LangWatch

LangWatch: AI Agent Testing and LLM Evaluation Platform

LangWatch is an open-source platform designed for AI agent testing, LLM evaluation, and LLM observability. It helps teams simulate AI agents, track responses, and catch failures before they impact production.

Key Features:

• Agent Simulation: Test AI agents with simulated users to catch edge cases and prevent regressions.
• LLM Evaluation: Evaluate the performance of LLMs with built-in tools for data selection and testing.
• LLM Observability: Track responses and debug issues in your production AI.
• Framework Flexible: Works with any LLM app, agent framework, or model.
• OpenTelemetry Native: Integrates with all LLMs & AI agent frameworks.
• Self-Hosted: Fully open-source; run locally or self-host.

How to Use LangWatch:

1. Build: Design smarter agents with evidence, not guesswork.
2. Evaluate: Use built-in tools for data selection, evaluation, and testing.
3. Deploy: Reduce rework, manage regressions, and build trust in your AI.
4. Monitor: Track responses and catch failures before production.
5. Optimize: Collaborate with your entire team to run experiments, evaluate datasets, and manage prompts and flows.

Integrations:

LangWatch integrates with various frameworks and models, including:

• Python
• Typescript
• OpenAI agents
• LiteLLM
• DSPy
• LangChain
• Pydantic AI
• AWS BedRock
• Agno
• Crew AI

Is LangWatch Right for You?

LangWatch is suitable for AI Engineers, Data Scientists, Product Managers, and Domain Experts who want to collaborate on building better AI agents.

FAQ:

• How does LangWatch work?
• What is LLM observability?
• What are LLM evaluations?
• Is LangWatch self-hosted available?
• How does LangWatch compare to Langfuse or LangSmith?
• What models and frameworks does LangWatch support and how do I integrate?
• Can I try LangWatch for free?
• How does LangWatch handle security and compliance?
• **How can I contribute to the project?

LangWatch helps you ship agents with confidence. Get started in as little as 5 minutes.