Startup
Judgment Labs
Find and fix what your agents get wrong
Judgment Labs makes a monitoring and improvement platform for long-horizon AI agents. It traces agent runs including subagents and tool calls, monitors custom signals with code checks or agentic judges, and surfaces recurring production failures. It also runs offline regression evals, and offers a Slack agent and an MCP server for use with coding agents. It can run in Judgment's cloud or in the customer's own AWS or GCP account.
Neighbours in the directory
San Francisco, CA · Est. 2022
The de-facto standard toolkit for building LLM applications and agents.
LangChain makes the LangChain framework and LangGraph, the low-level orchestration standard for stateful, controllable agents, plus the LangSmith platform for tracing, evaluating and monitoring them in production.
~$75M raised
San Francisco, CA · Est. 2023
Enterprise-grade evals, data and AI gateway.
Braintrust turns prompts and agent traces into testable datasets and CI, plus an inference gateway — helping teams measure whether harness changes actually improve agent quality.
Berkeley, CA · Est. 2020
Observability and evaluation for AI — makers of OSS Phoenix.
Arize traces and evaluates LLM and agent systems in production; their open-source Phoenix tracer is a common instrumentation choice for agent harnesses that need to be debuggable.
Connections
Relations from the Harness Hub knowledge graph, as charted in the State of Harness reports.
Built on · 1
- Model Context ProtocolProject
Similar entries · 1
- RaindropStartup
Sources
Verified Oct 29, 2026