Open source & open standard
AI Agent Testing
Test Your AI agents with simulated users
Skip manual testing and regression bugs. Our agent simulation framework runs realistic user scenarios against your agents to catch issues before production.
Simulate real user behavior and edge cases daily
Run version-controlled test suites like in CI/CD
Detect regressions with every prompt or workflow update
Understand why an agent failed, not just that it failed
versioned confidence
Detect model and prompt issues before agents hit production
LangWatch replaces manual testing or scattered scripts with structured, automated scenario testing to catch bugs so regressions don’t slip through.
TEsting & Annotations
Let domain experts test and annotate agent behavior on their own
Collaborate with the domain experts who knows what’s right. Let them build scenarios and annotate agent interactions without technical knowledge.
FLexible Framework
Works with any LLM app, agent framework, or model
Integrates with 10+ AI agent frameworks in Python and TypeScript
Fully open-source; run locally or self-host
Integrate your agent by implementing a simple call() method
Testing for your LLM apps
Enterprise-grade testing for production AI agents
Systematic quality assurance for teams deploying AI at scale with compliance, security, and domain expert collaboration built in.
Monitor, evaluate, and optimize your AI agents and LLM applications from a single platform.
LangWatch
Observability
Monitoring, Debugging, Annotations
LLM Evaluations
Integrate automated LLM evaluations directly into your workflow
Run both offline and online checks with LLM-as-a-Judge and code-based tests triggered on every push. Scale evaluations in production to catch regressions early and maintain performance.
Detect hallucinations and factual inaccuracies
Measure response quality with custom evaluations
Compare performance across different models / prompts
Create feedback loops with domain experts or user-feedback for continuous improvement
LLM Observability
Identify, debug, and resolve blindspots in your AI stack
With built-in native support for OpenTelemetry, you get full visibility into prompts, variables, tool calls, and agents across major AI frameworks. No setup headaches, just faster debugging and smarter insights.
• Trace every request through your entire stack
• Visualize token usage, response time, latency and costs
• Find the root cause
• Debug complex prompt engineering issues
LLM Optimization
Why write prompts yourself when AI can do it for you?
Self-hosted or Hybrid deployment
Deploy on your own infrastructure for full control over data and security, ensuring compliance with your enterprise standards. Or use the easiness of LangWatch Cloud and keep your customer data on your own premises.
Compliance
LangWatch is GDPR compliant and ISO27001 certified. For European customers, all our servers are hosted within Europe, with no 3rd party other than LLM providers, which you have full control of. For our Cloud solution we can host our solution in any region.
Role-based access controls
Assign specific roles and permissions to team members, ensuring the right access for the right people. Manage multiple projects and teams under the same organization.
Use your own models
& integrate via API
Integrate your custom models and leverage any API-accessible tools for maximum integration of the AI workflows with your enterprise sytems.