langwatch vs Windmill
Side-by-side comparison of two AI agent tools
Short answer
- Pick langwatch for: the platform for LLM evaluations and AI agent testing. Pick Windmill for: open-source developer platform to power your entire infra and turn scripts into webhooks, workflows and UIs.
From GitHub data refreshed daily.
langwatchfree
The platform for LLM evaluations and AI agent testing
Windmillopen-source
Open-source developer platform to power your entire infra and turn scripts into webhooks, workflows and UIs. Fastest workflow engine (13x vs Airflow). Open-source alternative to Retool and Temporal.
Metrics
| langwatch | Windmill | |
|---|---|---|
| Stars | 4.9k | 18.1k |
| Star velocity /mo | 275.2105263157895 | 316.10526315789474 |
| Commits (90d) | 1.6k | 1.3k |
| Releases (6m) | 10 | 10 |
| Downloads (30d, npm + PyPI) | 1.9K | — |
| Overall score | 0.8083039136612088 | 0.8093821444423039 |
Pros
- +End-to-end agent simulation capabilities that test against full stack including tools, state, and user interactions with detailed failure analysis
- +Open standards approach with OpenTelemetry/OTLP support ensuring no vendor lock-in and framework-agnostic compatibility
- +Integrated workflow combining tracing, evaluation, prompt optimization, and monitoring in a single platform eliminating tool sprawl
- +Multi-language support with automatic UI generation from scripts in Python, TypeScript, Go, Bash, SQL, and more
- +High performance workflow engine claiming 13x faster execution than Airflow
- +Self-hostable open-source solution with AGPLv3 license providing full control and customization
Cons
- -As a specialized platform, may require learning curve and setup time for teams new to LLM evaluation workflows
- -Self-hosting option available but may require infrastructure management for teams preferring on-premises deployment
- -AGPLv3 license may restrict some commercial use cases and require careful compliance consideration
- -Being a comprehensive platform may introduce complexity for simple automation tasks
- -Self-hosting requires infrastructure management and maintenance overhead
Use Cases
- •Regression testing of AI agents before production deployment using realistic scenario simulations to identify breaking points
- •Production monitoring and observability of LLM-powered applications with detailed tracing and performance evaluation
- •Collaborative prompt engineering and optimization with domain expert annotations and version control integration
- •Building internal APIs and webhooks from existing scripts without additional infrastructure
- •Creating automated workflows for background jobs and data processing pipelines
- •Developing low-code internal applications with custom UIs for non-technical team members
FAQ
- Which is more popular, langwatch or Windmill?
- Windmill has more GitHub stars (18,092 vs 4,908).
- Which is more actively developed, langwatch or Windmill?
- langwatch had more commits in the last 90 days (1,587 vs 1,264).
- Should I use langwatch or Windmill?
- Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.