LangWatch

Free Tier, PaidAI Orchestration and MLOps

AI Agent Testing and LLM Evaluation Platform

Founded by:

You can use LangWatch to test AI agents with synthetic conversations, evaluate LLM responses with custom scoring, and monitor production AI systems. It provides agent simulations, batch testing, prompt management, and real-time observability. The platform helps you detect issues before deployment, track model performance, and debug failures across different environments.

Use Cases

Test customer service chatbots before deploying to production

Evaluate RAG system accuracy across different document types

Monitor voice agent performance in multi-turn conversations

Debug AI agent failures using detailed trace analysis

Create regression tests from real user interactions

Simulate edge cases and multilingual scenarios

Track model performance changes after prompt updates

Collaborate between engineers and domain experts on AI quality

Prevent hallucinations through continuous evaluation

Optimize AI agent responses using structured experimentation

Integrations

Python

DSPy

OpenTelemetry, TypeScript

Standout Features

Run thousands of synthetic conversations to test agents

Create custom evaluations for specific product requirements

Monitor all LLM interactions across development and production

Version control prompts and models with audit trails

Automatically execute test suites for pre-release and production

Convert production traces into reusable test datasets

Collaborate on data review and labeling workflows

Integrate with any LLM framework using OpenTelemetry

Who is it for?

AI Engineer, Machine Learning Engineer, Software Engineer, Data Scientist, Product Manager, CTO, Quality Assurance (QA) Engineer, DevOps Engineer, AI Research Scientist, Full-Stack Developer