Judgment Labs builds the infrastructure layer that makes AI agents get better over time in production. Their platform ingests everything a deployed agent does — tool calls, reasoning traces, memory reads, retries, and outcomes — and turns that raw experience into structured signals: recurring failure modes, behavioral rubrics, and auto-generated evals. Teams can then identify exactly where agents go wrong, validate fixes before deploying, and close the loop by feeding that environment data back into post-training (RL and SFT). Unlike legacy observability tools built for single-turn chatbots, Judgment evaluates entire multi-step agent trajectories, not just final outputs. The open-source framework (Judgeval, Apache-2.0) drives developer adoption; the hosted cloud platform adds AutoRubrics, dashboards, and enterprise features. Primary buyers are AI-native companies deploying agents in high-stakes workflows — finance, legal, and operations. The company was founded in 2025 by CEO Alex Shan, Chief Scientist Andrew Li, and CTO Joseph Camyre — all under 24 — with deep roots in Stanford NLP research, TogetherAI, and Datadog infrastructure.