Book a LangWatch demo | Talk to the team
Talk to the team.
See how testing AI agents takes your product further, faster, safer, and smarter. Bring your use case and grab a time that works.
What we will cover
Evaluation-driven development
Agent simulations test your AI 8x faster, turning improvement cycles from guesswork into measurable iteration.
Collaborate on agent quality
Loop in your PMs and QA on agent quality, not just engineers.
Pricing that fits, fast
Enterprise volume pricing and the plan that matches your usage.
Compliance & security
ISO 27001, GDPR, SSO, RBAC, residency, self-hosting, and the security review.
We are looking forward to talk to you,
Manouk Draisma
Founder, CEO @ LangWatch
Rogerio Chaves
Founder, CTO @ LangWatch
The ROI
Validate a release in hours, not weeks.
Manual testing does not scale past your first agent. The user-simulator runs your real conversations in CI, so every prompt, tool, and model change is verified before it ships.
| Manual testing | With LangWatch | |
|---|---|---|
| Time to validate a release | 1 to 2 weeks | Under an hour |
| Engineers per test cycle | 6 of 7 | Runs in CI |
| Coverage per change | Manual spot-checks | Every turn, multi-turn |
| How it runs | Re-running prompts by hand | User-simulator + judge agent |
| Reproducible | No, nothing logged | Versioned and traced |
“Previously 6 of 7 engineers spent time testing our agents manually; with LangWatch that's reduced to less than an hour.”
LH
Lior Heber
AI Architect, Skai
Ready when you are.
Grab a time that works, or jump straight into the product on the free plan.
Platform
- Agentic AI TestingRun realistic user scenarios against your agent to catch issues before production
- LLM EvaluationMeasure response quality and accuracy so you ship agents that hold up in production
- LLM ObservabilityTrace every agent step and monitor cost and latency with full production visibility
- AI GovernanceNewGovern every model, key, and tool. Virtual keys with budgets, routing policies, and a full audit trail
- Prompt ManagementVersion, deploy, and A/B test prompts as code, with full history and GitHub sync
- Voice AITest and simulate your voice AI agents at scale, before they talk to customers
- LLM Red-teamingSimulated attacks that uncover safety and security gaps in AI agents