Ship quality AI at scale

Surface patterns in production, turn them into evals, and improve quality with every release.

Build with agents

Trusted by the best AI teams

Inspect traces in real time

AI fails differently than normal software. You need a new kind of observability to monitor and fix it.

AI drifts and regresses silently. With patterns surfaced automatically, the best teams can evaluate against expectations and iterate continuously.

AI observability and evaluation for the whole team. From engineering to product, in one platform.

Total LLM cost

Observability

See what actually happened in production. Inspect every trace and tool call, search across millions of logs, and track latency, cost, and quality in real time.

Evals

Define what good looks like before you ship. Run experiments against real datasets, compare prompts and models side-by-side, and score outputs with LLMs, code, or humans.

Automation

Turn production signals into improvements automatically. Topics surfaces patterns in real time across task, issues, and sentiment, online scoring catches regressions, and quality gates block bad releases.

Everything you need to build smarter, faster

Customer support prompt

Optimize this prompt based on human and automated scoring results.

Brainstore, the database built for AI data at scale. Designed for complex AI traces.

AI traces are large and nested. Traditional databases can't handle the complexity. Brainstore is designed specifically for AI observability so you can query millions of traces quickly.

Secure by default. Compliant from day one.

SOC 2 Type II certified. GDPR compliant. SSO, RBAC, HIPAA compliant, and hybrid deployment options out of the box.

SOC 2 Type II

Independently audited security controls verified annually.

Built for teams running AI in production. From first agent to enterprise scale.

Malte Ubl, CTO

“We didn't realize we needed deep observability until Braintrust.”

Trace everything

import { Eval } from "braintrust";
import { Factuality } from "autoevals";

Eval("Support Agent", {
  data: () => [
    { input: "Where is order #12345?", expected: "Your order is in transit via UPS" },
    { input: "Can I return an opened item?", expected: "Returns accepted within 30 days" },
  ],
  task: (input) => supportAgent(input),
  scores: [Factuality],
});

Native SDKs

SDKs for Python, TypeScript, Go, Ruby, C#, and more. Start tracing production AI with just a few lines of code.