Tests, evaluates, and observes AI agents and LLMs for reliable AI development.
Product memo
AI developers and engineers use Langwatch to bring traditional software engineering rigor to AI agent development. It provides broad testing, real-world scenario simulations, and specific observability. The platform turns production traces into evaluations and manages prompts and models, preventing regressions and hallucinations in AI deployments.
For who
AI developers and engineers
Solves what
Testing, evaluation, and observability for AI agents and LLMs
- Agent simulations
- Prompt and model management
- LLM observability
In their own words
Simulate real-world scenario's to test agents
Turn production traces into evals, compare prompts and models, simulate end-to-end agentic systems and improve quality with every release.
Commercial cues
Model
usage based
Free tier
No
Trial
No
Pricing Strategy
- • Usage-based pricing per request scales costs with actual platform consumption.
- • Enterprise handles custom requirements.
Operator context
Founded
Jun 2025
Platform
Web app
Audience
Developers
Public footprint
+2 more footprint links
Tech stack
Builder Strategy
- Strategy Type
- Open Source Commercial
- Stage
- Vc Growth
- Effort
- Small Team
About Langwatch Expand
Langwatch provides AI developers and engineers with essential tools for testing, evaluating, and observing AI agents and large language models. The platform helps teams deploy AI reliably by simulating real-world scenarios and turning production traces into actionable evaluations.
It also includes prompt and model management features, allowing developers to compare different iterations and prevent issues like regressions and hallucinations. This approach brings a structured engineering discipline to the often unpredictable world of AI development, serving as a critical layer for maintaining quality across releases.