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Braintrust vs Iris

A side-by-side comparison of Braintrust and Iris, two Eval tools, drawn from Ignaite's continuously-verified listings.

Compared from listings verified as of

Braintrust

Eval

Hosted eval + tracing platform for LLM apps.

View Braintrust

Iris

Eval

MCP-native eval and observability server for AI agents.

View Iris

At a glance

Feature comparison of Braintrust and Iris
AttributeBraintrustIris
CategoryEvalEval
PricingFREEMIUMFREEMIUM
License (differs)ProprietaryOpen core
Deployment (differs)CloudHybrid
Platforms (differs)Web, APIAPI
Model supportBYO key / modelBYO key / model
Vendor (differs)BraintrustIris

The honest brief

Braintrust

Eval-first: prompts are versioned objects and CI scorers block a merge when quality regresses.

  • Eval workflow as the primary interface
  • CI scorers block merges on regression
  • Dataset versioning + OTel tracing
  • Generous free tier
  • Closed-source SaaS
  • Self-hosting needs Enterprise contract
  • Overkill for tiny single-file eval needs

Iris

MCP-native: every output through the protocol is scored automatically with no SDK or instrumentation, rather than wiring evals into your code.

  • No SDK or instrumentation to add
  • Free self-host, free cloud tier
  • Trace logging and LLM-as-judge scoring
  • PII, injection, and cost checks
  • Newer, niche MCP-focused tool
  • Best fit for MCP-based agents
  • Smaller ecosystem than SDK evals