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EvalJudgment Labs

Judgment Labs

The continuous-improvement stack for AI agents.

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EvalObservability
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Open core
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Jun 21, 2026

An evaluation and monitoring platform for AI agents, built around the open-source judgeval framework. Judgment traces an agent's full trajectory — tool calls, memory, search queries, and long reasoning chains — then uses trajectory-level judges to surface failure modes, validate fixes before deploy, and catch behavioral regressions in production. The captured environment data and evals feed back into agent post-training (RL and SFT), not just pass/fail scoring. judgeval is Apache-2.0 and free; the hosted platform adds the dashboard, AutoRubrics, and enterprise features.

Pros & cons

  • Open-source judgeval framework (Apache-2.0)
  • Trajectory-level, not just output, evals
  • Feeds production data into RL/SFT
  • MCP integration with coding agents
  • Hosted platform pricing not public
  • Young company (founded 2026)
  • Geared to complex 'deep' agents

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