telli's AI assistant, over the Model Context Protocol.”
   • [probe] “official MCP server documented at https://docs.telli.com/integrations/mcp”

   proof ↗⚑ flag

Build

1. developerBuild a working phone voice agent — prompt, voice, and phone number — and take my first live call within an hour

   weight 3 · round to ElevenLabs Agents
   ElevenLabs Agents~partialclaimed7/10

   Docs show a clear quickstart path — create an agent via dashboard/API, pick from 5k+ voices, and connect phone numbers via SIP trunking to route calls to the agent without changing existing phone infrastructure — which together cover the prompt+voice+phone number pieces of the story. However, there's no explicit end-to-end 'first call in under an hour' walkthrough or independent timing evidence, and phone-number provisioning specifics (vs. just SIP integration) are thin. Missing for 10: an explicit timed/complete quickstart-to-live-call walkthrough, first-party or independent evidence of the actual time-to-first-call, and clearer native phone-number purchase/setup docs beyond SIP trunking.

   • [claimed-docs] “ElevenLabs Agents are managed either through the ElevenAgents dashboard, the ElevenLabs API, the Agents CLI or the hosted MCP server.”
   • [claimed-docs] “Select from 5k+ voices across 31 languages with customization options”
   • [claimed-docs] “This integration enables all customers to use their existing phone systems while leveraging ElevenLabs' advanced voice AI capabilities.”
   • [claimed-docs] “Route calls to AI agents without changing your existing phone infrastructure”
   • [claimed-docs] “we'll start by creating an agent via the API or the web dashboard”
   • [claimed-docs] “This assistant can be embedded into your website or app to provide real-time support to your customers”

   proof ↗⚑ flag

   telli~partialclaimed6/10

   telli provides agent builder, test call feature, voice cloning, and phone number setup (forwarding or SIP trunk import) which together support building and testing a voice agent with prompt, voice, and number, but there's no explicit walkthrough or evidence confirming a full end-to-end setup can be completed within an hour or that phone number provisioning is instant/self-serve for new numbers. missing for 10: a documented quick-start/time-to-first-call benchmark, evidence of instant/native number provisioning (vs SIP/forwarding setup), and independent/hands-on confirmation of the full flow's speed.

   • [claimed-docs] “In the agent builder, click Test call to open the dialog. Pick the agent version (your draft with unsaved changes or any saved revision)...”
   • [claimed-docs] “Use the side-by-side view to listen to the recording while following along in the transcript.”
   • [claimed-docs] “Voice cloning lets you give your agent a custom voice (your own, a colleague's, or a professional voice actor's), so the agent sounds exactl…”
   • [claimed-docs] “Keep your public business number and forward incoming calls to a telli number. You configure the forwarding with your phone provider or PBX.”
   • [claimed-docs] “Connect an existing number and phone system for incoming and outgoing calls. You need SIP trunk access from your provider.”
   • [claimed-docs] “Imports a phone number from your own SIP trunk provider. This allows you to use existing phone numbers with telli by configuring custom SIP …”

   proof ↗⚑ flag

2. developerRun conversations in multiple languages, including detecting and switching language mid-call

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents~partialclaimed4/10

   Docs confirm broad multi-language support (70+ languages, language-specific voice settings) and voice-switching for multi-character use, but there is no explicit documentation of automatic language detection or switching languages mid-call. Missing for 10: explicit language-detection/mid-call switching feature docs, and any hands-on demonstration of a live language switch during a single conversation.

   • [claimed-docs] “Configure, deploy and monitor natural, human-sounding agents in 70+ languages with leading accuracy and ultra-low latency across voice or ch…”
   • [claimed-docs] “You can customize various aspects of your AI agent's voice to create a more natural and engaging conversation experience. This includes cont…”
   • [claimed-docs] “Enable your agent to switch between different voices for multi-character conversations, storytelling, and language tutoring.”
   • [claimed-docs] “Select from 5k+ voices across 31 languages with customization options”

   proof ↗⚑ flag

   telli—none0/10

   No evidence in the pack mentions multilingual support, language detection, or mid-call language switching for telli's voice agents; all documented features concern scheduling, webhooks, tools, analytics, and MCP integration.

   ⚑ flag

3. founderDesign multi-step conversation flows in a visual builder with branching, states, and handoffs without writing code

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents~partialclaimed6/10

   Docs explicitly claim a 'visual workflow builder' for multi-step workflows, plus dashboard-based agent creation, conversation-flow settings (turn-taking, interruptions, timeouts), and tools/handoff-like actions (webhooks, client tools) — supporting the no-code, branching, multi-step story. However, evidence never details branching logic, explicit 'states' or agent-to-agent 'handoffs' within the builder, nor independent hands-on confirmation of the visual builder's depth. Missing for 10: concrete detail/screenshots of branching and state logic in the builder, explicit handoff-between-agents feature description, and independent/third-party corroboration of the builder's no-code sufficiency.

   • [claimed-docs] “Build multi-step workflows with visual workflow builder”
   • [claimed-docs] “Conversation flow settings determine how your assistant handles periods of user silence, interruptions during speech, and turn-taking behavi…”
   • [claimed-docs] “Configure turn-taking, interruptions, and timeout settings”
   • [claimed-docs] “we'll start by creating an agent via the API or the web dashboard”
   • [claimed-docs] “Enable agents to call clients & APIs to perform actions”

   proof ↗⚑ flag

   telli~partialclaimed4/10

   telli has an 'agent builder' with test-call and versioning, and workflow triggers (scheduled, SMS/WhatsApp) suggesting some no-code workflow configuration, plus tool-calls like transfer to another agent implying handoffs. But there's no evidence of a visual flow builder with branching/state diagrams — evidence only shows agent settings, tools, and triggers, not a drag-and-drop conversation flow canvas. missing for 10: explicit visual builder UI with branching/state nodes, evidence of designing multi-step flows with conditional paths, and documentation of handoff logic beyond simple 'transfer tool'.

   • [claimed-docs] “In the agent builder, click Test call to open the dialog. Pick the agent version (your draft with unsaved changes or any saved revision)...”
   • [claimed-docs] “Transfer tools | Move the call to another agent or number.”
   • [claimed-docs] “Choose SMS and WhatsApp workflow recipients from contact properties, collected values, or a fixed number”
   • [claimed-docs] “Workflows can now run automatically on a recurring schedule. Add a Scheduled trigger, choose the interval and start time, and let the workfl…”

   proof ↗⚑ flag

Personalization

1. developerInject dynamic variables and per-caller context at call time so each conversation is personalized

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents✓fullclaimed8/10

   Docs explicitly state 'Use dynamic variables and overrides for per-conversation customization' as a core build feature, directly matching the story of injecting per-caller context at call time. Missing for 10: no independent/hands-on example showing a real dynamic-variable injection call in code, and no detail on variable scoping/limits beyond the single doc mention.

   • [claimed-docs] “Use dynamic variables and overrides for per-conversation customization”

   proof ↗⚑ flag

   telli—none0/10

   The evidence describes contact properties and collected values being used to select SMS/WhatsApp recipients (telli-docs-5) and APIs to manage contacts and schedule calls (telli-docs-12, telli-docs-17), but nowhere does it document injecting dynamic variables or per-caller context into an agent's voice call script/persona at call time. Missing for 10: explicit documentation of variable placeholders in agent prompts, a mechanism for passing per-call custom data via the schedule-call API, and any example of personalized call content driven by caller-specific fields.

   • [claimed-docs] “Choose SMS and WhatsApp workflow recipients from contact properties, collected values, or a fixed number”
   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”
   • [claimed-docs] “Schedules a call at the earliest opportunity within the dialer window. May occur immediately or on the next business day depending on settin…”

   proof ↗⚑ flag

2. developerGround the agent on my documents with a built-in knowledge base or RAG so it answers from my content

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents✓fullclaimed8/10

   Docs explicitly state agents support uploading documents and enabling RAG for grounded responses, directly matching the story's built-in knowledge base/RAG capability. Missing for 10: independent/hands-on corroboration of RAG quality and details on knowledge base management (chunking, size limits, sources).

   • [claimed-docs] “Upload documents and enable RAG for grounded responses”

   proof ↗⚑ flag

   telli—none0/10

   No evidence of a built-in knowledge base or RAG feature for grounding agents on uploaded documents; the docs describe custom tools for API integration and a web_search tool for public information, but nothing about ingesting documents or content for retrieval-based answers.

   ⚑ flag

Agent access

1. ai-native userPoint an agent at llms.txt or agent-oriented docs

   weight 2 · round drawn
   ElevenLabs Agents✓fullprobed9/10

   ElevenLabs publishes a working llms.txt at the root (HTTP 200) and structures its docs as machine-readable .md pages with an explicit pointer to a full docs/llms.txt index, exactly matching the ai-native 'point an agent at llms.txt' pattern; this was independently verified via live probes rather than just claimed docs. Missing for 10: no evidence of a hands-on agent actually consuming the file end-to-end to complete a task (only that the endpoint/format is live and documented).

   • [probe] “PROBE llms.txt: HTTP 200 at https://elevenlabs.io/llms.txt # ElevenLabs ElevenLabs is an AI research and product company transforming how w…”
   • [probe] “PROBE docs-md: HTTP 200 at https://elevenlabs.io/docs/eleven-agents/overview.md > This is a page from the ElevenLabs documentation. For a co…”

   proof ↗⚑ flag

   telli✓fullprobed9/10

   telli hosts a live llms.txt file (confirmed via probe, HTTP 200) plus machine-readable OpenAPI spec explicitly intended for coding agents, and docs also mention agent-oriented context for downloading API specs. missing for 10: no independent/third-party confirmation of an agent successfully consuming llms.txt in practice.

   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.telli.com/llms.txt # telli Documentation > telli is the AI voice platform for agents that sell, su…”
   • [claimed-docs] “Download them to generate client libraries, import the API into tools like Postman, or give coding agents machine-readable API context”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.telli.com/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

2. ai-native userRun the product headlessly / in CI for automation

   weight 2 · round drawn
   ElevenLabs Agents~partialprobed6/10

   ElevenLabs Agents can be managed via a full REST API and an official CLI (verified runtime install/run), enabling scripted/headless creation and configuration of agents outside the dashboard, which supports CI-style automation. However, evidence is docs/probe-based with no CI pipeline examples, no first-class 'run in CI' guidance, and Agent testing is described as pre-deploy validation without confirmation it can be triggered non-interactively/headlessly. Missing for 10: explicit CI/CD integration examples, headless testing invocation docs, and independent hands-on confirmation of automated pipelines.

   • [claimed-docs] “ElevenLabs Agents are managed either through the ElevenAgents dashboard, the ElevenLabs API, the Agents CLI or the hosted MCP server.”
   • [claimed-docs] “we'll start by creating an agent via the API or the web dashboard”
   • [claimed-docs] “Agent testing lets you verify conversational responses, tool usage, and full multi-turn outcomes before you deploy.”
   • [probe] “PROBE runtime (recorded 2026-09-05): `npx -y @elevenlabs/cli --version` printed `elevenlabs 1.1.0` keylessly — the official ElevenLabs CLI (…”

   proof ↗⚑ flag

   telli~partialprobed6/10

   telli exposes a full REST API (with OpenAPI spec) to programmatically schedule calls, manage contacts, and trigger workflows, plus webhooks for event-driven automation and scheduled/recurring workflow triggers — all of which support headless, non-UI automation suitable for CI-like pipelines. However there is no explicit CI/CD example, CLI tool, or documented automated pipeline integration beyond the API/webhook primitives. Missing for 10: dedicated CI/CD documentation or examples, a CLI for scripted invocation, and independent confirmation of headless use in production pipelines.

   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”
   • [claimed-docs] “Schedules a call at the earliest opportunity within the dialer window. May occur immediately or on the next business day depending on settin…”
   • [claimed-docs] “Workflows can now run automatically on a recurring schedule. Add a Scheduled trigger, choose the interval and start time, and let the workfl…”
   • [claimed-docs] “Webhooks push data from telli to your systems in real time. When something happens on a call, telli sends a POST request to the endpoint you…”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.telli.com/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

3. ai-native userPlug MCP servers into this product so it can use their tools

   weight 3 · round to ElevenLabs Agents
   ElevenLabs Agents✓fullclaimed8/10

   Docs explicitly describe connecting conversational agents to external MCP servers so agents can access data sources and tools via MCP, directly matching the story, and this is corroborated by dedicated documentation pages (mcp.md) rather than just passing mention. Missing for 10: independent/hands-on verification of an actual third-party MCP server being plugged in and tool-calls succeeding in production (only docs and a runtime probe on the separate hosted-server feature are present).

   • [claimed-docs] “ElevenLabs allows you to connect your conversational agents to external MCP servers. This enables your agents to: Access and process informa…”
   • [claimed-docs] “ElevenLabs allows you to connect your conversational agents to external MCP servers.”
   • [claimed-docs] “Access and process information from various data sources via the MCP server”

   proof ↗⚑ flag

   telli—none0/10

   Telli's documented MCP support only runs in the opposite direction — it exposes an MCP server so external AI tools (Claude, ChatGPT, Codex) can talk to its Charlie assistant (telli-docs-22, telli-probe-3), not a mechanism for telli's own voice agents to consume external MCP servers' tools. Custom Tools (telli-docs-14, telli-docs-20) let agents call external APIs but are described as custom integrations, not MCP-based tool ingestion.

   • [claimed-docs] “The telli MCP server lets AI tools like Claude, ChatGPT, and Codex talk to Charlie, telli's AI assistant, over the Model Context Protocol.”
   • [probe] “official MCP server documented at https://docs.telli.com/integrations/mcp”
   • [claimed-docs] “Custom Tools: Extend telli's capabilities with custom integrations and workflows.”
   • [claimed-docs] “Custom tools allow your AI agents to access external information by connecting to your APIs.”

   proof ↗⚑ flag

4. ai-native userConnect an agent via an official MCP server

   weight 3 · round to ElevenLabs Agents
   ElevenLabs Agents✓fullprobed9/10

   ElevenLabs explicitly documents and operates a hosted MCP server (api.elevenlabs.io/v1/mcp) that lets external MCP clients like Claude connect to create, configure, and manage agents through natural language, with a runtime probe confirming the live endpoint correctly responds with the MCP OAuth challenge. This is a first-party 'official MCP server' offering, not just client-side MCP consumption, matching the story precisely. Missing for 10: independent/community hands-on confirmation beyond ElevenLabs' own docs and the single runtime probe.

   • [claimed-docs] “ElevenLabs Agents are managed either through the ElevenAgents dashboard, the ElevenLabs API, the Agents CLI or the hosted MCP server.”
   • [claimed-docs] “an assistant such as Claude can create, configure, and manage the agents in your workspace through natural language, with nothing to install…”
   • [claimed-docs] “connect the hosted MCP server to Claude or any other MCP client to create and manage agents through natural language”
   • [claimed-docs] “create, configure, and manage the agents in your workspace through natural language, with nothing to install or run locally”
   • [probe] “official MCP server documented at https://elevenlabs.io/docs/eleven-agents/operate/hosted-mcp”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://api.elevenlabs.io/v1/mcp returned HTT…”

   proof ↗⚑ flag

   telli✓fullprobed8/10

   telli documents an official MCP server that lets external AI tools (Claude, ChatGPT, Codex) connect over the Model Context Protocol to interact with Charlie, telli's assistant, confirmed both in docs and via a live probe of the integrations/mcp page. Missing for 10: no independent/hands-on corroboration beyond first-party docs and the probe, and no detail on server setup/auth specifics.

   • [claimed-docs] “The telli MCP server lets AI tools like Claude, ChatGPT, and Codex talk to Charlie, telli's AI assistant, over the Model Context Protocol.”
   • [probe] “official MCP server documented at https://docs.telli.com/integrations/mcp”

   proof ↗⚑ flag

5. ai-native userUse an official CLI

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents✓fullprobed9/10

   ElevenLabs documents an official Agents CLI for managing agents, and runtime probing confirms `npx @elevenlabs/cli` installs and runs keylessly from npm, corroborating the docs claim with hands-on evidence. Missing for 10: deeper documentation of full CLI command surface/subcommands beyond basic install confirmation.

   • [claimed-docs] “ElevenLabs Agents are managed either through the ElevenAgents dashboard, the ElevenLabs API, the Agents CLI or the hosted MCP server.”
   • [claimed-docs] “Use the ElevenLabs agents skill to build and manage voice agents from your AI coding assistant: npx skills add elevenlabs/skills --skill age…”
   • [claimed-docs] “Use the ElevenLabs agents skill to build and manage voice agents from your AI coding assistant”
   • [probe] “PROBE runtime (recorded 2026-09-05): `npx -y @elevenlabs/cli --version` printed `elevenlabs 1.1.0` keylessly — the official ElevenLabs CLI (…”

   proof ↗⚑ flag

   telli—none0/10

   telli offers a REST API, webhooks, and an MCP server for AI assistants, but there is no mention anywhere in the evidence of an official CLI tool for telli. missing for 10: any documentation or reference to a telli CLI, its commands, or installation instructions.

   ⚑ flag

6. ai-native userDrive the product through a documented public API

   weight 3 · round drawn
   ElevenLabs Agents✓fullprobed9/10

   ElevenLabs Agents ships a documented public API alongside a dashboard, CLI, and hosted MCP server for programmatic agent creation/management, with quickstart docs explicitly noting 'creating an agent via the API' and full customization (tools, voice, analysis, testing) accessible programmatically. Runtime probes confirm the CLI installs keylessly and the hosted MCP endpoint is live and functional. Missing for 10: no independent third-party API reference/SDK usage examples or community corroboration beyond first-party docs.

   • [claimed-docs] “ElevenLabs Agents are managed either through the ElevenAgents dashboard, the ElevenLabs API, the Agents CLI or the hosted MCP server.”
   • [claimed-docs] “we'll start by creating an agent via the API or the web dashboard”
   • [claimed-docs] “Enable agents to call clients & APIs to perform actions”
   • [probe] “PROBE runtime (recorded 2026-09-05): `npx -y @elevenlabs/cli --version` printed `elevenlabs 1.1.0` keylessly — the official ElevenLabs CLI (…”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://api.elevenlabs.io/v1/mcp returned HTT…”

   proof ↗⚑ flag

   telli✓fullprobed9/10

   telli documents a REST API with endpoints (schedule-call, import-phone-number), API key/bearer auth, webhooks, and a downloadable OpenAPI spec (confirmed live at openapi.json), plus an MCP server for AI tool access — enabling full programmatic/agentic control. missing for 10: independent third-party validation of API robustness beyond vendor docs.

   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”
   • [claimed-docs] “Webhooks: Receive real-time notifications about call events, status changes, and outcomes.”
   • [claimed-docs] “All endpoints authenticate with an API key from the telli app (Settings > Developer), sent as a bearer token”
   • [claimed-docs] “Download them to generate client libraries, import the API into tools like Postman, or give coding agents machine-readable API context”
   • [claimed-docs] “Schedules a call at the earliest opportunity within the dialer window. May occur immediately or on the next business day depending on settin…”
   • [claimed-docs] “Imports a phone number from your own SIP trunk provider. This allows you to use existing phone numbers with telli by configuring custom SIP …”
   • [claimed-docs] “Webhooks push data from telli to your systems in real time. When something happens on a call, telli sends a POST request to the endpoint you…”
   • [claimed-docs] “The telli MCP server lets AI tools like Claude, ChatGPT, and Codex talk to Charlie, telli's AI assistant, over the Model Context Protocol.”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.telli.com/openapi.json — contains "openapi" key”
   • [probe] “official MCP server documented at https://docs.telli.com/integrations/mcp”

   proof ↗⚑ flag

7. ai-native userIssue scoped/least-privilege API credentials for an agent

   weight 2 · round drawn
   ElevenLabs Agents—none0/10

   Evidence covers agent-side authentication (protecting inbound access to a deployed agent) and OAuth for the hosted MCP server, but there is no documentation of issuing scoped or least-privilege API keys/tokens that limit what an agent itself can do via the ElevenLabs API. Missing for 10: any docs on API key permission scopes, workspace role-based tokens, or restricted-credential issuance for agents.

   • [claimed-docs] “Secure agent access | Authentication | Implement custom authentication for protected agent access”
   • [claimed-docs] “Implement custom authentication for protected agent access”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://api.elevenlabs.io/v1/mcp returned HTT…”

   proof ↗⚑ flag

   telli—none0/10

   telli documents a single API key (bearer token) generated in Settings > Developer, but there's no evidence of scoped permissions, role-based keys, or least-privilege credential issuance for agents specifically.

   • [claimed-docs] “All endpoints authenticate with an API key from the telli app (Settings > Developer), sent as a bearer token”

   proof ↗⚑ flag

8. ai-native userBuild against official SDKs

   weight 2 · round to telli
   ElevenLabs Agents~partialprobed4/10

   Docs confirm programmatic access via the ElevenLabs API and an official CLI (`@elevenlabs/cli`, verified runtime) for building agents, but no evidence pack item explicitly documents a first-party language SDK (Python/Node/etc.) for Agents beyond the generic API reference. Missing for 10: explicit official SDK docs/repos, SDK code examples, and independent confirmation of SDK feature parity with the API.

   • [claimed-docs] “ElevenLabs Agents are managed either through the ElevenAgents dashboard, the ElevenLabs API, the Agents CLI or the hosted MCP server.”
   • [claimed-docs] “we'll start by creating an agent via the API or the web dashboard”
   • [probe] “PROBE runtime (recorded 2026-09-05): `npx -y @elevenlabs/cli --version` printed `elevenlabs 1.1.0` keylessly — the official ElevenLabs CLI (…”

   proof ↗⚑ flag

   telli~partialprobed5/10

   telli provides a REST API with an OpenAPI spec that can be used to generate client libraries, plus webhooks, custom tools, and an MCP server for agent integration, but there is no evidence of telli-maintained official SDKs in specific languages (e.g., Python/JS packages published by telli) — only self-generated clients from the OpenAPI spec. missing for 10: dedicated first-party SDK packages/repos, language-specific SDK documentation, versioning/release notes for such SDKs.

   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”
   • [claimed-docs] “All endpoints authenticate with an API key from the telli app (Settings > Developer), sent as a bearer token”
   • [claimed-docs] “Download them to generate client libraries, import the API into tools like Postman, or give coding agents machine-readable API context”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.telli.com/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

9. ai-native userSubscribe to events via webhooks

   weight 2 · round to telli
   ElevenLabs Agents—none0/10

   The evidence describes 'webhook tools' that let an agent make outbound calls to external endpoints during a conversation (docs-14, docs-29, docs-31), which is the opposite of subscribing to platform-emitted events via webhooks. There is no documented mechanism for a developer to register a webhook URL to receive event notifications (e.g., conversation-ended, call-completed) from ElevenLabs Agents.

   • [claimed-docs] “Tools give your assistant the ability to make external function calls to third party apps so you can get real-time information.”
   • [claimed-docs] “Tools allow ElevenLabs agents to perform actions beyond generating text responses.”
   • [claimed-docs] “allow an assistant to trigger authenticated actions based on the conversation, like scheduling meetings or initiating order returns”

   proof ↗⚑ flag

   telli✓fullclaimed8/10

   telli documents a webhooks system that pushes real-time POST notifications about call events, status changes, and outcomes, explicitly described as event-driven subscription for external systems (telli-docs-13, telli-docs-21). Missing for 10: no evidence of configurable event-type filtering/subscription granularity or independent third-party confirmation of reliability.

   • [claimed-docs] “Webhooks: Receive real-time notifications about call events, status changes, and outcomes.”
   • [claimed-docs] “Webhooks push data from telli to your systems in real time. When something happens on a call, telli sends a POST request to the endpoint you…”
   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”

   proof ↗⚑ flag

Agentic features

1. ai-native userGet AI-generated insights and suggestions from my data inside the product

   weight 2 · round to telli
   ElevenLabs Agents~partialclaimed5/10

   Agent-analysis features (sentiment analysis, success evaluation, structured data extraction, semantic conversation search) generate AI-derived insights from the user's own conversation data, which partially satisfies the story. However, these are evaluation/reporting metrics rather than proactive AI-generated suggestions or recommendations for next actions, and there is no independent/hands-on corroboration of this analytics experience. Missing for 10: evidence of proactive suggestion generation (e.g., recommended actions/optimizations), a dashboard summarization view, and independent verification beyond first-party docs.

   • [claimed-docs] “Success evaluation: Define custom criteria to assess conversation quality, goal achievement, and customer satisfaction”
   • [claimed-docs] “Data collection: Extract specific data points from conversations such as contact information, issue details, or any structured information”
   • [claimed-docs] “Sentiment analysis: Understand user sentiment across completed conversations”
   • [claimed-docs] “Searching conversations: Find messages by keyword or meaning across your conversation history.”
   • [claimed-docs] “Define custom criteria to assess conversation quality, goal achievement, and customer satisfaction”
   • [claimed-docs] “Extract structured information from conversations such as contact details and business data”

   proof ↗⚑ flag

   telli~partialclaimed6/10

   telli ships a built-in AI assistant (Charlie) that can 'analyze your calls' and help build/refine agents, plus dashboards for reach rate, call duration, success rate, and per-call transcript/outcome analysis, which together provide AI-driven insight into product data. However, the docs don't detail proactive, autonomous 'suggestions' surfaced to the user (e.g., recommended actions, anomaly detection) beyond on-demand analysis via Charlie or manual dashboard review. Missing for 10: concrete examples of Charlie proactively surfacing insights/recommendations, independent user corroboration of insight quality.

   • [claimed-docs] “Charlie: Build and refine agents, automate workflows, and analyze your calls with telli's built-in AI assistant.”
   • [claimed-docs] “Track key metrics like reach rate, call duration, and success rate.”
   • [claimed-docs] “Analyze individual calls, transcripts, and call outcome fields.”
   • [claimed-docs] “Submit feedback on calls to continuously improve your agent.”

   proof ↗⚑ flag

2. ai-native userSet up automations that run autonomously in the background

   weight 2 · round to telli
   ElevenLabs Agents~partialclaimed4/10

   ElevenLabs Agents supports tool-calling, webhook actions, and multi-step workflows that let a voice agent perform actions (scheduling, API calls, MCP access) during a conversation, and agents can be created/managed via API for programmatic triggering, which give some automation flavor. But all documented action-taking is tied to a live conversational turn (voice/chat) rather than an autonomous background process that runs without a triggering conversation or human interaction, so the 'runs autonomously in the background' framing is only weakly supported. Missing for 10: evidence of scheduled/cron-triggered autonomous runs, evidence of multi-step tasks executing without a live conversation session, and independent confirmation of background automation outside the demoed conversational/tool-call flow.

   • [claimed-docs] “Build multi-step workflows with visual workflow builder”
   • [claimed-docs] “Enable agents to call clients & APIs to perform actions”
   • [claimed-docs] “Tools give your assistant the ability to make external function calls to third party apps so you can get real-time information.”
   • [claimed-docs] “allow an assistant to trigger authenticated actions based on the conversation, like scheduling meetings or initiating order returns”
   • [claimed-docs] “ElevenLabs allows you to connect your conversational agents to external MCP servers. This enables your agents to: Access and process informa…”
   • [claimed-docs] “we'll start by creating an agent via the API or the web dashboard”

   proof ↗⚑ flag

   telli✓fullclaimed7/10

   telli supports Scheduled triggers so workflows run automatically without a call event, plus retry/dialing-window configuration, webhooks, and an AI assistant (Charlie) to build/automate workflows — together enabling background autonomous automations. Missing for 10: independent/hands-on verification of scheduled automations running reliably in production, and more detail on monitoring/error-handling for autonomous runs beyond docs claims.

   • [claimed-docs] “Workflows can now run automatically on a recurring schedule. Add a Scheduled trigger, choose the interval and start time, and let the workfl…”
   • [claimed-docs] “Configure dialing windows, calling strategies, and retry behavior.”
   • [claimed-docs] “Charlie: Build and refine agents, automate workflows, and analyze your calls with telli's built-in AI assistant.”
   • [claimed-docs] “Webhooks: Receive real-time notifications about call events, status changes, and outcomes.”
   • [claimed-docs] “Schedules a call at the earliest opportunity within the dialer window. May occur immediately or on the next business day depending on settin…”

   proof ↗⚑ flag

3. ai-native userDelegate tasks to a built-in AI assistant inside the product

   weight 3 · round to telli
   ElevenLabs Agents~partialprobed5/10

   ElevenLabs documents a first-party hosted MCP server letting an assistant like Claude create, configure, and manage agents in the workspace via natural language, with nothing to install locally — a form of task delegation to an AI assistant for managing the product. However this is not a native in-product chat/assistant UI; it requires an external MCP client (e.g., Claude) to act as the assistant, and delegation is scoped to agent-management tasks rather than general product tasks. Missing for 10: a built-in assistant surface inside the ElevenLabs dashboard itself, evidence of broader task delegation beyond agent CRUD, and independent hands-on confirmation of the natural-language workflow.

   • [claimed-docs] “an assistant such as Claude can create, configure, and manage the agents in your workspace through natural language, with nothing to install…”
   • [claimed-docs] “an assistant such as Claude can create, configure, and manage the agents in your workspace through natural language”
   • [claimed-docs] “connect the hosted MCP server to Claude or any other MCP client to create and manage agents through natural language”
   • [claimed-docs] “create, configure, and manage the agents in your workspace through natural language, with nothing to install or run locally”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://api.elevenlabs.io/v1/mcp returned HTT…”

   proof ↗⚑ flag

   telli✓fullprobed8/10

   telli documents "Charlie," a built-in AI assistant that can build/refine agents, automate workflows, and analyze calls, and this assistant is also exposed via an MCP server for external AI tools to interact with. This directly matches delegating tasks to a built-in assistant within the product. Missing for 10: independent/hands-on verification of Charlie's task delegation in practice and more detail on the scope of tasks it can autonomously execute.

   • [claimed-docs] “Charlie: Build and refine agents, automate workflows, and analyze your calls with telli's built-in AI assistant.”
   • [claimed-docs] “The telli MCP server lets AI tools like Claude, ChatGPT, and Codex talk to Charlie, telli's AI assistant, over the Model Context Protocol.”
   • [probe] “official MCP server documented at https://docs.telli.com/integrations/mcp”

   proof ↗⚑ flag

4. ai-native userOperate the product with natural-language commands

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents✓fullprobed8/10

   ElevenLabs Agents ships a hosted MCP server explicitly designed so assistants like Claude can 'create, configure, and manage the agents in your workspace through natural language, with nothing to install or run locally,' and a runtime probe confirms the endpoint is live and speaks the MCP OAuth flow. This is a direct, first-party natural-language control surface, not just a client-side integration. Missing for 10: independent/community hands-on confirmation of a full natural-language agent-management session (only endpoint liveness was probed, not an actual successful NL task).

   • [claimed-docs] “an assistant such as Claude can create, configure, and manage the agents in your workspace through natural language, with nothing to install…”
   • [claimed-docs] “an assistant such as Claude can create, configure, and manage the agents in your workspace through natural language”
   • [claimed-docs] “connect the hosted MCP server to Claude or any other MCP client to create and manage agents through natural language”
   • [claimed-docs] “create, configure, and manage the agents in your workspace through natural language, with nothing to install or run locally”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://api.elevenlabs.io/v1/mcp returned HTT…”
   • [probe] “official MCP server documented at https://elevenlabs.io/docs/eleven-agents/operate/hosted-mcp”

   proof ↗⚑ flag

   telli~partialprobed6/10

   telli offers Charlie, a built-in AI assistant that can build/refine agents, automate workflows, and analyze calls via natural language, plus an MCP server letting external AI tools (Claude, ChatGPT, Codex) converse with Charlie — both point to natural-language operation. However, most of the product surface (workflows, scheduling, dialing windows, phone number setup) is described as configured through UI/API rather than conversational commands, and there's no independent/hands-on evidence of Charlie's NL command scope or reliability. missing for 10: hands-on evidence of Charlie executing complex natural-language commands, documentation detailing the breadth of actions controllable purely via NL, independent corroboration beyond vendor docs.

   • [claimed-docs] “Charlie: Build and refine agents, automate workflows, and analyze your calls with telli's built-in AI assistant.”
   • [claimed-docs] “The telli MCP server lets AI tools like Claude, ChatGPT, and Codex talk to Charlie, telli's AI assistant, over the Model Context Protocol.”
   • [probe] “official MCP server documented at https://docs.telli.com/integrations/mcp”

   proof ↗⚑ flag

Api quality

1. ai-native userExplore an interactive API reference with runnable examples

   weight 2 · round to telli
   ElevenLabs Agents—none0/10

   The evidence pack contains extensive markdown documentation for ElevenLabs Agents (quickstart, customization, tools, etc.) but nothing describes an interactive API reference page with runnable/'try it' examples — no mention of a Swagger/OpenAPI explorer, live code sandbox, or embedded runnable snippets. Since ElevenLabs Agents exposes an API, this axis is applicable, but no evidence supports the specific capability.

   ⚑ flag

   telli~partialprobed5/10

   telli publishes an OpenAPI spec (openapi.json) and API docs with downloadable schemas for generating client libraries or feeding coding agents, but there is no evidence of an interactive reference with runnable/'try it' examples in-browser. missing for 10: an interactive try-it console, live runnable code samples, or sandboxed request execution within the docs site.

   • [claimed-docs] “Download them to generate client libraries, import the API into tools like Postman, or give coding agents machine-readable API context”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.telli.com/openapi.json — contains "openapi" key”
   • [claimed-docs] “All endpoints authenticate with an API key from the telli app (Settings > Developer), sent as a bearer token”

   proof ↗⚑ flag

2. ai-native userDownload a machine-readable API spec (OpenAPI or equivalent)

   weight 2 · round to telli
   ElevenLabs Agents—none0/10

   The evidence pack documents the API, CLI, dashboard, and hosted MCP server for ElevenLabs Agents, but nowhere mentions a downloadable OpenAPI/Swagger spec or machine-readable schema for the API. This axis clearly applies to an API-driven product, but no evidence shows it being delivered.

   ⚑ flag

   telli✓fullprobed9/10

   telli provides a downloadable OpenAPI spec confirmed live at /openapi.json, and docs explicitly state it can be downloaded to generate client libraries, import into tools, or give coding agents machine-readable API context. Missing for 10: no independent third-party confirmation of spec completeness/versioning beyond first-party docs and probe.

   • [claimed-docs] “Download them to generate client libraries, import the API into tools like Postman, or give coding agents machine-readable API context”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.telli.com/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

3. ai-native userTest against a sandbox environment without touching production data

   weight 1 · round drawn
   ElevenLabs Agents~partialclaimed4/10

   Docs describe an 'agent testing' feature to verify conversational responses, tool usage, and multi-turn outcomes 'before you deploy', implying a pre-production test workflow, and tool execution can run in a 'sandboxed environment' on ElevenLabs' infrastructure. However there is no explicit documentation of a separate sandbox/staging environment or test data isolation from production conversation/analytics data. Missing for 10: explicit sandbox/staging environment separate from production data, documentation of test-vs-prod data isolation, independent confirmation that test runs don't affect production analytics or logs.

   • [claimed-docs] “Agent testing lets you verify conversational responses, tool usage, and full multi-turn outcomes before you deploy.”
   • [claimed-docs] “Agent testing lets you verify conversational responses, tool usage, and full multi-turn outcomes before you deploy”
   • [claimed-docs] “Custom JavaScript executed in a sandboxed environment on ElevenLabs' infrastructure.”
   • [claimed-docs] “Custom JavaScript executed in a sandboxed environment on ElevenLabs' infrastructure”

   proof ↗⚑ flag

   telli~partialclaimed4/10

   telli's agent builder includes a 'Test call' feature that lets users dial a draft or saved agent version and review the recording/transcript before going live, which functions as a lightweight test mode (telli-docs-28, telli-docs-29). However, there is no documentation of a dedicated sandbox environment, separate test dataset, or explicit guarantee that test calls don't write to production contacts/analytics. missing for 10: explicit sandbox/staging environment separate from production, confirmation that test calls don't affect production data/metrics, and any mention of test API keys or isolated test accounts.

   • [claimed-docs] “In the agent builder, click Test call to open the dialog. Pick the agent version (your draft with unsaved changes or any saved revision)...”
   • [claimed-docs] “Use the side-by-side view to listen to the recording while following along in the transcript.”

   proof ↗⚑ flag

4. ai-native userRely on versioned APIs with a documented deprecation policy

   weight 2 · round drawn
   ElevenLabs Agents—none0/10

   No evidence in the pack mentions API versioning scheme, version numbers, or any documented deprecation policy for ElevenLabs Agents' API/CLI/MCP interfaces. missing for 10: versioned API endpoints or version headers, changelog/release notes, explicit deprecation policy or sunset timelines, migration guides for breaking changes.

   ⚑ flag

   telli—none0/10

   Evidence shows an OpenAPI spec and API key auth exist, but nothing in the pack mentions API versioning (e.g., v1/v2 paths, version headers) or any documented deprecation/sunset policy for endpoints. Missing for 10: explicit API version scheme, changelog of breaking changes, and a stated deprecation/sunset policy.

   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”
   • [claimed-docs] “All endpoints authenticate with an API key from the telli app (Settings > Developer), sent as a bearer token”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.telli.com/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

1. ai-native userPerform bulk operations across many items at once

   weight 2 · round to telli
   ElevenLabs Agents—none0/10

   The evidence documents API, CLI, and MCP-based management of agents, but nothing describes bulk/batch operations (e.g., batch-create, batch-update, or batch-delete across many agents or conversations at once). This axis is fair to ask given the product exposes an API and CLI, but no evidence confirms bulk-operation support.

   ⚑ flag

   telli~partialprobed6/10

   Telli's platform is built around calling large contact lists (dialing windows, calling strategies, retry behavior, reach-rate metrics) and its REST API lets users 'programmatically manage contacts, schedule calls' at scale, implying bulk campaign operations. However, there is no explicit documentation of a bulk-upload/bulk-schedule endpoint or UI for acting on many items simultaneously — the schedule-call endpoint documented is single-call oriented. Missing for 10: explicit bulk-contact import/schedule endpoint, documented batch size limits, and independent evidence of large-scale bulk execution.

   • [claimed-docs] “Configure dialing windows, calling strategies, and retry behavior.”
   • [claimed-docs] “Track key metrics like reach rate, call duration, and success rate.”
   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”
   • [claimed-docs] “Schedules a call at the earliest opportunity within the dialer window. May occur immediately or on the next business day depending on settin…”
   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.telli.com/llms.txt # telli Documentation > telli is the AI voice platform for agents that sell, su…”

   proof ↗⚑ flag

2. ai-native userDefine rules that trigger actions automatically on events

   weight 3 · round to ElevenLabs Agents
   ElevenLabs Agents~partialclaimed6/10

   ElevenLabs Agents supports tool-calling and webhook actions that are triggered automatically based on conversation events (e.g., 'trigger authenticated actions based on the conversation, like scheduling meetings or initiating order returns'), plus multi-step visual workflows and MCP-based external actions. This covers event-triggered automation within a conversation but the evidence doesn't show general rule-based triggers on arbitrary system events (e.g., scheduled/external triggers outside a live conversation) — missing for 10: documentation of standalone event/rule engine independent of a live conversation, examples of conditional branching logic beyond tool calls, and independent verification of automation reliability.

   • [claimed-docs] “Enable agents to call clients & APIs to perform actions”
   • [claimed-docs] “Tools give your assistant the ability to make external function calls to third party apps so you can get real-time information.”
   • [claimed-docs] “allow an assistant to trigger authenticated actions based on the conversation, like scheduling meetings or initiating order returns”
   • [claimed-docs] “Build multi-step workflows with visual workflow builder”
   • [claimed-docs] “ElevenLabs allows you to connect your conversational agents to external MCP servers. This enables your agents to: Access and process informa…”

   proof ↗⚑ flag

   telli~partialclaimed5/10

   telli's workflows can be triggered by call events (implied default) and now by a recurring schedule, and webhooks notify external systems on call events, showing some event-driven automation. However there's no documented rule-definition interface (conditions, event-type selection, if/then logic) for arbitrary events beyond calls/schedule. Missing for 10: explicit rule/condition builder, broader event-type coverage beyond calls, and evidence of user-defined trigger logic rather than fixed schedule/call triggers.

   • [claimed-docs] “Workflows can now run automatically on a recurring schedule. Add a Scheduled trigger, choose the interval and start time, and let the workfl…”
   • [claimed-docs] “Webhooks: Receive real-time notifications about call events, status changes, and outcomes.”
   • [claimed-docs] “Webhooks push data from telli to your systems in real time. When something happens on a call, telli sends a POST request to the endpoint you…”

   proof ↗⚑ flag

3. ai-native userSchedule recurring jobs or workflows

   weight 2 · round to telli
   ElevenLabs Agents—none0/10

   The evidence pack covers multi-step workflow building, tool calling, MCP integration, and analysis, but no documentation mentions scheduling recurring jobs, cron-like triggers, or automated recurring workflow execution. This is a fair capability to expect from an automation-focused agent platform, but no evidence supports it.

   ⚑ flag

   telli✓fullclaimed7/10

   telli documents scheduled triggers that let workflows run recurringly on an interval/start time without a call event, directly matching the recurring-workflow story, and also supports scheduling individual calls via API. missing for 10: independent/hands-on corroboration of recurrence reliability and detail on editing/monitoring scheduled workflow runs.

   • [claimed-docs] “Workflows can now run automatically on a recurring schedule. Add a Scheduled trigger, choose the interval and start time, and let the workfl…”
   • [claimed-docs] “Schedules a call at the earliest opportunity within the dialer window. May occur immediately or on the next business day depending on settin…”
   • [claimed-docs] “Optional flag to bypass dialing window restrictions for the scheduled call. When true, calls at the scheduled time regardless of dialing win…”

   proof ↗⚑ flag

4. ai-native userVersion, review, and roll back my automations

   weight 1 · round to telli
   ElevenLabs Agents—none0/10

   The docs describe building, testing, and analyzing agents (agent-testing, agent-analysis) but there is no mention of version history, change review workflows, or rollback/revert capability for agent configurations. Missing for 10: version history UI, rollback/restore of prior agent configs, change-review/approval workflow, audit trail of edits.

   ⚑ flag

   telli~partialclaimed3/10

   The only hint of versioning is in agent testing, where you can pick 'your draft with unsaved changes or any saved revision' (telli-docs-28), implying saved agent versions exist. However there is no documented review interface for comparing versions, no explicit rollback/restore action, and no versioning mentioned for broader automations/workflows (only agents). Missing for 10: explicit rollback UI/API, version diff/review tooling, and versioning coverage for workflows beyond agent test calls.

   • [claimed-docs] “In the agent builder, click Test call to open the dialog. Pick the agent version (your draft with unsaved changes or any saved revision)...”

   proof ↗⚑ flag

Compliance

1. founderMeet call-recording consent and disclosure obligations with per-call recording controls and configurable data retention

   weight 2 · round to telli
   ElevenLabs Agents~partialclaimed4/10

   Docs confirm configurable data-retention settings for conversation transcripts and audio recordings, which addresses the retention half of the story, plus HIPAA/BAA support suggesting compliance posture. However, there is no evidence of per-call recording enable/disable controls or built-in consent/disclosure messaging mechanisms for calls. Missing for 10: per-call recording toggle, consent/disclosure prompt configuration, and any independent verification of retention enforcement.

   • [claimed-docs] “Retention settings allow you to configure how long your conversational agent stores conversation transcripts and audio recordings.”
   • [claimed-docs] “Retention settings allow you to configure how long your conversational agent stores conversation transcripts and audio recordings”
   • [claimed-docs] “ElevenLabs allows such customers to develop AI-powered voice agents for the handling Protected Health Information (PHI)”
   • [claimed-docs] “ElevenLabs Agents is one of ElevenLabs' HIPAA-eligible services, and we offer Business Associate Agreements (BAAs) to eligible customers”

   proof ↗⚑ flag

   telli~partialclaimed6/10

   telli documents conditional recording based on caller consent and a configurable data-retention policy that auto-deletes contacts and call data after a defined age, directly addressing the founder's compliance need. However, evidence lacks detail on per-call granular controls (e.g., pause/resume, jurisdiction-specific disclosure scripts), audit logging of consent events, or independent verification that these features work as described. Missing for 10: per-call recording toggle/audit trail details, jurisdiction-specific disclosure templates, retention configuration granularity (e.g., per-data-type settings), and independent/hands-on confirmation of compliance behavior.

   • [claimed-docs] “Data retention deletes contacts and call data automatically once they reach an age you define.”
   • [claimed-docs] “In telli, you can easily make audio recording conditional on the caller's consent — so a call is only recorded once they agree.”

   proof ↗⚑ flag

2. platform-engineerRun regulated workloads with HIPAA/BAA support, SOC 2, and data-residency options

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents~partialclaimed5/10

   ElevenLabs Agents documents HIPAA eligibility and BAA availability for eligible customers, directly supporting regulated PHI workloads. However, there is no evidence in the pack of SOC 2 certification or data-residency options, both explicitly named in the story. Missing for 10: SOC 2 attestation/report evidence, data-residency region selection or documentation, independent audit corroboration of HIPAA/BAA claims.

   • [claimed-docs] “ElevenLabs allows such customers to develop AI-powered voice agents for the handling Protected Health Information (PHI)”
   • [claimed-docs] “ElevenLabs allows such customers to develop AI-powered voice agents for the handling Protected Health Information (PHI).”
   • [claimed-docs] “ElevenLabs Agents is one of ElevenLabs' HIPAA-eligible services, and we offer Business Associate Agreements (BAAs) to eligible customers”

   proof ↗⚑ flag

   telli—none0/10

   No evidence in the pack mentions HIPAA, BAA, SOC 2, or data-residency options; only data retention and consent-based recording are covered, which don't establish formal compliance certifications.

   ⚑ flag

Scale

1. platform-engineerSee documented concurrency limits and scale to many simultaneous calls without manual capacity begging

   weight 2 · round drawn
   ElevenLabs Agents—none0/10

   No evidence pack item documents concurrency limits, per-account call caps, autoscaling behavior, or a process for scaling to many simultaneous calls without contacting sales/support; docs cover features like tools, voice customization, SIP trunking, HIPAA, and MCP but nothing on capacity/scale numbers or self-service scaling guarantees.

   ⚑ flag

   telli—none0/10

   No evidence pack item documents concurrency limits, per-account call caps, or scaling guarantees for simultaneous calls; docs mention dialing windows/retry strategy but not concurrency ceilings or auto-scaling behavior. This is a fair question for a voice-calling platform (scaling many simultaneous calls is core to the product's value), so 'none' applies rather than 'na'.

   ⚑ flag

Self host

1. platform-engineerSelf-host the voice agent runtime from open-source code on my own infrastructure

   weight 3 · round drawn
   ElevenLabs Agents—none0/10

   ElevenLabs Agents is entirely a managed/hosted service — the CLI and MCP server are clients/interfaces to ElevenLabs' cloud infrastructure, not open-source runtime code that can be deployed on a platform-engineer's own servers. Nothing in the evidence pack mentions open-sourcing the runtime, self-hosting instructions, or on-prem deployment options; all references (dashboard, API, CLI, hosted MCP, SIP trunking) point to ElevenLabs-operated infrastructure.

   • [claimed-docs] “ElevenLabs Agents are managed either through the ElevenAgents dashboard, the ElevenLabs API, the Agents CLI or the hosted MCP server.”
   • [claimed-docs] “an assistant such as Claude can create, configure, and manage the agents in your workspace through natural language, with nothing to install…”
   • [claimed-docs] “create, configure, and manage the agents in your workspace through natural language, with nothing to install or run locally”
   • [probe] “PROBE runtime (recorded 2026-09-05): `npx -y @elevenlabs/cli --version` printed `elevenlabs 1.1.0` keylessly — the official ElevenLabs CLI (…”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://api.elevenlabs.io/v1/mcp returned HTT…”

   proof ↗⚑ flag

   telli—none0/10

   The axis applies to this product kind (peer products hold positive or none verdicts on this story), so lack of evidence for an applicable capability is "none", never "na". (na/none harmonized at arena bring-up — see pipeline/scripts/na-harmonize.ts.)

   ⚑ flag

Latency

1. platform-engineerSee documented end-to-end voice latency numbers or tuning guidance backing the platform's speed claims

   weight 3 · round to ElevenLabs Agents
   ElevenLabs Agents~partialclaimed4/10

   ElevenLabs markets 'ultra-low latency' (docs-37) and does document conversation-flow tuning knobs like turn-taking, interruption handling and timeouts (docs-33, docs-42, docs-19/49/54), which counts as tuning guidance for latency/turn-taking behavior. However there are no documented end-to-end latency benchmark numbers (e.g., ms figures, percentile breakdowns) anywhere in the evidence pack. Missing for 10: concrete latency benchmark numbers/metrics, methodology for measuring end-to-end latency, and any independent corroboration of the 'ultra-low latency' marketing claim.

   • [claimed-docs] “Configure, deploy and monitor natural, human-sounding agents in 70+ languages with leading accuracy and ultra-low latency across voice or ch…”
   • [claimed-docs] “Conversation flow settings determine how your assistant handles periods of user silence, interruptions during speech, and turn-taking behavi…”
   • [claimed-docs] “Configure turn-taking, interruptions, and timeout settings”
   • [claimed-docs] “The Max conversation duration setting limits the total time a conversation can remain active. ... The default is 600 seconds (10 minutes).”

   proof ↗⚑ flag

   telli—none0/10

   No evidence pack item mentions latency numbers, turn-taking performance, or tuning guidance for voice response speed; documentation covers workflows, API, webhooks, and agent building but nothing on end-to-end latency benchmarks or tuning.

   ⚑ flag

Turn taking

1. developerRely on the agent to handle interruptions (barge-in) gracefully — stopping speech, updating context, and recovering the turn

   weight 3 · round to ElevenLabs Agents
   ElevenLabs Agents~partialclaimed6/10

   Docs explicitly document configuring turn-taking, interruptions, and timeout settings, and conversation-flow settings that 'determine how your assistant handles periods of user silence, interruptions during speech, and turn-taking behavior,' confirming barge-in handling is a first-class configurable feature. However, evidence lacks detail on how context is updated after an interruption or how turn recovery specifically behaves, and there's no hands-on/independent validation of graceful recovery in practice. Missing for 10: technical detail on context truncation/update after interruption, independent or hands-on testing confirming graceful recovery, and latency benchmarks for barge-in specifically.

   • [claimed-docs] “Conversation flow settings determine how your assistant handles periods of user silence, interruptions during speech, and turn-taking behavi…”
   • [claimed-docs] “Configure turn-taking, interruptions, and timeout settings”
   • [claimed-docs] “The Max conversation duration setting limits the total time a conversation can remain active. ... The default is 600 seconds (10 minutes).”

   proof ↗⚑ flag

   telli—none0/10

   No evidence in the pack addresses barge-in, interruption handling, speech-stopping, or turn recovery mechanics; the docs cover scheduling, workflows, analytics, and integrations but never mention conversational turn-taking behavior.

   ⚑ flag

2. developerEnable noise suppression or audio filtering so the agent stays coherent on noisy real-world calls

   weight 1 · round drawn
   ElevenLabs Agents—none0/10

   The evidence pack covers voice customization, turn-taking/interruption settings, tools, testing, and telephony (SIP) integration, but nowhere mentions noise suppression, background noise handling, or audio filtering for noisy real-world calls. This is a fair capability to expect for a voice-agent platform handling phone calls, but no documentation or feature reference confirms it exists.

   • [claimed-docs] “Conversation flow settings determine how your assistant handles periods of user silence, interruptions during speech, and turn-taking behavi…”
   • [claimed-docs] “Configure turn-taking, interruptions, and timeout settings”
   • [claimed-docs] “This integration enables all customers to use their existing phone systems while leveraging ElevenLabs' advanced voice AI capabilities.”

   proof ↗⚑ flag

   telli—none0/10

   No evidence pack item mentions noise suppression, audio filtering, or any mechanism for handling noisy call environments; documentation covers scheduling, workflows, analytics, and voice cloning but not audio quality/noise handling.

   ⚑ flag

3. developerUse model-based end-of-turn detection beyond simple VAD silence timeouts so the agent doesn't talk over slow speakers

   weight 2 · round drawn
   ElevenLabs Agents—none0/10

   Docs mention configurable turn-taking, interruption handling, and timeout settings (docs-33, docs-42), but nothing in the evidence describes a model-based end-of-turn detector that goes beyond a VAD/silence-timeout mechanism — no mention of semantic or ML-based turn-completion detection to avoid interrupting slow speakers. Missing for 10: any documentation of a dedicated end-of-turn prediction model, benchmarks or comparisons versus simple VAD timeouts, or hands-on evidence that the agent waits appropriately for slow speakers.

   • [claimed-docs] “Conversation flow settings determine how your assistant handles periods of user silence, interruptions during speech, and turn-taking behavi…”
   • [claimed-docs] “Configure turn-taking, interruptions, and timeout settings”
   • [claimed-docs] “The Max conversation duration setting limits the total time a conversation can remain active. ... The default is 600 seconds (10 minutes).”

   proof ↗⚑ flag

   telli—none0/10

   No evidence in the pack discusses turn-taking, end-of-turn detection, VAD, or interruption handling in telli's voice agent; the docs cover scheduling, workflows, tools, and integrations but not conversational latency/turn-taking mechanics.

   ⚑ flag

1. ai-native userDo everything through the API that I can do in the UI

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents~partialprobed7/10

   Docs show agents can be created, configured, and managed via the API, CLI, dashboard, or hosted MCP server, and quickstart explicitly says agents can be created 'via the API or the web dashboard,' implying broad parity across surfaces (elevenlabs-agents-docs-1, docs-39, docs-44). However, there's no explicit feature-by-feature confirmation that every dashboard capability (e.g., visual workflow builder, analytics dashboards, testing UI) has a full API equivalent, nor independent verification of parity. Missing for 10: an explicit parity statement or changelog confirming all dashboard features (workflow builder, analytics, testing suite) are fully scriptable via API, and independent/hands-on confirmation of that parity.

   • [claimed-docs] “ElevenLabs Agents are managed either through the ElevenAgents dashboard, the ElevenLabs API, the Agents CLI or the hosted MCP server.”
   • [claimed-docs] “we'll start by creating an agent via the API or the web dashboard”
   • [claimed-docs] “create, configure, and manage the agents in your workspace through natural language, with nothing to install or run locally”
   • [claimed-docs] “Build multi-step workflows with visual workflow builder”
   • [probe] “PROBE runtime (recorded 2026-09-05): `npx -y @elevenlabs/cli --version` printed `elevenlabs 1.1.0` keylessly — the official ElevenLabs CLI (…”

   proof ↗⚑ flag

   telli~partialprobed6/10

   telli exposes a REST API (with OpenAPI spec) covering contacts, scheduling calls, phone number import, custom tools, and webhooks, and also offers an MCP server so external AI tools can interact with Charlie. However, several UI-native features—agent builder/test-call dialog, live monitoring dashboard, side-by-side transcript/recording view, voice cloning setup, workflow trigger/recurring schedule configuration UI, and analytics dashboards—are not documented as API-accessible endpoints, so full UI/API parity is not evidenced. missing for 10: API endpoints for agent building/testing, live monitoring, voice cloning, workflow scheduling configuration, and analytics/reporting equivalent to UI dashboards.

   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”
   • [claimed-docs] “All endpoints authenticate with an API key from the telli app (Settings > Developer), sent as a bearer token”
   • [claimed-docs] “Download them to generate client libraries, import the API into tools like Postman, or give coding agents machine-readable API context”
   • [claimed-docs] “Schedules a call at the earliest opportunity within the dialer window. May occur immediately or on the next business day depending on settin…”
   • [claimed-docs] “Imports a phone number from your own SIP trunk provider. This allows you to use existing phone numbers with telli by configuring custom SIP …”
   • [claimed-docs] “Custom tools allow your AI agents to access external information by connecting to your APIs.”
   • [claimed-docs] “Webhooks push data from telli to your systems in real time. When something happens on a call, telli sends a POST request to the endpoint you…”
   • [claimed-docs] “The telli MCP server lets AI tools like Claude, ChatGPT, and Codex talk to Charlie, telli's AI assistant, over the Model Context Protocol.”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.telli.com/openapi.json — contains "openapi" key”
   • [probe] “official MCP server documented at https://docs.telli.com/integrations/mcp”

   proof ↗⚑ flag

2. ai-native userExport all of my data in open formats and leave

   weight 3 · round drawn
   ElevenLabs Agents—none0/10

   No evidence describes a data export feature, open-format data dumps, or account deletion/portability tooling; only conversation retention settings are documented, not export mechanisms. Missing for 10: any documented export API/CLI command, supported open export formats (e.g., JSON/CSV), and confirmation of full data portability/account closure process.

   ⚑ flag

   telli—none0/10

   No evidence of a bulk data-export feature or open-format data portability; only API endpoints to manage/read specific records and a data-retention deletion policy are documented, not a full self-service export/leave capability. Missing for 10: documented full-account export tool/endpoint, open-format (CSV/JSON) bulk export, and any explicit data-portability statement.

   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”
   • [claimed-docs] “Data retention deletes contacts and call data automatically once they reach an age you define.”

   proof ↗⚑ flag

3. ai-native userRead the product's source under an open license

   weight 2 · round drawn
   ElevenLabs Agents—none0/10

   ElevenLabs Agents is a closed, proprietary SaaS product; the CLI is open on npm but no evidence indicates the core Agents platform/backend source is available under an open license. No license file, GitHub repo, or open-source statement is present in the evidence pack.

   ⚑ flag

   telli—none0/10

   The axis applies to this product kind (peer products hold positive or none verdicts on this story), so lack of evidence for an applicable capability is "none", never "na". (na/none harmonized at arena bring-up — see pipeline/scripts/na-harmonize.ts.)

   ⚑ flag

4. ai-native userSelf-host the core product

   weight 3 · round drawn
   ElevenLabs Agents—none0/10

   ElevenLabs Agents is entirely a hosted SaaS product—managed via dashboard, API, CLI, and hosted MCP server, all pointing to ElevenLabs' own infrastructure; there is no evidence of an open-source release, downloadable server binary, or self-hosting option for the core voice-agent runtime. missing for 10: any open-source repo or self-hosted deployment package, docs describing running the core service on one's own infrastructure, independent confirmation of self-hosting.

   • [claimed-docs] “ElevenLabs Agents are managed either through the ElevenAgents dashboard, the ElevenLabs API, the Agents CLI or the hosted MCP server.”
   • [claimed-docs] “an assistant such as Claude can create, configure, and manage the agents in your workspace through natural language, with nothing to install…”
   • [claimed-docs] “create, configure, and manage the agents in your workspace through natural language, with nothing to install or run locally”

   proof ↗⚑ flag

   telli—none0/10

   The axis applies to this product kind (peer products hold positive or none verdicts on this story), so lack of evidence for an applicable capability is "none", never "na". (na/none harmonized at arena bring-up — see pipeline/scripts/na-harmonize.ts.)

   ⚑ flag

Pricing

1. founderSee published per-minute or usage pricing and estimate cost per call before committing

   weight 2 · round drawn
   ElevenLabs Agents—none0/10

   No evidence item in the pack references pricing, per-minute rates, usage-based billing, or cost calculators for ElevenLabs Agents; all citations are product/docs feature descriptions. Since founders evaluating a voice-agent SaaS could reasonably expect published pricing, the axis applies but is entirely unaddressed in this evidence pack.

   ⚑ flag

   telli—none0/10

   No evidence in the pack mentions pricing, per-minute rates, usage costs, or any cost calculator/estimator; the docs cover features (workflows, appointments, API, MCP, etc.) but nothing about published pricing.

   ⚑ flag

1. ai-native userChoose where my data is stored (region/residency)

   weight 2 · round drawn
   ElevenLabs Agents—none0/10

   Evidence covers data retention duration settings, HIPAA/BAA eligibility, and infrastructure details, but nothing addresses selectable data region/residency options for storage location. missing for 10: any mention of region selection, data residency controls, or geographic storage options.

   • [claimed-docs] “Retention settings allow you to configure how long your conversational agent stores conversation transcripts and audio recordings.”
   • [claimed-docs] “Retention settings allow you to configure how long your conversational agent stores conversation transcripts and audio recordings”
   • [claimed-docs] “ElevenLabs Agents is one of ElevenLabs' HIPAA-eligible services, and we offer Business Associate Agreements (BAAs) to eligible customers”

   proof ↗⚑ flag

   telli—none0/10

   No evidence in the pack mentions data residency, region selection, or data storage location controls; data retention (deletion timing) is covered but that is a different capability from choosing storage region.

   ⚑ flag

2. ai-native userPrevent my data from being used to train AI models

   weight 3 · round drawn
   ElevenLabs Agents—none0/10

   The evidence pack covers data retention settings (how long transcripts/audio are stored) and HIPAA/BAA compliance, but nowhere mentions an explicit opt-out or policy regarding use of customer data/conversations for AI model training. missing for 10: explicit training-data opt-out policy or setting, terms-of-service language on model training use, any statement distinguishing enterprise vs free-tier data usage for training.

   • [claimed-docs] “Retention settings allow you to configure how long your conversational agent stores conversation transcripts and audio recordings.”
   • [claimed-docs] “Retention settings allow you to configure how long your conversational agent stores conversation transcripts and audio recordings”
   • [claimed-docs] “ElevenLabs Agents is one of ElevenLabs' HIPAA-eligible services, and we offer Business Associate Agreements (BAAs) to eligible customers”

   proof ↗⚑ flag

   telli—none0/10

   No evidence in the pack addresses AI training data usage or opt-out policies; data retention docs cover deletion of contacts/call data but not model-training exclusion.

   ⚑ flag

3. ai-native userControl data retention and deletion

   weight 2 · round drawn
   ElevenLabs Agents~partialclaimed6/10

   Docs explicitly document configurable retention settings for conversation transcripts and audio recordings, giving users control over how long data is stored. However, evidence does not detail a deletion mechanism (e.g., data subject deletion requests, API/CLI commands to purge stored data) beyond retention duration settings. Missing for 10: explicit deletion/export controls, granular per-conversation deletion API, and independent verification of retention enforcement.

   • [claimed-docs] “Retention settings allow you to configure how long your conversational agent stores conversation transcripts and audio recordings.”
   • [claimed-docs] “Retention settings allow you to configure how long your conversational agent stores conversation transcripts and audio recordings”

   proof ↗⚑ flag

   telli~partialclaimed6/10

   telli documents automatic data retention deletion (contacts and call data purged once they reach a defined age) and conditional consent-based recording, giving users some control over data lifecycle and privacy. However, there's no evidence of user-initiated manual deletion, export/right-to-access tools, or granular per-record deletion controls beyond the age-based policy. missing for 10: manual/on-demand deletion controls, data export capability, independent verification of retention enforcement.

   • [claimed-docs] “Data retention deletes contacts and call data automatically once they reach an age you define.”
   • [claimed-docs] “In telli, you can easily make audio recording conditional on the caller's consent — so a call is only recorded once they agree.”

   proof ↗⚑ flag

4. ai-native userOpt out of telemetry and usage tracking

   weight 2 · round drawn
   ElevenLabs Agents—none0/10

   The evidence pack covers conversation transcript/audio retention settings (docs-26, docs-52) but nothing about opting out of product telemetry or usage tracking (e.g., CLI analytics, dashboard usage metrics) for the AI-native user. Retention configuration is about customer conversation data, not the vendor's own telemetry collection, so this axis has no supporting evidence.

   ⚑ flag

   telli—none0/10

   telli is a voice-agent platform, not a developer tool where telemetry opt-out is typically discussed, but the axis is still fair to ask (does the product track usage, and can a user disable it). The evidence pack (data retention, consent-based recording, etc.) never mentions any telemetry/usage-tracking opt-out mechanism for the product itself. Missing for 10: any documentation of telemetry collection practices or an opt-out setting/toggle.

   ⚑ flag

Call control

1. developerEscalate a live call to a human with warm or blind transfer, passing context along

   weight 2 · round to telli
   ElevenLabs Agents—none0/10

   The evidence pack covers telephony features like SIP trunking, tools, webhooks, and MCP integrations, but nowhere documents call transfer (warm or blind) to a human agent or passing conversation context during handoff. Missing for 10: any mention of transfer_to_number/transfer_to_agent tool types, warm/blind transfer configuration, or context-passing during escalation.

   ⚑ flag

   telli~partialclaimed4/10

   Docs confirm a transfer tool that can move a call to another agent or number, matching the core escalation-to-human idea, but there's no mention of distinct warm vs. blind transfer modes or explicit context-passing to the human recipient. missing for 10: explicit warm/blind transfer distinction, evidence of context/data hand-off during transfer, hands-on confirmation of the feature in practice.

   • [claimed-docs] “Transfer tools | Move the call to another agent or number.”

   proof ↗⚑ flag

2. developerMy agent can send DTMF keypresses, navigate IVR menus, and detect or leave voicemail

   weight 1 · round drawn
   ElevenLabs Agents—none0/10

   The evidence pack confirms ElevenLabs Agents supports telephony integration via SIP trunking and phone numbers, so the telephony axis clearly applies, but nothing in the docs mentions DTMF tone sending, IVR menu navigation, or voicemail detection/leaving capabilities.

   • [claimed-docs] “This integration enables all customers to use their existing phone systems while leveraging ElevenLabs' advanced voice AI capabilities.”
   • [claimed-docs] “Route calls to AI agents without changing your existing phone infrastructure”

   proof ↗⚑ flag

   telli—none0/10

   No evidence in the pack mentions DTMF keypress sending, IVR menu navigation, or voicemail detection/leaving; telli's docs cover scheduling, transfers, web search tool, and webhooks but nothing about touch-tone or answering machine handling.

   ⚑ flag

Campaigns

1. founderRun batch outbound call campaigns with scheduling and throughput controls

   weight 2 · round to telli
   ElevenLabs Agents—none0/10

   The evidence pack documents phone-number/SIP trunking integration for routing calls to agents, but contains no mention of batch outbound calling, campaign scheduling, or throughput/rate controls for outbound call volume. Since telephony campaign management is a fair capability to expect from a voice-agent telephony product, absence of evidence here is 'none' rather than 'na'.

   • [claimed-docs] “This integration enables all customers to use their existing phone systems while leveraging ElevenLabs' advanced voice AI capabilities.”
   • [claimed-docs] “Route calls to AI agents without changing your existing phone infrastructure”

   proof ↗⚑ flag

   telli~partialclaimed6/10

   telli documents dialing windows, calling strategies, and retry behavior (telli-docs-9) plus a schedule-call API endpoint that respects dialer windows or can bypass them (telli-docs-17, telli-docs-18) and reach-rate/success metrics (telli-docs-7), which together support scheduled, throughput-controlled outbound calling. However there is no explicit mention of a 'campaign' concept, bulk contact upload, or concurrency/rate limits for large batches. Missing for 10: explicit batch/campaign creation UI or endpoint, bulk contact import for calling, and documented concurrency/throughput limits beyond dialing windows.

   • [claimed-docs] “Configure dialing windows, calling strategies, and retry behavior.”
   • [claimed-docs] “Schedules a call at the earliest opportunity within the dialer window. May occur immediately or on the next business day depending on settin…”
   • [claimed-docs] “Optional flag to bypass dialing window restrictions for the scheduled call. When true, calls at the scheduled time regardless of dialing win…”
   • [claimed-docs] “Track key metrics like reach rate, call duration, and success rate.”
   • [claimed-docs] “Workflows can now run automatically on a recurring schedule. Add a Scheduled trigger, choose the interval and start time, and let the workfl…”

   proof ↗⚑ flag

Numbers

1. developerProvision phone numbers and run both inbound and outbound calls through the platform's API

   weight 3 · round to telli
   ElevenLabs Agents~partialclaimed6/10

   Docs confirm phone/telephony integration via SIP trunking, letting agents route inbound/outbound calls over existing phone infrastructure, and agents can be created/configured via the API. However, evidence does not explicitly show a documented API endpoint for provisioning new phone numbers or explicitly triggering outbound calls programmatically vs. via SIP trunk setup. Missing for 10: explicit phone-number provisioning API endpoint docs, explicit outbound-call-initiation API example, and independent/hands-on confirmation of inbound+outbound call flows.

   • [claimed-docs] “This integration enables all customers to use their existing phone systems while leveraging ElevenLabs' advanced voice AI capabilities.”
   • [claimed-docs] “Route calls to AI agents without changing your existing phone infrastructure”
   • [claimed-docs] “we'll start by creating an agent via the API or the web dashboard”

   proof ↗⚑ flag

   telli~partialprobed7/10

   telli's docs show a REST API with a schedule-call endpoint for outbound calls, an import-phone-number endpoint to bring SIP-trunk numbers under API control, webhooks for call events, and an OpenAPI spec confirming the API surface. However, inbound handling is documented mainly as manual forwarding/SIP trunk setup rather than a clear 'provision a new number via API' flow, and there's no explicit doc of purchasing/creating a fresh telli-hosted number through the API. missing for 10: a documented endpoint to provision/purchase brand-new phone numbers (not just import existing SIP trunk numbers), and clearer API-driven inbound call handling beyond forwarding.

   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”
   • [claimed-docs] “Schedules a call at the earliest opportunity within the dialer window. May occur immediately or on the next business day depending on settin…”
   • [claimed-docs] “Imports a phone number from your own SIP trunk provider. This allows you to use existing phone numbers with telli by configuring custom SIP …”
   • [claimed-docs] “Webhooks push data from telli to your systems in real time. When something happens on a call, telli sends a POST request to the endpoint you…”
   • [claimed-docs] “Keep your public business number and forward incoming calls to a telli number. You configure the forwarding with your phone provider or PBX.”
   • [claimed-docs] “Connect an existing number and phone system for incoming and outgoing calls. You need SIP trunk access from your provider.”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.telli.com/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

Sip

1. platform-engineerConnect my own carrier or PBX via SIP trunking (or import Twilio/Telnyx numbers) instead of being locked to bundled telephony

   weight 2 · round to telli
   ElevenLabs Agents~partialclaimed7/10

   Docs explicitly describe a SIP trunking integration that lets customers connect their existing phone systems/carrier infrastructure to ElevenLabs agents without changing carriers, directly addressing the core ask of bringing your own PBX/carrier. However, the pack has no explicit mention of importing existing Twilio/Telnyx numbers or detailed carrier onboarding steps, and no independent/hands-on confirmation of a live SIP trunk setup working end-to-end. Missing for 10: explicit Twilio/Telnyx number import instructions, and third-party/hands-on validation of the SIP trunking flow.

   • [claimed-docs] “This integration enables all customers to use their existing phone systems while leveraging ElevenLabs' advanced voice AI capabilities.”
   • [claimed-docs] “Route calls to AI agents without changing your existing phone infrastructure”

   proof ↗⚑ flag

   telli✓fullclaimed8/10

   Docs explicitly support importing numbers from a customer's own SIP trunk provider via a dedicated API endpoint, plus general SIP trunk connection for incoming/outgoing calls and call forwarding from an existing PBX/provider number. This directly matches the platform-engineer's need to bring their own carrier rather than being locked into bundled telephony. Missing for 10: no explicit mention of native Twilio/Telnyx number import (only generic SIP trunk import), and no independent/hands-on confirmation of the SIP trunk setup working in practice.

   • [claimed-docs] “Imports a phone number from your own SIP trunk provider. This allows you to use existing phone numbers with telli by configuring custom SIP …”
   • [claimed-docs] “Keep your public business number and forward incoming calls to a telli number. You configure the forwarding with your phone provider or PBX.”
   • [claimed-docs] “Connect an existing number and phone system for incoming and outgoing calls. You need SIP trunk access from your provider.”

   proof ↗⚑ flag

Analytics

1. ai-native userThe platform's AI reviews my calls for me — scoring quality, flagging failures, and analyzing resolution automatically

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents✓fullclaimed7/10

   Docs explicitly describe automated post-call analysis: 'Success evaluation' scores conversation quality/goal achievement, 'Sentiment analysis' flags user sentiment, and 'Data collection' extracts structured resolution details — directly matching the story's scoring/flagging/resolution-analysis ask. Missing for 10: no independent/hands-on validation of analysis accuracy, and no explicit 'failure flagging' terminology beyond success-criteria evaluation.

   • [claimed-docs] “Success evaluation: Define custom criteria to assess conversation quality, goal achievement, and customer satisfaction”
   • [claimed-docs] “Data collection: Extract specific data points from conversations such as contact information, issue details, or any structured information”
   • [claimed-docs] “Sentiment analysis: Understand user sentiment across completed conversations”
   • [claimed-docs] “Define custom criteria to assess conversation quality, goal achievement, and customer satisfaction”
   • [claimed-docs] “Extract structured information from conversations such as contact details and business data.”

   proof ↗⚑ flag

   telli~partialclaimed5/10

   telli provides analytics like reach rate, success rate, call outcome fields, transcripts, and manual feedback submission for agent improvement, but there's no evidence of automated AI-driven quality scoring, failure flagging, or resolution analysis performed autonomously by the platform's AI — feedback and analysis appear human-driven rather than AI-automated review. missing for 10: automated AI scoring of call quality, automatic failure/anomaly flagging, AI-generated resolution analysis without human review.

   • [claimed-docs] “Track key metrics like reach rate, call duration, and success rate.”
   • [claimed-docs] “Analyze individual calls, transcripts, and call outcome fields.”
   • [claimed-docs] “Submit feedback on calls to continuously improve your agent.”

   proof ↗⚑ flag

2. founderSee call analytics — success rates, durations, outcomes, sentiment — in dashboards without building my own

   weight 2 · round drawn
   ElevenLabs Agents~partialclaimed6/10

   Docs confirm built-in agent-analysis features—success evaluation, sentiment analysis, data extraction, and conversation search—managed via the ElevenAgents dashboard, which covers most of the story's asked-for metrics without custom-building analytics. However, there's no explicit evidence of a dashboard showing aggregated success-rate percentages or call-duration analytics/rollups across calls, only per-conversation criteria and settings. Missing for 10: dashboard screenshots/evidence of aggregate success-rate metrics, call-duration reporting/rollups, and independent corroboration that these appear in a unified analytics view.

   • [claimed-docs] “Success evaluation: Define custom criteria to assess conversation quality, goal achievement, and customer satisfaction”
   • [claimed-docs] “Data collection: Extract specific data points from conversations such as contact information, issue details, or any structured information”
   • [claimed-docs] “Sentiment analysis: Understand user sentiment across completed conversations”
   • [claimed-docs] “Searching conversations: Find messages by keyword or meaning across your conversation history.”
   • [claimed-docs] “ElevenLabs Agents are managed either through the ElevenAgents dashboard, the ElevenLabs API, the Agents CLI or the hosted MCP server.”
   • [claimed-docs] “Extract structured information from conversations such as contact details and business data.”

   proof ↗⚑ flag

   telli~partialclaimed6/10

   telli's docs describe built-in dashboards tracking reach rate, call duration, and success rate, plus per-call analysis of transcripts and outcome fields, and a live monitoring overview—covering most of the story without needing custom tooling. However, there is no explicit mention of sentiment analysis in dashboards. missing for 10: sentiment scoring/analysis in dashboards, independent/hands-on corroboration of dashboard usability.

   • [claimed-docs] “Track key metrics like reach rate, call duration, and success rate.”
   • [claimed-docs] “Analyze individual calls, transcripts, and call outcome fields.”
   • [claimed-docs] “Live Monitoring > Real-time call overview of your contacts”

   proof ↗⚑ flag

Monitoring

1. platform-engineerMonitor live calls in production and get alerts when agents misbehave or error rates spike

   weight 1 · round to telli
   ElevenLabs Agents~partialclaimed4/10

   Docs show post-call analytics (sentiment analysis, success evaluation, data extraction, conversation search) and a marketing claim to 'monitor' agents, but there is no evidence of live/real-time call monitoring dashboards, error-rate metrics, or alerting/notification mechanisms for misbehaving agents. Missing for 10: real-time monitoring dashboard, error-rate/latency metrics, alerting/notification system, on-call integration (e.g., PagerDuty/Slack alerts).

   • [claimed-docs] “Success evaluation: Define custom criteria to assess conversation quality, goal achievement, and customer satisfaction”
   • [claimed-docs] “Sentiment analysis: Understand user sentiment across completed conversations”
   • [claimed-docs] “Searching conversations: Find messages by keyword or meaning across your conversation history.”
   • [claimed-docs] “Define custom criteria to assess conversation quality, goal achievement, and customer satisfaction”
   • [claimed-docs] “Configure, deploy and monitor natural, human-sounding agents in 70+ languages with leading accuracy and ultra-low latency across voice or ch…”

   proof ↗⚑ flag

   telli~partialclaimed5/10

   telli offers a real-time Live Monitoring call overview (telli-docs-32) and webhooks that push real-time notifications on call events/status/outcomes (telli-docs-13, telli-docs-21), which a platform engineer could wire into an alerting pipeline, plus metric tracking like success/reach rate (telli-docs-7). However there is no documented built-in alerting mechanism, error-rate-spike detection, or agent-misbehavior alerting system. Missing for 10: native alert/notification thresholds, anomaly or error-rate-spike detection, and evidence of alert delivery (email/Slack/PagerDuty) tied to live monitoring.

   • [claimed-docs] “Live Monitoring > Real-time call overview of your contacts”
   • [claimed-docs] “Webhooks: Receive real-time notifications about call events, status changes, and outcomes.”
   • [claimed-docs] “Webhooks push data from telli to your systems in real time. When something happens on a call, telli sends a POST request to the endpoint you…”
   • [claimed-docs] “Track key metrics like reach rate, call duration, and success rate.”

   proof ↗⚑ flag

Testing

1. developerTest agents with simulated conversations or evals before putting them on real phone calls

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents✓fullclaimed8/10

   ElevenLabs documents an explicit Agent Testing feature that verifies conversational responses, tool usage, and full multi-turn outcomes before deployment, including converting real conversations into simulated test cases, plus success-evaluation criteria for assessing conversation quality/goal achievement — directly matching the pre-deployment simulated testing story. Missing for 10: no independent/hands-on report validating test accuracy or CI-integration details, and no explicit mention of automated eval scoring pipelines beyond docs description.

   • [claimed-docs] “Agent testing lets you verify conversational responses, tool usage, and full multi-turn outcomes before you deploy.”
   • [claimed-docs] “Transform real conversations into test cases when you find an interaction where the agent underperformed.”
   • [claimed-docs] “Agent testing lets you verify conversational responses, tool usage, and full multi-turn outcomes before you deploy”
   • [claimed-docs] “Success evaluation: Define custom criteria to assess conversation quality, goal achievement, and customer satisfaction”
   • [claimed-docs] “Define custom criteria to assess conversation quality, goal achievement, and customer satisfaction”

   proof ↗⚑ flag

   telli~partialclaimed5/10

   telli's agent builder includes a 'Test call' feature to trial a draft or saved agent version and review the recording/transcript side-by-side before going live, which covers pre-production testing, and feedback submission helps iterate on agent quality. However, there is no evidence of simulated/synthetic conversation runs, automated eval suites, or scripted test scenarios independent of an actual phone call. Missing for 10: automated evals framework, non-call simulated conversation testing, batch/regression testing tools.

   • [claimed-docs] “In the agent builder, click Test call to open the dialog. Pick the agent version (your draft with unsaved changes or any saved revision)...”
   • [claimed-docs] “Use the side-by-side view to listen to the recording while following along in the transcript.”
   • [claimed-docs] “Submit feedback on calls to continuously improve your agent.”

   proof ↗⚑ flag

Post call

1. developerExtract structured data from every call — outcomes, entities, dispositions — delivered via API or webhook after the call

   weight 2 · round drawn
   ElevenLabs Agents~partialclaimed6/10

   Docs show structured post-call outputs (data collection with contact/business data extraction, success-evaluation criteria, sentiment analysis) available via 'agent-analysis' features, and the platform is manageable via API. However, the pack never explicitly documents a webhook payload/callback delivering this structured analysis after a call, only webhook *tools* for in-call actions — missing for 10: explicit post-call webhook delivery mechanism/schema for outcomes and dispositions, and confirmation these analysis fields are retrievable via a documented API endpoint.

   • [claimed-docs] “Success evaluation: Define custom criteria to assess conversation quality, goal achievement, and customer satisfaction”
   • [claimed-docs] “Data collection: Extract specific data points from conversations such as contact information, issue details, or any structured information”
   • [claimed-docs] “Sentiment analysis: Understand user sentiment across completed conversations”
   • [claimed-docs] “Extract structured information from conversations such as contact details and business data”
   • [claimed-docs] “Extract structured information from conversations such as contact details and business data.”
   • [claimed-docs] “Tools give your assistant the ability to make external function calls to third party apps so you can get real-time information.”
   • [claimed-docs] “allow an assistant to trigger authenticated actions based on the conversation, like scheduling meetings or initiating order returns”

   proof ↗⚑ flag

   telli~partialclaimed6/10

   telli documents webhooks pushing real-time call event/status/outcome data and a REST API for programmatic access, plus conversation views showing appointment/outcome fields and call outcome analysis, supporting structured post-call data delivery. However, there's no explicit documentation of a structured schema for entities/dispositions extraction or example payloads showing the full breadth of structured fields promised. missing for 10: example webhook/API payload showing structured entities and disposition fields, documentation of a dedicated 'call outcomes' data model, independent/hands-on confirmation of data completeness.

   • [claimed-docs] “Webhooks: Receive real-time notifications about call events, status changes, and outcomes.”
   • [claimed-docs] “Webhooks push data from telli to your systems in real time. When something happens on a call, telli sends a POST request to the endpoint you…”
   • [claimed-docs] “Analyze individual calls, transcripts, and call outcome fields.”
   • [claimed-docs] “Conversations now show appointments saved during a call, including the time, status, hosts, and provider link.”
   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”

   proof ↗⚑ flag

Tools

1. ai-native userMy voice agent can plug in MCP servers as tool sources so one integration grants it whole toolsets mid-call

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents✓fullclaimed8/10

   Docs explicitly describe connecting conversational agents to external MCP servers as a tool source, enabling access to data/processing capabilities via that server mid-call, directly matching the story. Missing for 10: independent hands-on confirmation of mid-call multi-tool retrieval from a connected MCP server (only vendor docs, no third-party validation) and detail on how many tools/toolsets a single MCP connection exposes.

   • [claimed-docs] “ElevenLabs allows you to connect your conversational agents to external MCP servers. This enables your agents to: Access and process informa…”
   • [claimed-docs] “ElevenLabs allows you to connect your conversational agents to external MCP servers.”
   • [claimed-docs] “Access and process information from various data sources via the MCP server”

   proof ↗⚑ flag

   telli—none0/10

   telli documents custom tools connecting to external APIs (telli-docs-20) and even an MCP server (telli-docs-22, telli-probe-3), but that MCP server lets external AI tools like Claude/ChatGPT talk to telli's Charlie assistant — it is telli acting as an MCP server, not the voice agent consuming external MCP servers as a tool source mid-call. There is no evidence the voice agent itself can plug in MCP servers to gain toolsets during a call.

   • [claimed-docs] “The telli MCP server lets AI tools like Claude, ChatGPT, and Codex talk to Charlie, telli's AI assistant, over the Model Context Protocol.”
   • [probe] “official MCP server documented at https://docs.telli.com/integrations/mcp”
   • [claimed-docs] “Custom tools allow your AI agents to access external information by connecting to your APIs.”

   proof ↗⚑ flag

2. developerMy agent can call external APIs and custom functions mid-conversation and speak the result without awkward dead air

   weight 3 · round to ElevenLabs Agents
   ElevenLabs Agents✓fullclaimed7/10

   Docs clearly describe multiple tool-calling mechanisms — webhook tools for external API calls, client-side tools, sandboxed custom JS, and MCP server integration — explicitly for making external function calls mid-conversation to fetch real-time info and trigger authenticated actions. Conversation-flow settings (turn-taking, interruption handling, ultra-low latency) address smooth conversational pacing, though not explicitly framed as avoiding dead air during tool execution. Missing for 10: explicit documentation of filler/hold-speech behavior while awaiting API results, and independent/hands-on verification that tool calls don't introduce audible pauses.

   • [claimed-docs] “Enable agents to call clients & APIs to perform actions”
   • [claimed-docs] “Tools executed directly on the client-side application (e.g., web browser, mobile app).”
   • [claimed-docs] “Tools give your assistant the ability to make external function calls to third party apps so you can get real-time information.”
   • [claimed-docs] “Custom JavaScript executed in a sandboxed environment on ElevenLabs' infrastructure.”
   • [claimed-docs] “ElevenLabs allows you to connect your conversational agents to external MCP servers. This enables your agents to: Access and process informa…”
   • [claimed-docs] “Tools allow ElevenLabs agents to perform actions beyond generating text responses.”
   • [claimed-docs] “allow an assistant to trigger authenticated actions based on the conversation, like scheduling meetings or initiating order returns”
   • [claimed-docs] “Conversation flow settings determine how your assistant handles periods of user silence, interruptions during speech, and turn-taking behavi…”
   • [claimed-docs] “Configure, deploy and monitor natural, human-sounding agents in 70+ languages with leading accuracy and ultra-low latency across voice or ch…”

   proof ↗⚑ flag

   telli~partialclaimed6/10

   Docs confirm custom tools let agents call external APIs mid-call (telli-docs-20) and built-in tool calls like web_search operate during live calls (telli-docs-30), plus transfer tools show mid-call action execution (telli-docs-31). However, there is no documentation addressing latency masking or filler-speech to avoid 'dead air' while awaiting API responses. missing for 10: explicit evidence of latency-hiding/filler speech during tool calls, independent hands-on confirmation of smooth voice continuity.

   • [claimed-docs] “Custom tools allow your AI agents to access external information by connecting to your APIs.”
   • [claimed-docs] “For a Duo agent, open Tools > System and enable web_search to let the agent search the web for current public information during calls.”
   • [claimed-docs] “Transfer tools | Move the call to another agent or number.”

   proof ↗⚑ flag

Recording

1. platform-engineerRetrieve full call recordings and transcripts programmatically for every call

   weight 2 · round drawn
   ElevenLabs Agents~partialclaimed5/10

   Docs confirm that conversation transcripts and audio recordings are stored with configurable retention, and that conversations can be searched, analyzed, and have structured data extracted (docs-26/52, docs-21/23/56), implying underlying storage of call recordings/transcripts. However, there is no explicit documentation of a specific API endpoint or method for programmatically retrieving full call recordings and transcripts on a per-call basis. Missing for 10: an explicit 'get conversation' or 'get recording/transcript' API reference, example request/response showing programmatic export of audio + transcript per call.

   • [claimed-docs] “Retention settings allow you to configure how long your conversational agent stores conversation transcripts and audio recordings.”
   • [claimed-docs] “Retention settings allow you to configure how long your conversational agent stores conversation transcripts and audio recordings”
   • [claimed-docs] “Data collection: Extract specific data points from conversations such as contact information, issue details, or any structured information”
   • [claimed-docs] “Searching conversations: Find messages by keyword or meaning across your conversation history.”
   • [claimed-docs] “Extract structured information from conversations such as contact details and business data.”

   proof ↗⚑ flag

   telli~partialprobed5/10

   Docs confirm transcripts and recordings exist and can be reviewed in-app (side-by-side view, consent-based recording) and telli exposes a general REST API plus webhooks for call events, but no endpoint is documented that explicitly returns full call recordings or transcripts programmatically for every call. missing for 10: a documented GET/recording or GET/transcript API endpoint, confirmation of bulk/enumerable retrieval, and independent verification that recordings are accessible via the API rather than only in the UI.

   • [claimed-docs] “Analyze individual calls, transcripts, and call outcome fields.”
   • [claimed-docs] “Use the side-by-side view to listen to the recording while following along in the transcript.”
   • [claimed-docs] “In telli, you can easily make audio recording conditional on the caller's consent — so a call is only recorded once they agree.”
   • [claimed-docs] “API Endpoints: Use telli's REST API to programmatically manage contacts, schedule calls, and integrate with your existing systems.”
   • [claimed-docs] “Webhooks: Receive real-time notifications about call events, status changes, and outcomes.”
   • [claimed-docs] “Webhooks push data from telli to your systems in real time. When something happens on a call, telli sends a POST request to the endpoint you…”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.telli.com/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

Transcription

1. developerGet accurate real-time transcription with control over the STT provider, language models, or key terms

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents~partialclaimed4/10

   Docs confirm agents let developers choose or bring custom LLMs (docs-41) and mention real-time voice interaction (docs-37), but there is no evidence of selectable STT providers, transcription accuracy tuning, or 'key terms'/vocabulary boosting controls anywhere in the pack. Missing for 10: STT provider selection, transcription-specific accuracy settings, key-term/glossary support, and any independent verification of transcription accuracy claims.

   • [claimed-docs] “Choose from supported LLMs or bring your own custom model”
   • [claimed-docs] “Configure, deploy and monitor natural, human-sounding agents in 70+ languages with leading accuracy and ultra-low latency across voice or ch…”
   • [claimed-docs] “Conversation flow settings determine how your assistant handles periods of user silence, interruptions during speech, and turn-taking behavi…”

   proof ↗⚑ flag

   telli—none0/10

   telli documents transcript viewing and side-by-side playback (telli-docs-29) but provides no evidence of developer-facing control over STT provider selection, choice of underlying language models, or custom key-term/vocabulary boosting for transcription accuracy.

   • [claimed-docs] “Use the side-by-side view to listen to the recording while following along in the transcript.”

   proof ↗⚑ flag

Voices

1. founderClone a custom brand voice and use it for my agents, with a documented consent process

   weight 2 · round to telli
   ElevenLabs Agents—none0/10

   The evidence pack describes selecting from 5k+ pre-built voices and voice customization (speed, multi-voice switching) but contains no mention of a voice-cloning feature for creating a custom brand voice, nor any documented consent process for cloning (e.g., voice verification, spoken consent statement) required by ElevenLabs' broader platform. Missing for 10: any docs on voice cloning/Instant or Professional Voice Cloning for Agents, and any consent-verification workflow.

   • [claimed-docs] “Select from 5k+ voices across 31 languages with customization options”
   • [claimed-docs] “Enable your agent to switch between different voices for multi-character conversations, storytelling, and language tutoring.”
   • [claimed-docs] “You can customize various aspects of your AI agent's voice to create a more natural and engaging conversation experience. This includes cont…”

   proof ↗⚑ flag

   telli~partialclaimed5/10

   Voice cloning is documented as a real feature (telli-docs-27) letting founders give agents a custom voice, but the pack's only consent-related documentation concerns call recording consent (telli-docs-26), not a consent process specifically for cloning someone's voice. Missing for 10: explicit documented consent/authorization workflow for the voice being cloned (e.g., proof of rights from the voice owner), and any legal/compliance guardrails for cloning third-party voices.

   • [claimed-docs] “Voice cloning lets you give your agent a custom voice (your own, a colleague's, or a professional voice actor's), so the agent sounds exactl…”
   • [claimed-docs] “In telli, you can easily make audio recording conditional on the caller's consent — so a call is only recorded once they agree.”

   proof ↗⚑ flag

2. developerChoose from a broad voice library or plug in multiple TTS providers to get the voice I want

   weight 2 · round to ElevenLabs Agents
   ElevenLabs Agents~partialclaimed5/10

   Docs confirm a broad in-house voice library (5k+ voices across 31 languages, docs-6) with customization like speed, pronunciation, and multi-voice switching (docs-17/32/48), satisfying the first half of the story. However, there is no evidence of plugging in third-party/alternative TTS providers — the docs only mention bring-your-own LLM (docs-41), not bring-your-own TTS engine. Missing for 10: any documented support for external/third-party TTS provider integration, evidence of provider-agnostic voice pipeline, independent confirmation of using non-ElevenLabs voices.

   • [claimed-docs] “Select from 5k+ voices across 31 languages with customization options”
   • [claimed-docs] “Enable your agent to switch between different voices for multi-character conversations, storytelling, and language tutoring.”
   • [claimed-docs] “You can customize various aspects of your AI agent's voice to create a more natural and engaging conversation experience. This includes cont…”
   • [claimed-docs] “Enable your agent to switch between different voices for multi-character conversations, storytelling, and language tutoring”
   • [claimed-docs] “Choose from supported LLMs or bring your own custom model”

   proof ↗⚑ flag

   telli~partialclaimed3/10

   Docs mention voice cloning to give an agent a custom voice, but there is no evidence of a curated voice library to choose from or the ability to plug in multiple external TTS providers as the story requires. missing for 10: evidence of a selectable voice library, multi-provider TTS integration, developer API/config for switching TTS engines.

   • [claimed-docs] “Voice cloning lets you give your agent a custom voice (your own, a colleague's, or a professional voice actor's), so the agent sounds exactl…”

   proof ↗⚑ flag