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LLM Evals & Observability Arena

LLM Evals & Observability arenaBuyer checklist

Every requirement we judge llm evals & observability products against, as a ready-to-send RFP checklist — with each item's priority, why it matters, and how the top-ranked products score on it today.

52 requirements · 10 themes · verdicts for 8 products · updated 2026-09-14 · priorities mirror the story weights our scoring uses (methodology)

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# LLM Evals & Observability — buyer checklist (RFP)

Derived from ProductArena's evidence-graded user-story taxonomy for LLM Evals & Observability: 52 judged requirements. Priorities mirror story weights (3 = must-have, 2 = should-have, 1 = nice-to-have).

## Agenticness

- [ ] **[must-have]** Plug MCP servers into this product so it can use their tools
- [ ] **[must-have]** Connect an agent via an official MCP server
- [ ] **[must-have]** Drive the product through a documented public API
- [ ] **[must-have]** Delegate tasks to a built-in AI assistant inside the product
- [ ] **[should-have]** Point an agent at llms.txt or agent-oriented docs
- [ ] **[should-have]** Run the product headlessly / in CI for automation
- [ ] **[should-have]** Use an official CLI
- [ ] **[should-have]** Issue scoped/least-privilege API credentials for an agent
- [ ] **[should-have]** Build against official SDKs
- [ ] **[should-have]** Subscribe to events via webhooks
- [ ] **[should-have]** Get AI-generated insights and suggestions from my data inside the product
- [ ] **[should-have]** Set up automations that run autonomously in the background
- [ ] **[should-have]** Operate the product with natural-language commands
- [ ] **[should-have]** Explore an interactive API reference with runnable examples
- [ ] **[should-have]** Download a machine-readable API spec (OpenAPI or equivalent)
- [ ] **[should-have]** Rely on versioned APIs with a documented deprecation policy
- [ ] **[nice-to-have]** Test against a sandbox environment without touching production data

## Alerting dashboards

- [ ] **[should-have]** Build custom dashboards over latency, error, cost, and eval-score metrics
- [ ] **[should-have]** Set alerts on error rates, cost spikes, or eval-score drops and get notified in Slack, PagerDuty, or email

## Automation depth

- [ ] **[must-have]** Define rules that trigger actions automatically on events
- [ ] **[should-have]** Perform bulk operations across many items at once
- [ ] **[should-have]** Schedule recurring jobs or workflows
- [ ] **[nice-to-have]** Version, review, and roll back my automations

## Cost monitoring

- [ ] **[must-have]** See cost and token usage per request, model, and time period in dashboards
- [ ] **[should-have]** Attribute cost and usage to users, sessions, and features via custom metadata

## Data access export

- [ ] **[should-have]** Bulk-export traces and datasets to blob storage or my data warehouse

## Evals datasets

- [ ] **[must-have]** Compare eval runs side by side to catch regressions between prompt or model versions
- [ ] **[must-have]** Score outputs with configurable LLM-as-a-judge evaluators
- [ ] **[must-have]** Curate datasets from production traces and run offline evaluations against them
- [ ] **[should-have]** Have an agent create a dataset, trigger an eval run programmatically, and read back the results
- [ ] **[should-have]** Route outputs to human annotation queues for review and labeling
- [ ] **[should-have]** Run evals in CI and gate deployments on their results
- [ ] **[should-have]** Write custom code-based scorers and metrics for my evaluations
- [ ] **[should-have]** Run evaluators continuously on live production traffic, not just offline datasets

## Openness

- [ ] **[must-have]** Export all of my data in open formats and leave
- [ ] **[must-have]** Self-host the core product
- [ ] **[should-have]** Do everything through the API that I can do in the UI
- [ ] **[should-have]** Read the product's source under an open license

## Privacy posture

- [ ] **[must-have]** Prevent my data from being used to train AI models
- [ ] **[should-have]** Choose where my data is stored (region/residency)
- [ ] **[should-have]** Control data retention and deletion
- [ ] **[should-have]** Opt out of telemetry and usage tracking

## Prompt management

- [ ] **[must-have]** Version prompts and deploy changes to production without shipping code
- [ ] **[should-have]** Iterate on prompts in a playground against real models and variables

## Tracing instrumentation

- [ ] **[must-have]** Have an agent query my traces, metrics, and eval results through an API or MCP server to debug my app
- [ ] **[must-have]** Send and receive traces over OpenTelemetry (OTLP) instead of a proprietary format
- [ ] **[must-have]** Capture traces of my LLM calls with inputs, outputs, latency, and token usage
- [ ] **[should-have]** Mask or redact sensitive data before it is stored in traces
- [ ] **[should-have]** Instrument apps in both Python and JS/TS with officially supported SDKs
- [ ] **[should-have]** Trace multi-step agent runs as nested spans grouped into sessions or threads
- [ ] **[should-have]** Instrument my app through existing integrations for frameworks like LangChain, the OpenAI SDK, or the Vercel AI SDK
- [ ] **[nice-to-have]** Capture multimodal payloads (images, audio, files) inside my traces

---

Source: https://ultrametric.ai/productarena/arena/llm-evals-observability (evidence-graded verdicts for 8 products) · methodology: https://ultrametric.ai/productarena/methodology

Chips show the top 5 ranked products' current verdict on each requirement — ✓ full · ~ partial · ! disputed · — none · n/a not applicable.

Agenticness — how well agents can access and operate the productAgenticness· 17 items

How well agents can access and operate the product

Alerting dashboards — stories about alerting dashboards in this arenaAlerting dashboards· 2 items

Stories about alerting dashboards in this arena

  • ml engineerBuild custom dashboards over latency, error, cost, and eval-score metrics

    Important, not disqualifying — weighs 2× in arena scoring · 2 of 8 products fully deliver this today

    Braintrust logoBraintrustCekura logoCekuraW&B Weave logoW&B WeaveHelicone logoHeliconeLangfuse logoLangfuse
    should-have

  • developerSet alerts on error rates, cost spikes, or eval-score drops and get notified in Slack, PagerDuty, or email

    Important, not disqualifying — weighs 2× in arena scoring · 1 of 8 products fully deliver this today

    Braintrust logoBraintrustCekura logoCekuraW&B Weave logoW&B WeaveHelicone logoHeliconeLangfuse logoLangfuse
    should-have

Automation depth — how much of the product can run unattendedAutomation depth· 4 items

How much of the product can run unattended

Cost monitoring — stories about cost monitoring in this arenaCost monitoring· 2 items

Stories about cost monitoring in this arena

Data access export — stories about data access export in this arenaData access export· 1 item

Stories about data access export in this arena

Evals datasets — measuring quality — datasets, eval runs, regression trackingEvals datasets· 8 items

Measuring quality — datasets, eval runs, regression tracking

Openness — open source, data portability, and self-hosting storiesOpenness· 4 items

Open source, data portability, and self-hosting stories

Privacy posture — data-handling and privacy storiesPrivacy posture· 4 items

Data-handling and privacy stories

Prompt management — stories about prompt management in this arenaPrompt management· 2 items

Stories about prompt management in this arena

Tracing instrumentation — instrumenting code and tracing requests end to endTracing instrumentation· 8 items

Instrumenting code and tracing requests end to end

Full evidence behind every verdict lives on the arena page and each product page — chips above deep-link straight to the judged story.