Vapi vs Bolna

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 drawn
   Vapi✓fullprobed8/10

   Vapi documents API/SDK-based assistant creation, phone number attachment, and call placement (vapi-docs-1, vapi-docs-18, vapi-docs-19), a CLI for managing assistants, phone numbers, and calls entirely from the terminal (vapi-docs-2, vapi-docs-31, vapi-probe-rt-1 confirming keyless install/version), and an official MCP server exposing these same operations to any MCP-compatible agent, verified live and auth-gated in a runtime probe (vapi-docs-33, vapi-probe-rt-2). Together these three surfaces (API, CLI, MCP) cover the full agent-provision-number-call workflow without dashboard use. missing for 10: no single end-to-end hands-on trace showing one agent chaining create→attach→call purely via CLI/MCP/API in one session, and no independent (non-vendor) confirmation of the full workflow succeeding.

   • [claimed-docs] “const assistant = await vapi.assistant”
   • [claimed-docs] “Manage assistants, phone numbers, and calls from your terminal”
   • [claimed-docs] “Create a voice assistant, connect it to a phone number, and make your first calls.”
   • [claimed-docs] “In under 5 minutes, you'll create a voice assistant and start talking to it over the phone.”
   • [claimed-docs] “Build, test, and deploy voice AI applications without leaving your development environment.”
   • [claimed-docs] “The Vapi MCP Server exposes Vapi APIs as tools via the Model Context Protocol (MCP), so you can manage assistants, phone numbers, and calls …”
   • [probe] “official MCP server documented at https://docs.vapi.ai/sdk/mcp-server”
   • [probe] “official CLI documented at https://docs.vapi.ai/cli”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vapi CLI installed via the vendor's one-liner (`curl -sSL https://vapi.ai/install.sh | bas…”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”

   proof ↗⚑ flag

   Bolna✓fullprobed8/10

   Bolna offers all three surfaces needed for agent-native provisioning: a documented API quickstart to create an agent, attach a number, and place a call (bolna-docs-14, bolna-docs-15), a native Go CLI to manage agents, calls, and phone numbers from the terminal (bolna-docs-16, bolna-probe-4), and an official MCP server to connect Claude/Cursor/Windsurf clients (bolna-docs-17, bolna-probe-3), all without requiring dashboard interaction. missing for 10: independent/hands-on confirmation that MCP or CLI can complete the full create-attach-call flow end-to-end (only vendor docs), and no OpenAPI spec was resolvable (bolna-probe-2) to verify API completeness.

   • [claimed-docs] “Make your first Voice AI call with the Bolna API — verify your key, get an agent, place a call, and fetch the transcript in about five minut…”
   • [claimed-docs] “Click the Create a new API Key button to generate your unique authentication credentials.”
   • [claimed-docs] “The Bolna CLI (bolna) is a single Go binary that lets you manage agents, calls, phone numbers, and batches directly from your terminal”
   • [claimed-docs] “Connect Claude, Cursor, Windsurf, or any MCP client to your Bolna account with the Bolna MCP server.”
   • [probe] “official MCP server documented at https://www.bolna.ai/docs/build-with-ai/mcp”
   • [probe] “official CLI documented at https://www.bolna.ai/docs/cli/introduction”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.bolna.ai/openapi.json, https://docs.bolna.ai/swagger.json, https://docs.bolna.ai/api/op…”

   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
   Vapi—none0/10

   Evidence shows Vapi provides CLI, MCP server, tool/webhook infrastructure, and testing frameworks (Evals, Voice Test Suites), plus a Customer Support template, but nothing indicates the platform itself uses AI to generate or improve prompts, conversation flows, or test cases from a natural-language description — testing tools require manually defined mock conversations/scripts rather than AI-authored ones.

   • [claimed-docs] “Voice Test Suites enable you to test your AI voice agents through simulated phone conversations.”
   • [claimed-docs] “Evals is Vapi's AI agent testing framework that enables you to systematically test assistants and squads using mock conversations with autom…”
   • [claimed-docs] “Our AI tester calls your voice agent and follows a script that simulates real customer behavior.”
   • [claimed-docs] “you'll create mock conversations, define expected behaviors, and validate your agents work correctly before production”
   • [claimed-docs] “Select the down arrow next to Create Assistant, then choose Customer Support.”

   proof ↗⚑ flag

   Bolna—none0/10

   No evidence shows Bolna's own platform AI generating or improving prompts, flows, or test cases from a description; the closest feature (build-with-ai/mcp) is an MCP server that lets external AI clients like Claude or Cursor manage the account via API, not the platform itself authoring agents. Templates can be cloned, but that's static copying, not AI-generated authoring.

   • [claimed-docs] “Connect Claude, Cursor, Windsurf, or any MCP client to your Bolna account with the Bolna MCP server.”
   • [claimed-docs] “Clone any template and customize it for your business.”

   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 Vapi
   Vapi✓fullcommunity9/10

   Docs explicitly walk through creating a voice assistant, connecting a phone number, and making a first call in under 5 minutes (vapi-docs-18, vapi-docs-19), with voice selection via the Voice Library (vapi-docs-8, vapi-docs-24) and dashboard-driven assistant creation with templates (vapi-docs-16); community evidence corroborates a working live-call demo (vapi-comm-1). Missing for 10: independent third-party benchmarking of the full 'within an hour' timing claim beyond vendor docs and a single anecdotal community comment.

   • [claimed-docs] “Create a voice assistant, connect it to a phone number, and make your first calls.”
   • [claimed-docs] “In under 5 minutes, you'll create a voice assistant and start talking to it over the phone.”
   • [claimed-docs] “Select the down arrow next to Create Assistant, then choose Customer Support.”
   • [claimed-docs] “The Voice Library in the Vapi Dashboard lists every voice available to your organization. Browse and preview voices there”
   • [claimed-docs] “Browse and preview voices there, then copy a voice's ID to use on an assistant.”
   • [community] “Called the demo number, sounds smooth! Good luck.”

   proof ↗⚑ flag

   Bolna✓fullclaimed8/10

   Docs directly support the story: templates can be cloned and customized, build/deploy claimed under 5 minutes, voice/accent selection, phone number and telephony setup (BYOT/SIP), and a quickstart walking through key verification, agent creation, placing a call, and fetching a transcript in ~5 minutes. This covers prompt (agent config/templates), voice (voice/provider selection), and phone number (telephony/SIP) end-to-end for a first live call within an hour. Missing for 10: independent/hands-on confirmation of the 'under 5 minutes' or 'first call in an hour' claims beyond vendor docs, and no third-party success report.

   • [claimed-docs] “Build and deploy in under 5 minutes”
   • [claimed-docs] “Clone any template and customize it for your business.”
   • [claimed-docs] “You can choose different voices, accents, and speaking styles to match your brand.”
   • [claimed-docs] “Bring Your Own Telephony (BYOT) lets you connect any standards-compliant SIP trunk to the Bolna platform.”
   • [claimed-docs] “Make your first Voice AI call with the Bolna API — verify your key, get an agent, place a call, and fetch the transcript in about five minut…”
   • [claimed-docs] “Bolna supports Deepgram, Azure, ElevenLabs, and more.”

   proof ↗⚑ flag

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

   weight 2 · round to Bolna
   Vapi—none0/10

   The evidence pack covers CLI, MCP server, tools, voices, compliance, and testing, but contains no mention of multi-language support, language detection, or mid-call language switching capabilities. Absence of evidence for this applicable axis (multilingual voice agents are a fair capability to expect from a voice AI platform) means it must be judged 'none'. missing for 10: any mention of multi-language conversation support, language auto-detection, or mid-call language switching features.

   ⚑ flag

   Bolna~partialclaimed6/10

   Docs claim the agent "detects and switches mid-call on its own" and marketing mentions "multilingual intelligence" for thousands of calls, directly supporting the story, but there's no detail on supported languages, configuration options, or independent/hands-on verification of mid-call switching reliability. Missing for 10: language list/configuration docs, hands-on or third-party confirmation of switching accuracy, and edge-case handling details.

   • [claimed-docs] “the agent detects and switches mid-call on its own”
   • [claimed-docs] “Power thousands of inbound and outbound calls every minute with human-like, multilingual intelligence”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   Vapi—none0/10

   Evidence covers Vapi's assistant configuration, tools, CLI, MCP server, voices, and testing, but there is no mention of a visual flow builder with branching, states, or handoffs — Vapi appears configuration/code-driven (assistant config, function tools, webhooks) rather than a no-code visual conversation designer.

   ⚑ flag

   Bolna—none0/10

   Evidence shows Bolna is built around APIs, CLI, and MCP server for defining agents and multi-step outreach sequences (bolna-docs-12, bolna-docs-16, bolna-docs-17), but there is no mention of a visual/no-code builder with branching, states, or handoffs; workflows are described as 'driven entirely through the Bolna API.' Missing for 10: any visual flow-builder UI, drag-and-drop branching/state design, no-code handoff configuration.

   • [claimed-docs] “Build multi-step outreach sequences that combine voice agent calls, WhatsApp messages, API calls, waits and retries, driven entirely through…”
   • [claimed-docs] “The Bolna CLI (bolna) is a single Go binary that lets you manage agents, calls, phone numbers, and batches directly from your terminal”
   • [claimed-docs] “Connect Claude, Cursor, Windsurf, or any MCP client to your Bolna account with the Bolna MCP server.”
   • [github] “Bolna is the end-to-end open source production ready framework for quickly building LLM based voice driven conversational applications.”

   proof ↗⚑ flag

Personalization

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

   weight 2 · round drawn
   Vapi—none0/10

   The evidence pack covers assistant creation, tools/webhooks, CLI, MCP server, voices, and testing, but contains no documentation of variable injection, assistantOverrides, or per-caller context personalization at call time. Missing for 10: docs on dynamic variable substitution (e.g., {{variableName}} templating), call-time overrides/metadata injection, and any example showing per-caller personalization.

   ⚑ flag

   Bolna—none0/10

   The evidence pack covers agent creation, extraction categories, call summaries, workflows, and providers, but nothing documents passing per-caller dynamic variables or context payloads at call time to personalize a conversation.

   ⚑ 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 drawn
   Vapi—none0/10

   Vapi is a voice-agent platform focused on assistants, phone numbers, custom webhook tools, and telephony/testing; the evidence pack shows no built-in knowledge base or RAG feature for grounding assistants on uploaded documents. Custom tools/webhooks could be used to build a workaround, but no document ingestion or retrieval capability is documented.

   • [claimed-docs] “Create your own webhook-based tools to extend assistant capabilities”
   • [claimed-docs] “This guide shows you how to create custom tools, including Function Tools, for your Vapi assistants.”
   • [claimed-docs] “Custom tools that you create... interact with your systems via webhooks”

   proof ↗⚑ flag

   Bolna—none0/10

   Bolna is a voice AI agent platform (telephony, TTS/STT, LLM providers, workflows) but the evidence pack contains no mention of a knowledge base, document ingestion, or RAG capability for grounding agent responses in custom content. This axis clearly applies to conversational agent-building platforms, so absence of evidence yields 'none'.

   ⚑ flag

Agent access

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

   weight 2 · round to Bolna
   Vapi✓fullprobed8/10

   Vapi confirms an llms.txt file exists and is served at docs.vapi.ai/llms.txt (HTTP 200), explicitly instructing agents on how to fetch clean Markdown per page, which directly satisfies the story. missing for 10: no independent/community corroboration of agents actually consuming llms.txt in practice, only first-party probe evidence.

   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.vapi.ai/llms.txt # Vapi ## Instructions for AI Agents - For clean Markdown of any page, append `.…”

   proof ↗⚑ flag

   Bolna✓fullprobed9/10

   A probe confirms llms.txt is live and returns 200 with structured agent-oriented doc links (bolna-probe-1), and Bolna also documents an official MCP server for connecting AI clients like Claude/Cursor to its docs/account (bolna-docs-17, bolna-probe-3), directly enabling agent-native consumption of its documentation. Missing for 10: no independent third-party confirmation that agents successfully use llms.txt in practice.

   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.bolna.ai/llms.txt # Bolna Docs > Quickly build and deploy conversational Voice AI agents - [Home]…”
   • [claimed-docs] “Connect Claude, Cursor, Windsurf, or any MCP client to your Bolna account with the Bolna MCP server.”
   • [probe] “official MCP server documented at https://www.bolna.ai/docs/build-with-ai/mcp”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   Vapi~partialprobed6/10

   Vapi ships an official CLI (vapi-docs-2/31/32, confirmed working keylessly in vapi-probe-rt-1) that can manage assistants, calls, and forward webhooks, which supports scripted/CI-style usage, and SDKs/REST APIs imply headless programmatic calls. However there is no explicit CI/automation documentation, no examples of running in a pipeline, and the MCP server requires bearer-key auth (vapi-probe-rt-2) which is unaddressed for CI contexts. missing for 10: explicit CI/automation examples or docs, non-interactive auth/service-account flow for CI, evidence of headless voice-testing/evals running in a pipeline.

   • [claimed-docs] “Manage assistants, phone numbers, and calls from your terminal”
   • [claimed-docs] “Build, test, and deploy voice AI applications without leaving your development environment.”
   • [claimed-docs] “The CLI auto-detects your tech stack and sets up everything you need.”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vapi CLI installed via the vendor's one-liner (`curl -sSL https://vapi.ai/install.sh | bas…”
   • [claimed-docs] “Evals is Vapi's AI agent testing framework that enables you to systematically test assistants and squads using mock conversations with autom…”
   • [claimed-docs] “you'll create mock conversations, define expected behaviors, and validate your agents work correctly before production”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”

   proof ↗⚑ flag

   Bolna~partialprobed6/10

   Bolna offers a CLI (single Go binary) for managing agents, calls, phone numbers, and batches from the terminal, plus a REST API for scripted call creation and transcript retrieval — both usable in CI/automation pipelines without a GUI. However, there's no explicit CI/pipeline example, headless-mode documentation, or exit-code/automation-specific guidance. missing for 10: explicit CI integration examples/guides, documented non-interactive/headless flags or exit codes, third-party confirmation of CI usage.

   • [claimed-docs] “The Bolna CLI (bolna) is a single Go binary that lets you manage agents, calls, phone numbers, and batches directly from your terminal”
   • [probe] “official CLI documented at https://www.bolna.ai/docs/cli/introduction”
   • [claimed-docs] “Make your first Voice AI call with the Bolna API — verify your key, get an agent, place a call, and fetch the transcript in about five minut…”
   • [claimed-docs] “Click the Create a new API Key button to generate your unique authentication credentials.”

   proof ↗⚑ flag

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

   weight 3 · round drawn
   Vapi—none0/10

   The evidence shows Vapi exposes its own APIs as an MCP server (so external MCP clients like Claude Desktop can control Vapi), but this is the opposite direction from the story — there's no evidence that Vapi assistants can consume/plug-in external MCP servers to use their tools within a conversation. Vapi's tool docs describe webhook-based custom tools and OpenAI-style function calling only, with no mention of MCP-server ingestion.

   • [claimed-docs] “so you can manage assistants, phone numbers, and calls from any MCP-compatible AI assistant (like Claude Desktop) or agent framework”
   • [claimed-docs] “The Vapi MCP Server exposes Vapi APIs as tools via the Model Context Protocol (MCP), so you can manage assistants, phone numbers, and calls …”
   • [claimed-docs] “Create your own webhook-based tools to extend assistant capabilities”
   • [claimed-docs] “Custom tools that you create... interact with your systems via webhooks”
   • [probe] “official MCP server documented at https://docs.vapi.ai/sdk/mcp-server”

   proof ↗⚑ flag

   Bolna—none0/10

   Evidence shows Bolna ships an MCP *server* so external clients like Claude, Cursor, or Windsurf can control a Bolna account (bolna-docs-17, bolna-probe-3) — this is the reverse direction from the story, which asks whether Bolna's own agents can plug in external MCP servers to gain their tools. No evidence describes Bolna voice agents consuming or calling external MCP servers.

   • [claimed-docs] “Connect Claude, Cursor, Windsurf, or any MCP client to your Bolna account with the Bolna MCP server.”
   • [probe] “official MCP server documented at https://www.bolna.ai/docs/build-with-ai/mcp”

   proof ↗⚑ flag

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

   weight 3 · round to Vapi
   Vapi✓fullprobed9/10

   Vapi ships an official hosted MCP server (mcp.vapi.ai) exposing its assistant/phone/call APIs as MCP tools for any MCP-compatible agent (Claude Desktop, agent frameworks), documented in first-party docs and confirmed live via a runtime probe (401 bearer-key gate exactly as documented). Missing for 10: independent/community hands-on testimonials specifically about using the MCP server (community evidence only covers general demo/founder trivia, not MCP usage).

   • [claimed-docs] “so you can manage assistants, phone numbers, and calls from any MCP-compatible AI assistant (like Claude Desktop) or agent framework”
   • [claimed-docs] “The Vapi MCP Server exposes Vapi APIs as tools via the Model Context Protocol (MCP), so you can manage assistants, phone numbers, and calls …”
   • [probe] “official MCP server documented at https://docs.vapi.ai/sdk/mcp-server”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”

   proof ↗⚑ flag

   Bolna✓fullprobed8/10

   Bolna documents an official MCP server that lets Claude, Cursor, Windsurf, or any MCP client connect to a Bolna account, confirmed by both docs and an independent probe hitting the live page. Missing for 10: independent hands-on validation or community confirmation of the MCP server working in practice beyond the docs/probe.

   • [claimed-docs] “Connect Claude, Cursor, Windsurf, or any MCP client to your Bolna account with the Bolna MCP server.”
   • [probe] “official MCP server documented at https://www.bolna.ai/docs/build-with-ai/mcp”

   proof ↗⚑ flag

5. ai-native userUse an official CLI

   weight 2 · round to Vapi
   Vapi✓fullprobed9/10

   Vapi ships a documented official CLI for managing assistants, phone numbers, and calls from the terminal, with webhook forwarding, org/environment switching, and tech-stack auto-detection, and this was independently verified in a runtime probe (successful install and `--version` output). missing for 10: no independent third-party review or community discussion of the CLI's day-to-day usage beyond the vendor docs and single install probe.

   • [claimed-docs] “Manage assistants, phone numbers, and calls from your terminal”
   • [claimed-docs] “vapi listen --forward-to localhost:3000/webhook”
   • [claimed-docs] “Switch between organizations and environments seamlessly”
   • [claimed-docs] “Forward webhooks to your local server for debugging”
   • [claimed-docs] “Build, test, and deploy voice AI applications without leaving your development environment.”
   • [claimed-docs] “The CLI auto-detects your tech stack and sets up everything you need.”
   • [probe] “official CLI documented at https://docs.vapi.ai/cli”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vapi CLI installed via the vendor's one-liner (`curl -sSL https://vapi.ai/install.sh | bas…”

   proof ↗⚑ flag

   Bolna✓fullprobed8/10

   Bolna documents an official CLI (single Go binary) letting users manage agents, calls, phone numbers, and batches from the terminal, corroborated by a live docs probe confirming the page exists. missing for 10: no independent/hands-on community usage reports or version/release history confirming real-world adoption beyond first-party docs.

   • [claimed-docs] “The Bolna CLI (bolna) is a single Go binary that lets you manage agents, calls, phone numbers, and batches directly from your terminal”
   • [probe] “official CLI documented at https://www.bolna.ai/docs/cli/introduction”

   proof ↗⚑ flag

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

   weight 3 · round to Vapi
   Vapi✓fullprobed9/10

   Vapi ships a documented public API/SDK (assistant management, calls, tools), a CLI for terminal-driven workflows, and a hosted MCP server exposing the API as tools, all confirmed by runtime probes (CLI installs and runs, MCP endpoint live and auth-gated as documented). This directly satisfies programmatic/AI-native control via a documented public interface. Missing for 10: no independent third-party developer report deeply exercising the API beyond docs/probes.

   • [claimed-docs] “const assistant = await vapi.assistant”
   • [claimed-docs] “Manage assistants, phone numbers, and calls from your terminal”
   • [claimed-docs] “so you can manage assistants, phone numbers, and calls from any MCP-compatible AI assistant (like Claude Desktop) or agent framework”
   • [claimed-docs] “The Vapi MCP Server exposes Vapi APIs as tools via the Model Context Protocol (MCP), so you can manage assistants, phone numbers, and calls …”
   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.vapi.ai/llms.txt # Vapi ## Instructions for AI Agents - For clean Markdown of any page, append `.…”
   • [probe] “official MCP server documented at https://docs.vapi.ai/sdk/mcp-server”
   • [probe] “official CLI documented at https://docs.vapi.ai/cli”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vapi CLI installed via the vendor's one-liner (`curl -sSL https://vapi.ai/install.sh | bas…”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”

   proof ↗⚑ flag

   Bolna✓fullprobed8/10

   Bolna provides a documented public API with quickstart, authentication, agent/call/extraction endpoints, and workflow automation entirely through the API, plus a CLI and MCP server built on top of it. Missing for 10: a discoverable OpenAPI/Swagger spec (probe found all standard OpenAPI paths 404) and independent third-party corroboration of API robustness.

   • [claimed-docs] “Make your first Voice AI call with the Bolna API — verify your key, get an agent, place a call, and fetch the transcript in about five minut…”
   • [claimed-docs] “Click the Create a new API Key button to generate your unique authentication credentials.”
   • [claimed-docs] “Build multi-step outreach sequences that combine voice agent calls, WhatsApp messages, API calls, waits and retries, driven entirely through…”
   • [claimed-docs] “The Bolna CLI (bolna) is a single Go binary that lets you manage agents, calls, phone numbers, and batches directly from your terminal”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.bolna.ai/openapi.json, https://docs.bolna.ai/swagger.json, https://docs.bolna.ai/api/op…”
   • [probe] “official CLI documented at https://www.bolna.ai/docs/cli/introduction”

   proof ↗⚑ flag

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

   weight 2 · round to Vapi
   Vapi~partialprobed3/10

   Vapi's enterprise docs mention Role Based Access Control (RBAC) and SSO, implying some access-scoping capability at the org level, and its MCP server/API require bearer API keys — but there is no documented mechanism for issuing per-agent, least-privilege scoped API keys or tokens tailored to a specific agent's permissions. missing for 10: explicit scoped API key creation/management UI or API, documentation of key-level permission granularity, and independent confirmation that RBAC restricts agent credentials rather than just human dashboard users.

   • [claimed-docs] “Single Sign On (SSO) supported for Okta, Azure AD, SAML, and OIDC * Role Based Access Control (RBAC)”
   • [claimed-docs] “Single Sign On (SSO) supported for Okta, Azure AD, SAML, and OIDC”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”

   proof ↗⚑ flag

   Bolna—none0/10

   Bolna documents API key creation but there is no evidence of scoped or least-privilege credential controls (e.g., role-based permissions, scoped tokens, restricted access levels) — only a single account-wide key generation flow is described.

   • [claimed-docs] “Click the Create a new API Key button to generate your unique authentication credentials.”

   proof ↗⚑ flag

8. ai-native userBuild against official SDKs

   weight 2 · round to Vapi
   Vapi✓fullprobed8/10

   Vapi documents an official JS/TS SDK usage pattern, official CLI (probe-confirmed installed and runnable), and official MCP server (probe-confirmed live and auth-gated), all clearly aimed at AI-native/agentic developer workflows including IDE assistant integration (Cursor/Windsurf/VSCode). missing for 10: independent third-party corroboration of SDK code quality and coverage across multiple languages beyond the docs snippets.

   • [claimed-docs] “const assistant = await vapi.assistant”
   • [claimed-docs] “Manage assistants, phone numbers, and calls from your terminal”
   • [claimed-docs] “so you can manage assistants, phone numbers, and calls from any MCP-compatible AI assistant (like Claude Desktop) or agent framework”
   • [claimed-docs] “The Vapi MCP Server exposes Vapi APIs as tools via the Model Context Protocol (MCP), so you can manage assistants, phone numbers, and calls …”
   • [claimed-docs] “Your IDE's AI assistant (Cursor, Windsurf, VSCode) gains complete, accurate knowledge of Vapi's APIs and best practices. No more hallucinate…”
   • [probe] “official MCP server documented at https://docs.vapi.ai/sdk/mcp-server”
   • [probe] “official CLI documented at https://docs.vapi.ai/cli”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vapi CLI installed via the vendor's one-liner (`curl -sSL https://vapi.ai/install.sh | bas…”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”

   proof ↗⚑ flag

   Bolna~partialprobed5/10

   Bolna documents an official Web Call SDK (bolna-docs-18) under a 'developer-resources/sdks' path, plus a CLI and MCP server, giving AI-native builders some official tooling to build against, but there is no evidence of broader language SDKs (e.g., Python, Node, Go client libraries) beyond the browser-based Web Call SDK. missing for 10: multi-language server-side SDKs, independent/hands-on verification of SDK usability, breadth beyond the single web-call SDK.

   • [claimed-docs] “The Web Call SDK connects a browser tab directly to a Bolna voice agent for a live, two-way conversation.”
   • [claimed-docs] “The Bolna CLI (bolna) is a single Go binary that lets you manage agents, calls, phone numbers, and batches directly from your terminal”
   • [probe] “official CLI documented at https://www.bolna.ai/docs/cli/introduction”
   • [claimed-docs] “Connect Claude, Cursor, Windsurf, or any MCP client to your Bolna account with the Bolna MCP server.”

   proof ↗⚑ flag

9. ai-native userSubscribe to events via webhooks

   weight 2 · round to Vapi
   Vapi✓fullclaimed7/10

   Vapi supports webhook-based events via Server URL (tool-calls messages), custom webhook tools, and CLI webhook forwarding for local debugging, giving AI-native users a documented event subscription mechanism. missing for 10: independent/hands-on confirmation of webhook delivery reliability, a full event-type catalog/schema, and signature/verification documentation.

   • [claimed-docs] “Create your own webhook-based tools to extend assistant capabilities”
   • [claimed-docs] “When tools are triggered, your Server URL receives a `tool-calls` message”
   • [claimed-docs] “Vapi supports OpenAI-style tool/function calling. Assistants can ping your server to perform actions.”
   • [claimed-docs] “Forward webhooks to your local server for debugging”
   • [claimed-docs] “Custom tools that you create... interact with your systems via webhooks”

   proof ↗⚑ flag

   Bolna—none0/10

   No evidence in the pack mentions webhooks or event subscription for Bolna; the docs cover agents, calls, CLI, MCP, SIP, pricing, and security but nothing about outbound event notifications. Missing for 10: any webhook registration/config API, event payload documentation, or third-party confirmation of webhook delivery.

   ⚑ flag

Agentic features

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

   weight 2 · round to Bolna
   Vapi—none0/10

   Evidence covers building/testing assistants (Evals, Voice Test Suites), CLI/MCP management tools, and tool-calling, but nothing describes the product itself surfacing AI-generated insights or suggestions derived from a user's own call/usage data (e.g., analytics dashboards with AI-generated recommendations).

   ⚑ flag

   Bolna~partialclaimed5/10

   Bolna offers agent-level call_summary_enabled to auto-generate AI summaries and an extraction-categories API to pull structured insights out of call data, both of which are AI-generated insights derived from user data (calls). However, there's no evidence of broader cross-call analytics, trend insights, or proactive suggestions surfaced in a dashboard beyond per-call outputs. Missing for 10: aggregated/dashboard-level insights across multiple calls, proactive recommendation surfacing, and independent confirmation of quality of generated summaries/extractions.

   • [claimed-docs] “POST /agent/{agent_id}/extraction-categories — create a category (name + model) and attach it to an agent”
   • [claimed-docs] “Call summaries are an agent-level toggle: call_summary_enabled (boolean, off by default) on the agent create and update APIs”

   proof ↗⚑ flag

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

   weight 2 · round to Bolna
   Vapi~partialclaimed4/10

   Vapi assistants operate autonomously once a call starts—handling conversation flow, invoking custom tools via webhooks, and triggering server-side automations without further human input (vapi-docs-6, vapi-docs-17, vapi-docs-23, vapi-docs-34). However, this autonomy is scoped to an active call session; there is no evidence of scheduled/cron-style background jobs or agent loops that run independently of a triggered call or user interaction. Missing for 10: evidence of scheduled/background triggers outside live calls, persistent autonomous task queues, or proactive (non-call-triggered) automation runs.

   • [claimed-docs] “Create your own webhook-based tools to extend assistant capabilities”
   • [claimed-docs] “When tools are triggered, your Server URL receives a `tool-calls` message”
   • [claimed-docs] “Vapi supports OpenAI-style tool/function calling. Assistants can ping your server to perform actions.”
   • [claimed-docs] “Custom tools that you create... interact with your systems via webhooks”
   • [claimed-docs] “This guide shows you how to create custom tools, including Function Tools, for your Vapi assistants.”

   proof ↗⚑ flag

   Bolna~partialprobed6/10

   Bolna's workflows feature lets users build multi-step outreach sequences (voice calls, WhatsApp, API calls, waits, retries) driven entirely through the API, which supports background automation, and the CLI can manage batches of calls autonomously. However there's no documented evidence of scheduling/triggers, monitoring/alerting on autonomous runs, or a dashboard for managing long-running background jobs beyond the API-driven workflow primitives. missing for 10: scheduling/trigger mechanisms, autonomous-run monitoring/alerting, independent hands-on confirmation of unattended long-running workflows.

   • [claimed-docs] “Build multi-step outreach sequences that combine voice agent calls, WhatsApp messages, API calls, waits and retries, driven entirely through…”
   • [claimed-docs] “The Bolna CLI (bolna) is a single Go binary that lets you manage agents, calls, phone numbers, and batches directly from your terminal”
   • [probe] “official CLI documented at https://www.bolna.ai/docs/cli/introduction”

   proof ↗⚑ flag

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

   weight 3 · round drawn
   Vapi—none0/10

   Vapi's docs describe building and configuring voice AI assistants for end-users (phone/web calls, tools, testing) and even an MCP server/CLI for managing those assistants, but there is no evidence of a built-in AI assistant/copilot inside the Vapi product itself that the AI-native user can delegate platform tasks to (e.g., an in-dashboard copilot that configures assistants or writes tools for you). The CLI mentions external IDE assistants (Cursor/Windsurf) gaining API knowledge, but that's a third-party tool, not a built-in in-product assistant.

   • [claimed-docs] “Your IDE's AI assistant (Cursor, Windsurf, VSCode) gains complete, accurate knowledge of Vapi's APIs and best practices. No more hallucinate…”
   • [claimed-docs] “Manage assistants, phone numbers, and calls from your terminal”
   • [claimed-docs] “so you can manage assistants, phone numbers, and calls from any MCP-compatible AI assistant (like Claude Desktop) or agent framework”

   proof ↗⚑ flag

   Bolna—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 userOperate the product with natural-language commands

   weight 2 · round drawn
   Vapi✓fullprobed7/10

   Vapi exposes an official MCP server that lets any MCP-compatible AI assistant (e.g. Claude Desktop) manage assistants, phone numbers, and calls via natural-language tool calls, and this endpoint is confirmed live and auth-gated in a runtime probe. It also ships a CLI and llms.txt docs optimized for AI agents to operate it. Missing for 10: no first-party evidence of a built-in chat/NL command console inside the Vapi product itself (beyond MCP/CLI proxies), and no independent hands-on report of an agent successfully performing multi-step tasks via MCP.

   • [claimed-docs] “so you can manage assistants, phone numbers, and calls from any MCP-compatible AI assistant (like Claude Desktop) or agent framework”
   • [claimed-docs] “The Vapi MCP Server exposes Vapi APIs as tools via the Model Context Protocol (MCP), so you can manage assistants, phone numbers, and calls …”
   • [claimed-docs] “Your IDE's AI assistant (Cursor, Windsurf, VSCode) gains complete, accurate knowledge of Vapi's APIs and best practices. No more hallucinate…”
   • [probe] “official MCP server documented at https://docs.vapi.ai/sdk/mcp-server”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vapi CLI installed via the vendor's one-liner (`curl -sSL https://vapi.ai/install.sh | bas…”
   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.vapi.ai/llms.txt # Vapi ## Instructions for AI Agents - For clean Markdown of any page, append `.…”

   proof ↗⚑ flag

   Bolna✓fullprobed7/10

   Bolna ships an official MCP server that lets AI-native tools like Claude, Cursor, or Windsurf connect to a Bolna account and operate it (manage agents, calls, etc.) via natural-language commands, confirmed both in docs and via a live probe. Missing for 10: independent/hands-on verification that the MCP integration works as described, and no additional natural-language control surfaces (e.g., chat-based dashboard) beyond MCP.

   • [claimed-docs] “Connect Claude, Cursor, Windsurf, or any MCP client to your Bolna account with the Bolna MCP server.”
   • [probe] “official MCP server documented at https://www.bolna.ai/docs/build-with-ai/mcp”

   proof ↗⚑ flag

Api quality

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

   weight 2 · round drawn
   Vapi—none0/10

   The evidence pack shows static markdown documentation, code snippets, a CLI, and an MCP server, but no interactive API reference or runnable/try-it-out examples are described anywhere in the docs pages cited.

   ⚑ flag

   Bolna—none0/10

   Bolna has an API reference doc listing basics like API key creation, but there is no evidence of an interactive reference with runnable/try-it examples, and a probe for a machine-readable OpenAPI spec (which typically powers such interactive docs) returned 404 on all checked paths.

   • [claimed-docs] “Click the Create a new API Key button to generate your unique authentication credentials.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.bolna.ai/openapi.json, https://docs.bolna.ai/swagger.json, https://docs.bolna.ai/api/op…”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   Vapi—none0/10

   The evidence pack covers Vapi's CLI, MCP server, docs, and SDKs, but no citation mentions an OpenAPI spec, API reference schema, or any machine-readable spec file available for download. This is a fair axis for an API-first product, but no supporting evidence exists in the pack.

   ⚑ flag

   Bolna—none0/10

   A direct probe for OpenAPI/Swagger spec files at all standard locations returned 404s, and no evidence pack item shows a downloadable machine-readable API spec despite having an API reference page.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.bolna.ai/openapi.json, https://docs.bolna.ai/swagger.json, https://docs.bolna.ai/api/op…”
   • [claimed-docs] “Click the Create a new API Key button to generate your unique authentication credentials.”

   proof ↗⚑ flag

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

   weight 1 · round to Vapi
   Vapi✓fullclaimed7/10

   Vapi offers dedicated Voice Test Suites (AI tester simulating conversations) and an Evals framework explicitly for creating mock conversations to 'validate your agents work correctly before production,' plus CLI webhook forwarding to localhost for local development/debugging — all separate from live production calls. Missing for 10: explicit vendor use of the term 'sandbox environment' and independent/hands-on verification that test runs are fully isolated from production data.

   • [claimed-docs] “Voice Test Suites enable you to test your AI voice agents through simulated phone conversations.”
   • [claimed-docs] “Evals is Vapi's AI agent testing framework that enables you to systematically test assistants and squads using mock conversations with autom…”
   • [claimed-docs] “Our AI tester calls your voice agent and follows a script that simulates real customer behavior.”
   • [claimed-docs] “you'll create mock conversations, define expected behaviors, and validate your agents work correctly before production”
   • [claimed-docs] “Forward webhooks to your local server for debugging”
   • [claimed-docs] “Build, test, and deploy voice AI applications without leaving your development environment.”

   proof ↗⚑ flag

   Bolna—none0/10

   No evidence pack item mentions a sandbox environment, test mode, staging account, or separation from production data for Bolna; the closest concepts (self-hosting, BYOK, data residency) are about deployment/privacy, not a distinct sandbox/test mode. missing for 10: any mention of a sandbox/test environment, test API keys, or safe testing workflow that avoids production data.

   ⚑ flag

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

   weight 2 · round drawn
   Vapi—none0/10

   No evidence pack item mentions API versioning scheme, version numbers in endpoints, or any documented deprecation/sunset policy for Vapi's APIs; the docs cover features (CLI, MCP, tools, voices) but not API lifecycle governance.

   ⚑ flag

   Bolna—none0/10

   There is a changelog page referenced and an API reference, but no evidence of API versioning scheme or a documented deprecation policy anywhere in the pack; OpenAPI spec probes even returned 404s. Missing for 10: versioned API endpoints/headers, explicit deprecation policy documentation, migration/versioning changelog entries.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.bolna.ai/openapi.json, https://docs.bolna.ai/swagger.json, https://docs.bolna.ai/api/op…”
   • [claimed-docs] “Click the Create a new API Key button to generate your unique authentication credentials.”

   proof ↗⚑ flag

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

   weight 2 · round to Bolna
   Vapi—none0/10

   The evidence pack documents CLI/SDK/MCP management of individual assistants, phone numbers, and calls, but nowhere shows bulk/batch endpoints or commands (e.g., batch-create, bulk-update, mass-delete) for operating across many items at once.

   ⚑ flag

   Bolna~partialclaimed5/10

   The CLI explicitly manages 'batches' of calls alongside agents and phone numbers (bolna-docs-16), and the platform claims to power 'thousands of inbound and outbound calls every minute' (bolna-docs-22), implying built-in bulk calling capability. However, there is no documentation of a specific bulk API endpoint, CSV/list upload, or bulk agent/category management workflow. Missing for 10: explicit bulk-operation API docs (e.g., batch call creation, bulk agent updates), a documented interface for uploading many items at once, and independent confirmation of bulk throughput.

   • [claimed-docs] “The Bolna CLI (bolna) is a single Go binary that lets you manage agents, calls, phone numbers, and batches directly from your terminal”
   • [claimed-docs] “Power thousands of inbound and outbound calls every minute with human-like, multilingual intelligence”
   • [claimed-docs] “Build multi-step outreach sequences that combine voice agent calls, WhatsApp messages, API calls, waits and retries, driven entirely through…”

   proof ↗⚑ flag

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

   weight 3 · round to Vapi
   Vapi~partialclaimed5/10

   Vapi supports event-driven server-side tools/webhooks that fire on call events (tool-calls messages, server-url events) which act as a rule-trigger mechanism, but this is scoped to voice-call events only rather than a general-purpose automation/rules engine for arbitrary triggers. missing for 10: a documented general condition/trigger-action rules engine spanning non-call events, cross-system automation, or independent hands-on evidence of complex conditional automation chains.

   • [claimed-docs] “When tools are triggered, your Server URL receives a `tool-calls` message”
   • [claimed-docs] “Vapi supports OpenAI-style tool/function calling. Assistants can ping your server to perform actions.”
   • [claimed-docs] “Custom tools that you create... interact with your systems via webhooks”
   • [claimed-docs] “Create your own webhook-based tools to extend assistant capabilities”

   proof ↗⚑ flag

   Bolna~partialclaimed4/10

   Bolna's workflow feature lets users chain voice calls, WhatsApp messages, API calls, waits and retries via the API, which is a form of automation, but the docs never describe defining conditional 'if event X happens then do Y' rules or an event/trigger system — it's presented as sequential outreach flows rather than rule-based event triggers. Missing for 10: explicit event-trigger/rule definition syntax, conditional branching logic, and any webhook-or-event-driven automation examples beyond the sequential workflow description.

   • [claimed-docs] “Build multi-step outreach sequences that combine voice agent calls, WhatsApp messages, API calls, waits and retries, driven entirely through…”

   proof ↗⚑ flag

3. ai-native userSchedule recurring jobs or workflows

   weight 2 · round drawn
   Vapi—none0/10

   No evidence in the pack shows Vapi supports scheduling recurring jobs, workflows, or automated recurring calls/tasks — the docs cover assistants, tools, CLI, MCP server, testing, and voice customization but nothing about cron-like scheduling or recurring automation triggers.

   ⚑ flag

   Bolna—none0/10

   Bolna's workflow docs describe multi-step outreach sequences with waits and retries (bolna-docs-12), but there is no evidence of a scheduler for recurring/cron-based jobs or workflows that re-trigger automatically over time. missing for 10: recurring/scheduled trigger mechanism, cron-like job definitions, evidence of periodic re-execution.

   • [claimed-docs] “Build multi-step outreach sequences that combine voice agent calls, WhatsApp messages, API calls, waits and retries, driven entirely through…”

   proof ↗⚑ flag

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

   weight 1 · round drawn
   Vapi—none0/10

   Vapi's docs cover assistant creation, tools, CLI, MCP server, and testing/evals, but there is no mention of versioning assistant configurations, review/approval workflows, or rollback to prior versions of automations. No evidence pack item addresses version history or rollback capability.

   ⚑ flag

   Bolna—none0/10

   Bolna is a voice AI agent platform (agent creation, calls, workflows, telephony) but the evidence pack shows no version control, review workflow, or rollback mechanism for automations/agents — no mention of agent versioning, change history, approval flows, or revert capability.

   ⚑ flag

Compliance

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

   weight 2 · round drawn
   Vapi—none0/10

   The evidence pack covers HIPAA toggle, SSO/RBAC, testing/evals, and CLI/MCP tooling, but contains no mention of call-recording enable/disable controls, consent disclosure features, or configurable data retention policies for call recordings — a fair and applicable axis for a voice-calling platform.

   ⚑ flag

   Bolna—none0/10

   The evidence pack shows security/data-residency features and call-summary toggles, but nothing about call-recording consent, per-call recording enable/disable controls, disclosure/announcement features, or configurable retention periods for recordings/transcripts. No mention of recording consent mechanisms or retention settings anywhere in the docs pack.

   ⚑ flag

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

   weight 2 · round to Vapi
   Vapi~partialclaimed5/10

   Vapi documents HIPAA compliance toggle in the dashboard and enterprise SSO/RBAC, indicating some regulated-workload support, but evidence lacks explicit SOC 2 certification details, BAA execution process, or data-residency region options. missing for 10: SOC 2 report/certification evidence, explicit BAA process details, data-residency/region selection options, independent audit confirmation.

   • [claimed-docs] “HIPAA compliance can be ensured by turning on HIPAA compliance in the Dashboard.”
   • [claimed-docs] “Single Sign On (SSO) supported for Okta, Azure AD, SAML, and OIDC * Role Based Access Control (RBAC)”
   • [claimed-docs] “Single Sign On (SSO) supported for Okta, Azure AD, SAML, and OIDC”

   proof ↗⚑ flag

   Bolna~partialclaimed3/10

   Bolna documents Indian data residency and self-hosting via Docker/Kubernetes for private enterprise deployments, but there is no mention of HIPAA/BAA support or SOC 2 certification anywhere in the evidence pack. missing for 10: HIPAA/BAA attestation, SOC 2 report or certification, broader multi-region data-residency options beyond India.

   • [claimed-docs] “Indian data residency is available for deployments where data must remain in India.”
   • [claimed-docs] “Learn how to self-host Bolna Voice AI on your own servers using Docker or Kubernetes for secure, private, and scalable enterprise deployment…”

   proof ↗⚑ flag

Scale

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

   weight 2 · round to Bolna
   Vapi—none0/10

   No evidence pack items document concurrency limits, per-org call caps, autoscaling behavior, or capacity-request processes; the docs cover CLI, MCP server, tools, voices, and enterprise SSO but nothing about simultaneous-call scaling limits or how to raise them.

   ⚑ flag

   Bolna~partialclaimed3/10

   Bolna's marketing page claims it can 'power thousands of inbound and outbound calls every minute' and docs mention self-hosting via Docker/Kubernetes for 'scalable enterprise deployments,' but there are no documented concurrency limits, rate-limit tables, or self-serve capacity-scaling mechanisms (e.g., no API rate-limit docs, no autoscaling guide, no numeric SLA). missing for 10: documented numeric concurrency/rate limits, self-serve scale-up process, autoscaling architecture details, independent verification of claimed call volume.

   • [claimed-docs] “Power thousands of inbound and outbound calls every minute with human-like, multilingual intelligence”
   • [claimed-docs] “Learn how to self-host Bolna Voice AI on your own servers using Docker or Kubernetes for secure, private, and scalable enterprise deployment…”

   proof ↗⚑ flag

Self host

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

   weight 3 · round to Bolna
   Vapi—none0/10

   Vapi is presented entirely as a hosted SaaS platform with a CLI, MCP server, and dashboard for managing cloud-hosted assistants; there is no evidence of open-source runtime code or any self-hosting option. One community note even references that a different product (pipecat by daily.co) is the open-source alternative, implicitly contrasting with Vapi's closed hosted model.

   • [community] “Vapi is also built on media framework by daily.co. They have an open source version of voice ai called pipecat.”
   • [claimed-docs] “Build, test, and deploy voice AI applications without leaving your development environment.”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”

   proof ↗⚑ flag

   Bolna✓fullclaimed8/10

   Bolna is explicitly an open-source framework on GitHub, and docs include dedicated enterprise instructions for self-hosting on Docker or Kubernetes for private/enterprise deployments. Missing for 10: independent hands-on reports confirming successful self-host deployment and more detail on infrastructure requirements/limitations of the self-hosted version vs SaaS.

   • [github] “Bolna is the end-to-end open source production ready framework for quickly building LLM based voice driven conversational applications.”
   • [claimed-docs] “Learn how to self-host Bolna Voice AI on your own servers using Docker or Kubernetes for secure, private, and scalable enterprise deployment…”

   proof ↗⚑ 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 Vapi
   Vapi~partialclaimed3/10

   Vapi's docs mention that 'Ultra Fast' vs 'High Intelligence' model settings trade off latency, giving conceptual tuning guidance, but there are no documented end-to-end latency numbers (e.g., ms benchmarks) or detailed tuning playbooks in the evidence pack. Missing for 10: concrete latency benchmark figures, component-level latency breakdowns (STT/LLM/TTS), and independent verification of speed claims.

   • [claimed-docs] “Ultra Fast uses speed-optimized models for lower latency. High Intelligence accepts higher latency for greater capability.”

   proof ↗⚑ flag

   Bolna—none0/10

   No evidence pack item provides documented latency numbers, benchmarks, or tuning guidance for end-to-end voice latency; only vague marketing claims like 'build in under 5 minutes' or 'power thousands of calls' appear, with no actual latency figures or turn-taking tuning documentation.

   • [claimed-docs] “Build and deploy in under 5 minutes”
   • [claimed-docs] “Power thousands of inbound and outbound calls every minute with human-like, multilingual intelligence”

   proof ↗⚑ 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 drawn
   Vapi—none0/10

   The evidence pack covers CLI, MCP server, tools, voices, compliance, and testing, but contains no documentation or evidence about interruption handling, barge-in behavior, context updates during interruptions, or turn recovery mechanics. This is a core latency/turn-taking capability for voice agents, but nothing in the pack addresses it directly.

   ⚑ flag

   Bolna—none0/10

   No evidence pack item mentions barge-in, interruption handling, speech-stop, or turn recovery mechanics; the docs cover extraction categories, summaries, providers, CLI, MCP, pricing, etc., but nothing about turn-taking or interruption behavior. missing for 10: any documentation of barge-in/interruption detection, mid-speech stop mechanics, context update on interruption, turn recovery logic.

   ⚑ flag

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

   weight 1 · round drawn
   Vapi—none0/10

   No evidence pack items mention noise suppression, background noise filtering, or audio denoising features for handling noisy real-world calls; the pack covers voices, tools, CLI, MCP, latency modes, and testing but nothing about audio filtering.

   ⚑ flag

   Bolna—none0/10

   No evidence pack item mentions noise suppression, background noise handling, or audio filtering settings for calls; the docs cover extraction categories, summaries, telephony, SDKs, and pricing but not audio quality/noise robustness features. Missing for 10: any mention of noise suppression/audio filtering configuration, VAD tuning for noisy environments, or documented handling of real-world call noise.

   ⚑ 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
   Vapi—none0/10

   The evidence pack lacks any mention of model-based end-of-turn detection, turn-taking models, or semantic VAD alternatives; only latency tuning between 'Ultra Fast' and 'High Intelligence' model modes is documented, which does not address end-of-turn detection beyond silence-based VAD. Missing for 10: any documentation of a model-based or semantic end-of-turn detector, comparison to VAD-only timeout behavior, or configuration options for turn-taking sensitivity.

   • [claimed-docs] “Ultra Fast uses speed-optimized models for lower latency. High Intelligence accepts higher latency for greater capability.”

   proof ↗⚑ flag

   Bolna—none0/10

   No evidence describes model-based end-of-turn/turn-taking detection distinct from VAD silence timeouts; evidence only covers mid-call model switching, extraction categories, and unrelated features. Missing for 10: any mention of endpointing model, semantic turn detection, or configurable end-of-turn logic beyond silence thresholds.

   ⚑ flag

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

   weight 2 · round to Vapi
   Vapi✓fullprobed8/10

   Vapi's API/SDK covers assistant, phone number, and call management, backed by a full CLI (vapi-docs-2 through 4, 27, 31-32, verified live in vapi-probe-rt-1) and an official MCP server exposing the same operations for external agents (vapi-docs-5,33, confirmed live and auth-gated in vapi-probe-rt-2). Dashboard-only conveniences like Voice Library browsing/preview remain UI-centric, though voice IDs and custom voices can be set via API (vapi-docs-9,24,26,35). Missing for 10: explicit confirmation that every dashboard-only feature (e.g., visual Voice Library browsing, HIPAA toggle) has a full API equivalent, and independent (non-vendor) verification of full UI/API parity.

   • [claimed-docs] “Manage assistants, phone numbers, and calls from your terminal”
   • [claimed-docs] “vapi listen --forward-to localhost:3000/webhook”
   • [claimed-docs] “so you can manage assistants, phone numbers, and calls from any MCP-compatible AI assistant (like Claude Desktop) or agent framework”
   • [claimed-docs] “The Vapi MCP Server exposes Vapi APIs as tools via the Model Context Protocol (MCP), so you can manage assistants, phone numbers, and calls …”
   • [claimed-docs] “Build, test, and deploy voice AI applications without leaving your development environment.”
   • [claimed-docs] “The CLI auto-detects your tech stack and sets up everything you need.”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vapi CLI installed via the vendor's one-liner (`curl -sSL https://vapi.ai/install.sh | bas…”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”
   • [claimed-docs] “You can use your own custom voice with any supported provider by setting the `voice` property in your assistant configuration”
   • [claimed-docs] “Browse and preview voices there, then copy a voice's ID to use on an assistant.”

   proof ↗⚑ flag

   Bolna~partialprobed7/10

   Docs show the platform is API-first — agent creation, extraction categories, call summaries, workflows, and telephony are all described as configurable via the API, and a CLI and MCP server both wrap that same API, implying broad parity. However, there is no explicit documentation stating full UI/API feature parity, and probes found no discoverable OpenAPI/swagger spec (404s), leaving some doubt about completeness of coverage for every UI action. Missing for 10: explicit UI-API parity statement, published OpenAPI/swagger spec, independent confirmation that all UI actions have API equivalents.

   • [claimed-docs] “POST /agent/{agent_id}/extraction-categories — create a category (name + model) and attach it to an agent”
   • [claimed-docs] “Call summaries are an agent-level toggle: call_summary_enabled (boolean, off by default) on the agent create and update APIs”
   • [claimed-docs] “Build multi-step outreach sequences that combine voice agent calls, WhatsApp messages, API calls, waits and retries, driven entirely through…”
   • [claimed-docs] “The Bolna CLI (bolna) is a single Go binary that lets you manage agents, calls, phone numbers, and batches directly from your terminal”
   • [claimed-docs] “Connect Claude, Cursor, Windsurf, or any MCP client to your Bolna account with the Bolna MCP server.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.bolna.ai/openapi.json, https://docs.bolna.ai/swagger.json, https://docs.bolna.ai/api/op…”
   • [probe] “official CLI documented at https://www.bolna.ai/docs/cli/introduction”

   proof ↗⚑ flag

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

   weight 3 · round to Bolna
   Vapi—none0/10

   No evidence of a data export feature, open-format data dumps, or account portability/deletion tooling; the docs cover CLI, MCP server, tools, and voice features but nothing about exporting assistants/call data/transcripts in open formats for user exit. Missing for 10: documented export functionality, open data formats supported, and any account/data portability guarantees.

   ⚑ flag

   Bolna~partialclaimed3/10

   Bolna's API lets you fetch call transcripts (bolna-docs-14) and the platform can be self-hosted via Docker/Kubernetes (bolna-docs-9), with an open-source core framework (bolna-gh-1), which together provide some data portability, but there is no documented bulk 'export all data' feature or guarantee of open, standard export formats covering call recordings, agent configs, analytics, etc. Missing for 10: an explicit full-data export tool/endpoint, documented open format specification for exported data, and independent confirmation that a user can fully migrate away with all their data.

   • [claimed-docs] “Make your first Voice AI call with the Bolna API — verify your key, get an agent, place a call, and fetch the transcript in about five minut…”
   • [claimed-docs] “Learn how to self-host Bolna Voice AI on your own servers using Docker or Kubernetes for secure, private, and scalable enterprise deployment…”
   • [github] “Bolna is the end-to-end open source production ready framework for quickly building LLM based voice driven conversational applications.”

   proof ↗⚑ flag

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

   weight 2 · round to Bolna
   Vapi—none0/10

   Vapi is a closed, commercial SaaS platform; nothing in the evidence indicates its core source (server, dashboard, or model runtime) is published under an open license—only SDKs/CLI tooling and docs are mentioned, and the one open-source reference (pipecat) is a third-party project, not Vapi itself.

   • [community] “Vapi is also built on media framework by daily.co. They have an open source version of voice ai called pipecat.”

   proof ↗⚑ flag

   Bolna~partialclaimed5/10

   The GitHub repo description explicitly calls Bolna 'the end-to-end open source production ready framework,' supporting that its source is publicly available under an open-license framing, but no specific license (e.g., MIT/Apache) is named or verified, and no independent corroboration exists. Missing for 10: explicit license identification (e.g., LICENSE file contents), confirmation the entire product (not just the framework) is open-sourced, and independent verification.

   • [github] “Bolna is the end-to-end open source production ready framework for quickly building LLM based voice driven conversational applications.”

   proof ↗⚑ flag

4. ai-native userSelf-host the core product

   weight 3 · round to Bolna
   Vapi—none0/10

   Vapi is presented exclusively as a hosted cloud platform (dashboard, hosted MCP server, hosted API/CLI against cloud endpoints); nothing in the evidence pack mentions a self-hostable core engine, open-source repo for the core product, or on-prem deployment option (the mentioned pipecat is a different open-source project, not Vapi itself). This is a fair axis for a voice-AI platform, but no evidence supports self-hosting.

   • [community] “Vapi is also built on media framework by daily.co. They have an open source version of voice ai called pipecat.”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”
   • [claimed-docs] “The Vapi MCP Server exposes Vapi APIs as tools via the Model Context Protocol (MCP), so you can manage assistants, phone numbers, and calls …”

   proof ↗⚑ flag

   Bolna✓fullclaimed8/10

   Bolna is explicitly open source (GitHub repo) and documentation provides dedicated on-premise instructions for self-hosting via Docker or Kubernetes for enterprise deployments, directly satisfying the self-host story. Missing for 10: independent/hands-on confirmation of a successful self-hosted deployment and more detail on feature parity between self-hosted and cloud versions.

   • [github] “Bolna is the end-to-end open source production ready framework for quickly building LLM based voice driven conversational applications.”
   • [claimed-docs] “Learn how to self-host Bolna Voice AI on your own servers using Docker or Kubernetes for secure, private, and scalable enterprise deployment…”

   proof ↗⚑ flag

Pricing

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

   weight 2 · round to Bolna
   Vapi—none0/10

   The evidence pack contains no mention of pricing pages, per-minute rates, usage-based cost breakdowns, or any pricing calculator/estimator; all evidence is about docs, CLI, MCP server, tools, and testing features. Absence of evidence for this applicable axis yields none.

   ⚑ flag

   Bolna~partialclaimed4/10

   There is a dedicated call-pricing doc page and mentions that BYOK/connected providers aren't charged (bolna-docs-19, bolna-docs-10), indicating some usage-based pricing structure exists, but no evidence pack item actually quotes a per-minute rate, tiered pricing table, or a cost calculator a founder could use to estimate cost per call. Missing for 10: explicit per-minute/usage rate figures, a pricing calculator or worked cost example, and independent confirmation that published rates are accurate.

   • [claimed-docs] “When you bring your own keys (BYOK), Bolna does not charge for those components.”
   • [claimed-docs] “We don't charge for any usage for providers that you have connected to Bolna.”

   proof ↗⚑ flag

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

   weight 2 · round to Bolna
   Vapi—none0/10

   The evidence pack contains no mention of data residency, regional storage options, or geographic data controls anywhere in Vapi's docs (only HIPAA toggle and SSO/RBAC are mentioned as compliance features). Missing for 10: any documentation of region selection, data residency guarantees, or storage location controls.

   ⚑ flag

   Bolna~partialclaimed6/10

   Docs explicitly mention Indian data residency as an available option, and self-hosting via Docker/Kubernetes lets enterprises control where data lives entirely. However, there's no broader multi-region selection (e.g., EU, US) documented beyond India, and no detail on how residency is configured or enforced. Missing for 10: documented multi-region choice beyond India, configuration/UI for selecting region, and independent confirmation of residency enforcement.

   • [claimed-docs] “Indian data residency is available for deployments where data must remain in India.”
   • [claimed-docs] “Learn how to self-host Bolna Voice AI on your own servers using Docker or Kubernetes for secure, private, and scalable enterprise deployment…”

   proof ↗⚑ flag

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

   weight 3 · round drawn
   Vapi—none0/10

   No evidence in the pack addresses data-training opt-out, model-training data policies, or privacy controls preventing AI training use; only HIPAA and SSO/RBAC enterprise features are mentioned, which are unrelated to this specific claim. missing for 10: explicit data-training opt-out policy, DPA/ToS language on training use, dashboard/API setting to exclude data from model training.

   ⚑ flag

   Bolna—none0/10

   No evidence pack item addresses a training-data opt-out or policy on AI model training use; security docs cover data residency and IP whitelisting only, not training-data usage controls. missing for 10: any explicit statement on AI training data usage/opt-out policy, data processing agreement terms, or contractual guarantee against training use.

   ⚑ flag

3. ai-native userControl data retention and deletion

   weight 2 · round drawn
   Vapi—none0/10

   The evidence pack covers HIPAA, SSO/RBAC, tooling, CLI, and MCP server features but contains no documentation about data retention policies, call/recording deletion controls, or user-initiated data export/erasure mechanisms. Missing for 10: retention period settings, deletion/erasure APIs or dashboard controls, data export tools, and any policy documentation on how long call data/transcripts are stored.

   ⚑ flag

   Bolna—none0/10

   No evidence of data retention controls, deletion APIs, or user-facing privacy/data-lifecycle settings; only tangential mentions of security (IP whitelisting, India data residency) which do not address retention/deletion. Self-hosting option exists but that's deployment control, not a retention/deletion feature.

   • [claimed-docs] “Indian data residency is available for deployments where data must remain in India.”
   • [claimed-docs] “Whitelist all three IPs on your server or firewall”
   • [claimed-docs] “Learn how to self-host Bolna Voice AI on your own servers using Docker or Kubernetes for secure, private, and scalable enterprise deployment…”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   Vapi—none0/10

   No evidence pack item addresses telemetry opt-out or usage tracking controls; Vapi's docs cover HIPAA/SSO/RBAC compliance but not a telemetry toggle.

   ⚑ flag

   Bolna—none0/10

   No evidence pack item addresses telemetry, analytics opt-out, or usage-tracking controls for the platform itself; existing security/data-residency docs don't cover this. Missing for 10: any documentation of telemetry collection or an opt-out/disable mechanism, privacy policy statement on usage tracking, self-host confirmation of no phone-home behavior.

   ⚑ flag

Call control

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

   weight 2 · round drawn
   Vapi—none0/10

   No evidence in the pack mentions call transfer, warm/blind transfer, or passing context to a human agent; the evidence covers assistants, CLI, MCP server, tools/webhooks, voices, and compliance, but nothing about live-call escalation/transfer capabilities.

   ⚑ flag

   Bolna—none0/10

   No evidence in the pack describes call transfer functionality (warm or blind) to a human agent, or context handoff during a live call; the closest items relate to model switching, summaries, and telephony/SIP trunking but not transfer escalation.

   ⚑ flag

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

   weight 1 · round drawn
   Vapi—none0/10

   The evidence pack contains no mention of DTMF keypress sending, IVR menu navigation, or voicemail detection/leaving functionality anywhere in the docs or community items — these telephony-specific capabilities are entirely unevidenced despite being a plausible axis for a voice AI telephony product.

   ⚑ flag

   Bolna—none0/10

   No evidence in the pack mentions DTMF keypress sending, IVR menu navigation, or voicemail detection/leaving; only unrelated telephony features like SIP trunking, call summaries, and workflows are documented.

   ⚑ flag

Campaigns

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

   weight 2 · round to Bolna
   Vapi—none0/10

   Evidence covers assistant creation, tools, CLI, MCP server, testing, and voice customization, but nothing addresses batch/outbound campaign management, call scheduling, or throughput/concurrency controls for bulk dialing. No mention of a campaigns API, CSV/list upload, dialer pacing, or rate-limiting controls for outbound calling at scale.

   ⚑ flag

   Bolna~partialprobed5/10

   The CLI explicitly manages 'batches' of calls alongside agents/phone numbers, and marketing copy claims support for 'thousands of inbound and outbound calls every minute,' plus a workflows API for multi-step outreach with waits/retries — together implying batch campaign and throughput capability. However, there's no explicit documentation of scheduling controls (e.g., time windows, campaign start/stop) or throughput/rate-limiting configuration for outbound campaigns specifically. Missing for 10: explicit scheduling/calendar controls for campaigns, documented throughput/rate-limit configuration knobs, and any hands-on/independent evidence of batch campaign execution.

   • [claimed-docs] “The Bolna CLI (bolna) is a single Go binary that lets you manage agents, calls, phone numbers, and batches directly from your terminal”
   • [claimed-docs] “Power thousands of inbound and outbound calls every minute with human-like, multilingual intelligence”
   • [claimed-docs] “Build multi-step outreach sequences that combine voice agent calls, WhatsApp messages, API calls, waits and retries, driven entirely through…”
   • [probe] “official CLI documented at https://www.bolna.ai/docs/cli/introduction”

   proof ↗⚑ flag

Numbers

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

   weight 3 · round to Vapi
   Vapi✓fullprobed8/10

   Docs explicitly cover creating an assistant, connecting it to a phone number, and making inbound/outbound calls via the quickstart, plus CLI/MCP support for managing phone numbers and calls, and SIP for advanced telephony integration, with runtime probes confirming the CLI and MCP endpoints work as documented. Missing for 10: independent hands-on confirmation of actual outbound call placement via raw API (only demo/inbound anecdote in community evidence) and explicit multi-number provisioning workflow details.

   • [claimed-docs] “const assistant = await vapi.assistant”
   • [claimed-docs] “Create a voice assistant, connect it to a phone number, and make your first calls.”
   • [claimed-docs] “In under 5 minutes, you'll create a voice assistant and start talking to it over the phone.”
   • [claimed-docs] “Manage assistants, phone numbers, and calls from your terminal”
   • [claimed-docs] “so you can manage assistants, phone numbers, and calls from any MCP-compatible AI assistant (like Claude Desktop) or agent framework”
   • [claimed-docs] “The Vapi MCP Server exposes Vapi APIs as tools via the Model Context Protocol (MCP), so you can manage assistants, phone numbers, and calls …”
   • [claimed-docs] “Use any SIP softphone (e.g., Zoiper, Linphone) to dial your SIP URI”
   • [claimed-docs] “This guide shows you how to set up and test SIP calls to your Vapi assistant using any SIP client or softphone.”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vapi CLI installed via the vendor's one-liner (`curl -sSL https://vapi.ai/install.sh | bas…”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”
   • [community] “Called the demo number, sounds smooth! Good luck.”

   proof ↗⚑ flag

   Bolna~partialprobed6/10

   Bolna's API/CLI clearly support placing outbound calls and receiving inbound calls (quickstart shows placing a call and fetching transcript via API, CLI manages calls and phone numbers, marketing claims thousands of inbound/outbound calls per minute), and BYOT lets you attach SIP trunks/numbers. However there's no explicit documented endpoint for provisioning/purchasing new phone numbers through the API itself — only CLI mention of managing 'phone numbers' and bringing your own trunk. Missing for 10: explicit phone-number provisioning API endpoint/documentation, independent confirmation of end-to-end inbound+outbound flow.

   • [claimed-docs] “Make your first Voice AI call with the Bolna API — verify your key, get an agent, place a call, and fetch the transcript in about five minut…”
   • [claimed-docs] “The Bolna CLI (bolna) is a single Go binary that lets you manage agents, calls, phone numbers, and batches directly from your terminal”
   • [claimed-docs] “Bring Your Own Telephony (BYOT) lets you connect any standards-compliant SIP trunk to the Bolna platform.”
   • [claimed-docs] “Power thousands of inbound and outbound calls every minute with human-like, multilingual intelligence”
   • [probe] “official CLI documented at https://www.bolna.ai/docs/cli/introduction”

   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 Bolna
   Vapi~partialclaimed5/10

   Docs confirm SIP connectivity: platform engineers can point any SIP client/softphone at a Vapi SIP URI to make/receive calls (vapi-docs-14, vapi-docs-22), which supports self-hosted/carrier SIP trunking use cases. However, the evidence never explicitly documents PBX/carrier trunk configuration options or a number-import workflow for Twilio/Telnyx accounts. missing for 10: explicit documentation of BYO-carrier/PBX trunk setup steps, and evidence of importing existing Twilio/Telnyx phone numbers into Vapi.

   • [claimed-docs] “Use any SIP softphone (e.g., Zoiper, Linphone) to dial your SIP URI”
   • [claimed-docs] “This guide shows you how to set up and test SIP calls to your Vapi assistant using any SIP client or softphone.”

   proof ↗⚑ flag

   Bolna✓fullclaimed8/10

   Bolna explicitly documents 'Bring Your Own Telephony (BYOT)' allowing any standards-compliant SIP trunk to connect to the platform, plus IP whitelisting requirements for the connection, directly addressing carrier/PBX independence from bundled telephony. missing for 10: explicit step-by-step Twilio/Telnyx number import walkthrough and independent/hands-on verification of SIP trunk setup working end-to-end.

   • [claimed-docs] “Bring Your Own Telephony (BYOT) lets you connect any standards-compliant SIP trunk to the Bolna platform.”
   • [claimed-docs] “Whitelist all three IPs on your server or firewall”

   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 Vapi
   Vapi~partialclaimed4/10

   Vapi's Evals framework provides automated validation of assistant behavior via mock conversations and its Voice Test Suites use an AI tester to simulate calls and check outcomes, which is adjacent to automated call review, but neither is documented as automatically scoring, flagging failures in, or analyzing resolution of real production calls after the fact. Missing for 10: evidence of automatic post-call quality scoring on live/production transcripts, explicit failure-flagging analytics, and resolution-outcome analysis dashboards distinct from pre-production test suites.

   • [claimed-docs] “Evals is Vapi's AI agent testing framework that enables you to systematically test assistants and squads using mock conversations with autom…”
   • [claimed-docs] “you'll create mock conversations, define expected behaviors, and validate your agents work correctly before production”
   • [claimed-docs] “Voice Test Suites enable you to test your AI voice agents through simulated phone conversations.”
   • [claimed-docs] “Our AI tester calls your voice agent and follows a script that simulates real customer behavior.”

   proof ↗⚑ flag

   Bolna~partialclaimed3/10

   Bolna offers post-call analysis primitives — configurable extraction-categories (bolna-docs-1) and toggleable call summaries (bolna-docs-2) — which could be used to build custom scoring/flagging, but there's no documented automated QA/quality-scoring, failure-flagging, or resolution-analysis feature out of the box. Missing for 10: dedicated call-scoring/QA dashboard, automatic failure detection, resolution-analysis reporting, and independent evidence these extraction fields are used for review purposes.

   • [claimed-docs] “POST /agent/{agent_id}/extraction-categories — create a category (name + model) and attach it to an agent”
   • [claimed-docs] “Call summaries are an agent-level toggle: call_summary_enabled (boolean, off by default) on the agent create and update APIs”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   Vapi—none0/10

   The evidence pack documents assistant creation, tools, testing (Evals, Voice Test Suites), CLI/MCP management, and voice library features, but contains no mention of a dashboard showing call success rates, durations, outcomes, or sentiment analytics — the core of this story.

   ⚑ flag

   Bolna—none0/10

   Evidence only shows API-level features like call summaries (call_summary_enabled) and extraction categories, but there is no mention of a dashboard UI presenting success rates, durrations, outcomes, or sentiment analytics — missing for 10: any dashboard/UI screenshot or docs describing aggregated call analytics views.

   • [claimed-docs] “POST /agent/{agent_id}/extraction-categories — create a category (name + model) and attach it to an agent”
   • [claimed-docs] “Call summaries are an agent-level toggle: call_summary_enabled (boolean, off by default) on the agent create and update APIs”

   proof ↗⚑ flag

Monitoring

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

   weight 1 · round drawn
   Vapi—none0/10

   The evidence pack covers pre-production testing (Voice Test Suites, Evals) and webhook debugging via the CLI, but contains no mention of live call monitoring dashboards, real-time alerting, or error-rate-spike detection for production traffic. This is a fair axis for a voice AI platform, but nothing in the pack demonstrates it.

   ⚑ flag

   Bolna—none0/10

   Evidence covers call summaries, extraction categories, transcripts, CLI, MCP, and SIP/telephony features, but nothing describes live-call monitoring dashboards, real-time observability, or alerting on agent misbehavior or error-rate spikes. No mention of metrics, alert thresholds, webhooks for anomaly detection, or a monitoring console for platform engineers. Missing for 10: real-time monitoring dashboard, alerting/notification system for errors or misbehavior, error-rate tracking, on-call/integration with observability tools.

   ⚑ flag

Testing

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

   weight 2 · round to Vapi
   Vapi✓fullclaimed9/10

   Vapi documents two dedicated testing features directly matching the story: Voice Test Suites for simulated phone conversations via an AI tester following scripted customer behavior, and Evals, a testing framework for mock conversations with automated validation before production. Missing for 10: independent/hands-on developer corroboration of these specific testing features beyond vendor docs.

   • [claimed-docs] “Voice Test Suites enable you to test your AI voice agents through simulated phone conversations.”
   • [claimed-docs] “Our AI tester calls your voice agent and follows a script that simulates real customer behavior.”
   • [claimed-docs] “Evals is Vapi's AI agent testing framework that enables you to systematically test assistants and squads using mock conversations with autom…”
   • [claimed-docs] “you'll create mock conversations, define expected behaviors, and validate your agents work correctly before production”

   proof ↗⚑ flag

   Bolna—none0/10

   No evidence of any simulated conversation testing, evals, or pre-production testing framework for agents; the evidence pack only covers deployment, telephony, providers, pricing, and SDKs. Missing for 10: any mention of test/eval tooling, simulated call testing, or conversation quality scoring before live calls.

   ⚑ flag

Post call

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

   weight 2 · round to Bolna
   Vapi—none0/10

   The evidence pack shows Vapi's webhook/tool-calling system for live in-call actions (tool-calls messages, custom webhook tools, function calling) but contains no mention of a post-call structured-data/analysis feature (outcomes, entities, dispositions) delivered via API or webhook after the call ends. Missing for 10: any docs on end-of-call reports, structured data extraction schemas, call analysis/summary webhooks, or an API endpoint returning call outcome/entity data.

   • [claimed-docs] “When tools are triggered, your Server URL receives a `tool-calls` message”
   • [claimed-docs] “Vapi supports OpenAI-style tool/function calling. Assistants can ping your server to perform actions.”
   • [claimed-docs] “Custom tools that you create... interact with your systems via webhooks”
   • [claimed-docs] “Create your own webhook-based tools to extend assistant capabilities”

   proof ↗⚑ flag

   Bolna~partialclaimed6/10

   Bolna provides extraction-categories API to attach custom entity/data extraction to agents and a call_summary_enabled toggle for summaries, plus transcript fetch via API — covering entities, summaries, and outcomes. However, there's no explicit documentation of a unified structured 'disposition' field, no clear webhook delivery mechanism for post-call structured payloads (only API fetch is shown), and no example of the combined extraction+summary+disposition JSON schema. missing for 10: webhook-based delivery of extraction results, documented disposition/outcome field, end-to-end example combining all three data types in one payload.

   • [claimed-docs] “POST /agent/{agent_id}/extraction-categories — create a category (name + model) and attach it to an agent”
   • [claimed-docs] “Call summaries are an agent-level toggle: call_summary_enabled (boolean, off by default) on the agent create and update APIs”
   • [claimed-docs] “Make your first Voice AI call with the Bolna API — verify your key, get an agent, place a call, and fetch the transcript in about five minut…”

   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 drawn
   Vapi—none0/10

   Evidence only shows Vapi exposing its own APIs as an MCP *server* for external AI assistants (e.g., Claude Desktop) to manage calls/assistants — the reverse direction of the story. There is no documentation or probe showing a Vapi voice assistant can itself act as an MCP *client*, plugging in external MCP servers as tool sources mid-call; tool integration is instead described only via webhook-based custom tools and OpenAI-style function calling.

   • [claimed-docs] “so you can manage assistants, phone numbers, and calls from any MCP-compatible AI assistant (like Claude Desktop) or agent framework”
   • [claimed-docs] “The Vapi MCP Server exposes Vapi APIs as tools via the Model Context Protocol (MCP), so you can manage assistants, phone numbers, and calls …”
   • [claimed-docs] “Create your own webhook-based tools to extend assistant capabilities”
   • [claimed-docs] “Vapi supports OpenAI-style tool/function calling. Assistants can ping your server to perform actions.”
   • [probe] “PROBE runtime (recorded 2026-09-05): keyless JSON-RPC initialize POST to the hosted MCP server https://mcp.vapi.ai/mcp returned HTTP 401 — t…”

   proof ↗⚑ flag

   Bolna—none0/10

   Evidence only shows Bolna exposing its OWN MCP server so external clients (Claude, Cursor, Windsurf) can manage a Bolna account (bolna-docs-17, bolna-probe-3) — the reverse direction of the story, which asks whether a Bolna voice agent can consume external MCP servers as tool sources mid-call. No documentation shows Bolna agents acting as an MCP client or importing toolsets from third-party MCP servers during a call. missing for 10: any evidence of Bolna voice agents connecting to external MCP servers as tool sources, mid-call toolset loading via MCP.

   • [claimed-docs] “Connect Claude, Cursor, Windsurf, or any MCP client to your Bolna account with the Bolna MCP server.”
   • [probe] “official MCP server documented at https://www.bolna.ai/docs/build-with-ai/mcp”

   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 Vapi
   Vapi~partialclaimed6/10

   Vapi's docs clearly show mid-call function/tool calling via webhook Server URLs and OpenAI-style tool-calls messages, letting the assistant fetch external API results and use them in conversation (vapi-docs-6, vapi-docs-7, vapi-docs-17, vapi-docs-20, vapi-docs-23, vapi-docs-34). However, the pack lacks explicit evidence about mechanisms for avoiding 'dead air' during the API call latency (e.g., async tool config, filler phrases, or interim speech) — only general latency-tuning docs for model selection are present (vapi-docs-15). Missing for 10: explicit documentation/demo of filler/interim speech or async tool handling during function execution, and independent hands-on confirmation that the conversation flow feels seamless during a live tool call.

   • [claimed-docs] “Create your own webhook-based tools to extend assistant capabilities”
   • [claimed-docs] “Server URL: The endpoint where your function is hosted”
   • [claimed-docs] “When tools are triggered, your Server URL receives a `tool-calls` message”
   • [claimed-docs] “This guide shows you how to create custom tools, including Function Tools, for your Vapi assistants.”
   • [claimed-docs] “Vapi supports OpenAI-style tool/function calling. Assistants can ping your server to perform actions.”
   • [claimed-docs] “Custom tools that you create... interact with your systems via webhooks”
   • [claimed-docs] “Ultra Fast uses speed-optimized models for lower latency. High Intelligence accepts higher latency for greater capability.”

   proof ↗⚑ flag

   Bolna—none0/10

   The evidence pack covers extraction categories, call summaries, workflows, and custom LLM providers, but nothing describes an agent invoking external APIs or custom functions mid-call and voicing the result seamlessly. Missing for 10: documentation of a function-calling/tool-use API, examples of mid-call API invocation, and any mention of latency-masking/filler techniques to avoid dead air.

   ⚑ flag

Recording

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

   weight 2 · round to Bolna
   Vapi—none0/10

   The evidence pack contains no documentation, API reference, or example demonstrating retrieval of call recordings or transcripts, despite this being a natural, expected capability for a voice AI platform; only tangential tooling (CLI, MCP server, custom tools, testing/evals) is covered.

   ⚑ flag

   Bolna~partialclaimed5/10

   Docs confirm fetching call transcripts via API (quickstart mentions 'fetch the transcript') and call summaries can be toggled, but there is no explicit documentation of a dedicated recordings-retrieval endpoint or bulk/programmatic export for all calls. missing for 10: explicit call-recording download/API endpoint, confirmation that recordings are retained and accessible for every call, and independent verification of transcript completeness/format.

   • [claimed-docs] “Make your first Voice AI call with the Bolna API — verify your key, get an agent, place a call, and fetch the transcript in about five minut…”
   • [claimed-docs] “Call summaries are an agent-level toggle: call_summary_enabled (boolean, off by default) on the agent create and update APIs”
   • [claimed-docs] “POST /agent/{agent_id}/extraction-categories — create a category (name + model) and attach it to an agent”

   proof ↗⚑ flag

Transcription

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

   weight 2 · round to Bolna
   Vapi—none0/10

   The evidence pack contains no documentation about selecting/configuring an STT provider, choosing language models for transcription, or defining custom key terms/vocabulary for real-time transcription — topics like 'transcriber', 'Deepgram', or keyword boosting are absent. While Vapi is clearly a voice AI platform where such controls are a fair axis, none of the provided docs, community items, or probes address it.

   ⚑ flag

   Bolna~partialclaimed5/10

   Docs confirm STT provider choice (Deepgram, Azure, ElevenLabs) and full LLM control including custom OpenAI-compatible endpoints, plus transcript retrieval via API, giving developers real provider/model flexibility. However there is no evidence of key-term/vocabulary boosting or accuracy tuning controls, nor any real-time transcription accuracy benchmarks. Missing for 10: key-term/keyword-boost configuration, accuracy/latency benchmarks for real-time transcription, and independent validation of transcription quality.

   • [claimed-docs] “Bolna supports Deepgram, Azure, ElevenLabs, and more.”
   • [claimed-docs] “For custom llm simply keep provider in the llm_agent key as custom and add a openai compatible base_url”
   • [claimed-docs] “Make your first Voice AI call with the Bolna API — verify your key, get an agent, place a call, and fetch the transcript in about five minut…”

   proof ↗⚑ flag

Voices

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

   weight 2 · round drawn
   Vapi—none0/10

   Vapi docs show you can plug in a 'custom voice' by setting the voice property with a provider ID (vapi-docs-9, vapi-docs-26) and browse a Voice Library (vapi-docs-8, vapi-docs-35), but nothing describes an actual voice-cloning workflow or any documented consent/verification process required before cloning a brand voice. Missing for 10: a described voice-cloning feature/flow, a documented consent or identity-verification process, and any policy language governing voice cloning.

   • [claimed-docs] “You can use your own custom voice with any supported provider by setting the `voice` property in your assistant configuration”
   • [claimed-docs] “You can use your own custom voice with any supported provider by setting the voice property in your assistant configuration”
   • [claimed-docs] “The Voice Library in the Vapi Dashboard lists every voice available to your organization. Browse and preview voices there”
   • [claimed-docs] “The **Voice Library** in the [Vapi Dashboard] lists every voice available to your organization. Browse and preview voices there, then copy a…”

   proof ↗⚑ flag

   Bolna—none0/10

   Evidence shows Bolna lets founders choose among third-party voices/accents/styles (bolna-docs-8) and integrates providers like ElevenLabs (bolna-docs-6), but there is no mention of a voice-cloning feature for a custom brand voice, nor any documented consent process for cloning. Missing for 10: voice cloning capability, consent/verification workflow documentation, any policy on brand voice usage.

   • [claimed-docs] “You can choose different voices, accents, and speaking styles to match your brand.”
   • [claimed-docs] “Bolna supports Deepgram, Azure, ElevenLabs, and more.”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   Vapi~partialclaimed6/10

   Docs confirm a Voice Library with many previewable voices and support for custom voices with any supported provider, indicating multi-provider TTS flexibility, but the evidence never names or lists specific TTS providers (e.g., ElevenLabs, PlayHT, Azure) or details plugging in third-party/custom TTS engines beyond voice ID selection. missing for 10: explicit list of supported TTS providers, documentation of custom/BYO TTS provider integration mechanics, independent hands-on confirmation of voice quality/variety.

   • [claimed-docs] “The Voice Library in the Vapi Dashboard lists every voice available to your organization. Browse and preview voices there”
   • [claimed-docs] “You can use your own custom voice with any supported provider by setting the `voice` property in your assistant configuration”
   • [claimed-docs] “Browse and preview voices there, then copy a voice's ID to use on an assistant.”
   • [claimed-docs] “You can use your own custom voice with any supported provider by setting the voice property in your assistant configuration”
   • [claimed-docs] “The **Voice Library** in the [Vapi Dashboard] lists every voice available to your organization. Browse and preview voices there, then copy a…”

   proof ↗⚑ flag

   Bolna~partialclaimed6/10

   Docs confirm multiple TTS providers (Deepgram, Azure, ElevenLabs, and more) plus voice/accent/style customization, satisfying the 'plug in providers' part of the story. However, there's no evidence of a broad pre-built voice library or catalog to browse/select from, only provider integration. Missing for 10: evidence of a large built-in voice library/catalog, provider-count breadth beyond three named examples, independent/hands-on confirmation of voice quality or selection UX.

   • [claimed-docs] “Bolna supports Deepgram, Azure, ElevenLabs, and more.”
   • [claimed-docs] “You can choose different voices, accents, and speaking styles to match your brand.”

   proof ↗⚑ flag