What is LangWatch?
LangWatch is a platform for testing and evaluating AI agents. It helps you move from hand-testing agents to continuous, simulation-based testing. The goal is to make agents reliable in production by catching issues before users do.
You start by describing the behavior you want to test in plain language, either in your editor or through the UI. LangWatch turns your requirements into test scenarios automatically. It simulates real users, both text and voice, that push your agent turn after turn. You can run these scenarios locally or in CI, and even red-team your agent for jailbreaks or unsafe tool calls.
Beyond testing, LangWatch evaluates outputs using LLM judges, custom code, or full workflows. It observes every trace, token, and cost with OpenTelemetry support. You can compare outputs side by side, evaluate images, and cluster conversations by topic. The platform works with any agent framework without requiring a rewrite.
LangWatch features
- Simulation-based testing: Simulate real users in text and voice to push your agent like production would.
- Spec-driven development: Turn plain-language requirements into automated agent tests automatically.
- Red teaming: Probe for jailbreaks, policy breaks, and unsafe tool calls before users find them.
- LLM as a judge: Score outputs with an LLM, custom code, or a full workflow over single outputs or conversations.
- OpenTelemetry native: Full GenAI spec support so traces work with any framework and OTel-compatible stack.
What you can do with LangWatch
- Test your agent's behavior with simulated users before deploying to production.
- Red-team your agent to find jailbreaks and unsafe tool calls.
- Compare two model outputs side by side to pick the better version.
- Trace every token and cost across your agent's runs for observability.
How to get started with LangWatch
- Sign up or book a demo on LangWatch's website.
- Describe the behavior you want to test in plain language or write scenarios in your editor.
- Run scenarios locally or in CI, then evaluate traces and fix issues from production.
Tips for better results with LangWatch
- Start by writing your agent's expected behavior in plain language in your editor, and let LangWatch generate the test scenarios for you automatically.
- Run your LangWatch simulations locally while building, then add the same scenarios to CI so every pull request gets tested without extra setup.
- Use LangWatch's red teaming to probe for jailbreaks and unsafe tool calls before deploying, and fix issues before real users encounter them.
- Turn a production trace into a simulation in LangWatch to replicate a reported issue, then prove your fix works before shipping it.
LangWatch pricing
LangWatch’s homepage does not list prices. Check langwatch.ai for current plans.
What to check before you rely on LangWatch
- Check whether LangWatch's pricing is listed on the website, since the pricing page does not show specific plans or costs.
- Verify if your agent framework is supported by LangWatch, as the site says it works with every framework but does not list specific integrations.
- Confirm what data and privacy protections apply to your traces and simulations, because the website does not state data handling policies.
Who LangWatch is for
LangWatch suits AI engineers, ML teams, Product managers and QA teams. If that is not you, the AI developer platforms below may fit better.
Similar tools compared with LangWatch
| Tool | What it is | Pricing |
|---|---|---|
| LangWatch | AI agent testing and evaluation platform | See website |
| SiVideoAPI | Unified API for top AI video models | Freemium |
| OpenSI | AI model comparison and pricing tool | See website |
| OpenRouter | Unified API for many AI models | Freemium |
| Ollama | Run open models locally or cloud | Freemium |
LangWatch FAQ
What does LangWatch do?
LangWatch is a platform for testing and evaluating AI agents. It uses simulations to test agents with realistic user interactions, evaluates outputs with LLM judges, and provides observability into traces, tokens, and costs.
Is LangWatch free?
The website does not state pricing details. It offers a demo and mentions self-hosting in 15 minutes, but you would need to check the pricing page or contact them for specific plan costs.
Who is LangWatch for?
LangWatch is for teams building AI agents, including developers, product managers, and QA engineers. It helps anyone who needs to test agents reliably before production and monitor them after.
What can I build or connect with LangWatch?
LangWatch works with any agent framework without requiring a rewrite. It supports tools, skills, and MCP servers, and integrates with OpenTelemetry-compatible stacks. You can test via API or hook into internals.
Does LangWatch run on my local machine or only in the cloud?
LangWatch can be self-hosted in about 15 minutes, according to the website. It also offers a cloud platform. You can run simulations locally and in CI, so you can use it on your own machine during development and in your automated pipelines.
Can LangWatch export my test results or traces to other tools?
LangWatch uses OpenTelemetry for tracing, which is a standard format that works with many observability tools. The website mentions full GenAI spec support, so traces can integrate with any OTel-compatible stack. For specific export options beyond that, check the docs or integrations page.
What does LangWatch's free plan include?
The website does not mention a free plan or its details. Pricing is listed as unknown. To find out what the free plan includes, if any, you should visit the pricing page or contact the LangWatch team directly.
