Surface patterns in production, turn them into scenarios, and improve quality with every release. For teams that can't afford to get it wrong.
Two problems every team hits as their agents grow. And how we solve them.
Every team starts with evals. But when an agent uses five tools across a ten-turn conversation, one score on the final answer doesn’t tell you much. You need to see whether the right tool fired, and where the conversation broke.
LangWatch is the only platform that runs simulations and evals side by side.
Engineers build the stack, the pipelines, the first eval set. From there, the best evals come from whoever knows the user best. That’s often a PM or domain expert, not the engineer.
Write scenarios with product. Hand the eval suite over sooner.
Agent testing, evals, traces and governance. Open by default, OpenTelemetry-native, runs against any model.
Test agents end-to-end with multi-turn simulations. A user simulator drives real conversations, a judge scores every turn, and you catch the failures single-shot evals miss.
Hello, and thank you for joining the interview. I am an AI assistant conducting this interview — the conversation may be recorded and assessed, and you can request a human at any time. Let's start: could you tell me about a recent project where you led the development of an LLM evaluation tool?
Langy turns a PM's goal into a full Scenario test plan — then turns the failures into pull requests.
PMs own the spec. Devs stay in flow. Nothing slips through.
LangWatch's open-source agent testing framework. Drop in to any agent in Python, TypeScript, or Go. Drive multi-turn flows yourself, or let UserSimulatorAgent play the user. JudgeAgent scores every turn. RedTeamAgent finds the edges.
from openai import OpenAI client = OpenAI( base_url="https://gateway.langwatch.ai/v1", default_headers={"x-cost-center": "payments-eu"}, )
Five ways to deploy — same product surface, same SDKs, same governance.
Managed multi-tenant SaaS — app.langwatch.ai, EU / US / UK / APAC regions.
docker compose up — full stack on a single machine for evaluation.
charts/langwatch + charts/gateway — production HA topology.
Marketplace templates for your VPC, customer-managed keys.
Data plane on your infra. Control plane on ours. Strict residency.
(Names changed to protect the no-longer-innocent.)
"LangWatch became our single source of truth for agent quality. Regressions get caught in evals before they ever reach a quarterly earnings call."
"We went from "we hope it works" to a deploy gate backed by 800 evaluators. Product and engineering finally agree on what good means."
"Scenario alone paid for the year. We replayed every release against a synthetic user set and caught a tool-routing bug 48 hours before rollout."
Thirty minutes with a LangWatch solutions engineer, your stack, live, end to end.
No credit card · Cloud · VPC · Self-hosted · Local
