aicoolies logo
LangWatch logo

LangWatch

AI agent testing and LLM evaluation platform

Share
open-sourceOpen Source
Visit Website →

LangWatch is an AI agent testing, LLM evaluation, and observability platform for production AI teams. It combines traces, evaluations, scenario simulations, guardrails, prompt management, and Optimization Studio/DSPy workflows, with cloud and self-managed options for teams that need release-quality feedback loops.

We have a review for this tool

A detailed review by the aicoolies team — click to read

About LangWatch

LangWatch is currently framed as an AI agent testing, LLM evaluation, and observability platform with tracing, simulations, guardrails, prompt management, and optimization workflows. The current site and docs emphasize traces, evaluations, scenario tests, simulations, prompt management, guardrails, Optimization Studio, DSPy optimization, Developer Free, Growth, and Enterprise/Regulated plans; GitHub reports an active Apache-2.0 repository.

Best-fit usage: production AI teams want traces, evals, datasets, prompts, and guardrails to become part of release discipline. The tool page should guide readers toward that workflow while making the major limitation clear: treating a sophisticated evaluation platform as a passive dashboard without assigning ownership for instrumentation, datasets, failure review, and release gates.

Procurement note: Developer Free is a starting point, Growth includes event/seat/usage/retention dimensions, and Enterprise or Regulated plans cover custom hosting, SSO/RBAC, audit, retention, uptime, and support requirements. If this becomes part of a production workflow, compare alternatives by the exact job to be done and verify data handling, support, and exit paths.

Pricing

Developer Free for agent monitoring/evaluation/simulations; Growth includes events, seats, usage add-ons, and retention terms; Enterprise/Regulated adds custom hosting, retention, SSO/RBAC, audit, and support.

Platforms

Cloud and self-managed platform with tracing, evaluations, scenario tests, simulations, guardrails, prompt management, OpenTelemetry-oriented instrumentation, and SDK/docs support.

Categories

Tags

Use Cases

Alternatives

Related Tools

Latitude

Sentry-style observability for AI agent conversations

Latitude is an agent observability platform for teams that need to inspect LLM traces, conversations, issues, and evaluation feedback in one workflow. Its public repo and docs position it as a Sentry-style monitor for AI agents, with semantic search, issue detection, annotations, MCP-assisted fixes, and cloud or self-hosted deployment paths for production debugging.

freemiumOpen SourceTelemetry

Spotlight by Backplanes

Session reports for Claude Code and Codex runs

Spotlight by Backplanes turns completed Claude Code and Codex sessions into concise reports for engineering, security, and spend review. The CLI installs on macOS, Linux, or WSL 2, watches sessions after they finish, redacts PII and credentials locally before upload, then summarizes files touched, commands run, external domains reached, scope drift, risky actions, and next-session improvements.

freemiumTelemetry
Traceway logo

Traceway

OpenTelemetry-native observability with AI tracing, logs, traces, metrics, and session replay — self-hosted in 90 seconds.

Traceway is an open-source, OpenTelemetry-native observability platform that combines logs, traces, metrics, exceptions, session replay, and AI tracing in a single self-hosted system. MIT licensed with no open-core restrictions, it deploys in 90 seconds via Docker Compose and accepts OTLP/HTTP from any OTel SDK without a Collector or per-language vendor SDK.

open-sourceOpen Source
Judgeval logo

Judgeval

Open-source post-building layer for agents — tracing, evals, and online monitoring

Judgeval is the open-source post-building layer for AI agents from Judgment Labs, providing OpenTelemetry-based tracing, hosted and custom evaluation scorers, and online behavior monitoring for LLM-powered applications. Instrument any function with a single decorator, score live production traffic against faithfulness and instruction-adherence checks, and feed real-world failures back into reinforcement learning or supervised fine-tuning loops.

open-sourceOpen Source
TraceRoot logo

TraceRoot

Open-source observability and self-healing layer for AI agents

TraceRoot is a YC S25-backed open-source observability platform purpose-built for AI agents and LLM apps. It combines OpenTelemetry-compatible tracing with an agentic debugging runtime that reads your source code, correlates failures with recent commits, and proposes fix PRs automatically. BYOK support spans seven LLM providers; the entire stack runs self-hosted via Docker Compose, with TraceRoot Cloud available for managed deployments.

open-sourceOpen Source
OpenSRE logo

OpenSRE

Open-source toolkit for building AI SRE incident response agents

OpenSRE is Tracer Cloud’s open-source public-alpha Python toolkit for building AI SRE agents that investigate and respond to production incidents. It ships 60+ tools across observability, databases, incident management, communications, deployment and protocol integrations, plus simulation/evaluation workflows for benchmarking agent accuracy before live pager use.

open-sourceOpen Source