Evals aren’t enough. Your agents need to be simulated.
Stop scoring what already happened. Start preventing it.
Braintrust scores what your AI already did. LangWatch simulates what your agent will do, before it ever reaches a real user. That is the difference between chasing problems and preventing them.
Join thousands of AI developers shipping reliable agents with LangWatch.
How LangWatch compares to Braintrust.
Five things teams care about when picking a quality layer for agents. Each row shows what Braintrust ships today and what LangWatch gives you on day one.
Scenario-based testing with tools, persistent state, a virtual user, and a judge. Catch failures in a sandbox, not in production.
Braintrust generates eval datasets from existing traces. No pre-production simulation with state, tools, or virtual users.
Strong pre-built evaluators with bring-your-own logic. Run from code or platform UI, online or offline.
Solid evaluations, but predominantly used by developers. Teams that need to hand it to less technical people tend to come to LangWatch.
Audit every component. Self-host with Docker in minutes at zero cost. Zero vendor lock-in at any tier.
Closed codebase. You cannot inspect what processes your trace data or how it is stored.
Friendly platform UI for domain experts. Powerful APIs and SDKs for engineers. Both edit the same source of truth.
Built for engineers. Human review queues exist but non-technical stakeholders have no real seat at the quality table.
Full STT → LLM → TTS pipeline simulation with real audio in and out. Unique in the LLMOps category.
Text-only platform. Teams building voice AI products have no testing path here.
Three reasons agent teams choose LangWatch.
Thousands of realistic multi-turn conversations against your full agent stack, before a single user interaction.
Apache 2.0 codebase. Helm chart for Kubernetes. No enterprise contract required to run it on your own infrastructure.
Domain experts build scenarios in the UI. PMs review quality. Legal annotates flagged outputs. All without touching code.
“Auto-evals showed us scores. Simulations showed us where the agent would actually break. That is the gap we needed to close before launch.”
Stop scoring failures. Start preventing them.
LangWatch is free to start. Connect in minutes, any framework, any model. Agent simulation included on day one.