Evaluate, observe, and actually ship agents that work
Trail traces every step your agents take and scores every run — so you can see what happened, prove it improved, and catch regressions before your users do.
Trace every run today. Add evals, experiments, and human review when you are ready.
Trusted by engineering teams running agents in production
Your agent is in production.
Nobody can prove it works.
Every team demos an agent in a week, then spends nine months afraid to touch it. Not because the model is weak — because there is no loop. The run fans out across a dozen calls and none of it is captured, so debugging starts from a screenshot and “better” means someone liked the demo.
Prompt fixes ship blind, customers find the bugs first, and every release becomes a negotiation. Teams that close the loop ship weekly.
See every step your agent takes
Trace each run from your app through every tool call and model call and back — latency, tokens, and cost in real time, down to the individual span.
Score every run, not just the demo
LLM-as-a-judge, heuristic scorers, or human review. Run evaluators on live production traces or inside a controlled experiment, and compare versions side by side.
Prove the new version is better
Define test cases, run your agent against them, and gate the release on the result. Set the passing bar once and every experiment is judged against it.
The rest of the loop
It reaches every framework
Python and TypeScript SDKs, a CLI for CI pipelines, and an MCP server for IDE agents. Auto-instrumentation over standard OpenTelemetry.
It brings humans in
Review queues for labelling runs, and golden datasets curated straight from production traces.
It keeps prompts straight
Version prompts and deploy changes without shipping code — the SDK pulls the live template at runtime.
It's yours to keep
Credentials never live in code. Encrypted, project-scoped, rotatable — and on Enterprise, inside your own boundary.
Try TrailUp and running in three steps.
Add the SDK, watch every run stream in, then score them with LLM judges or your own heuristics and gate releases on the result.
$ pip install trail# app.pyimport trailtrail.observe(app)trail.evaluate("accuracy", dataset="golden-set")# that's it — every run traced and scored# across 30+ agent libraries
Start free. Then pick your plan.
Every plan includes the full platform — observability, evaluation, and experiments. Scale up as your team and your agent traffic grow.
The free tier is live today. Starter and Growth prices shown are USD estimates — regional (SAR) pricing is confirmed when you talk to our team.
The full platform, on every tier.
Before you ask
Trail is one platform for running agents in production: it traces every step a run takes, scores runs with LLM judges or your own heuristics, compares versions in experiments, and turns real traces into regression datasets — so you don't stitch five tools together.
One SDK install and one init call. Trail auto-instruments over standard OpenTelemetry, so 30+ libraries — OpenAI, Anthropic, LangChain, LlamaIndex and more — are traced without any manual tracing code. Most teams see their first trace in about two minutes.
Generic APM sees an HTTP request; Trail sees a model call. Token counts, per-call cost, prompt versions, provider comparisons, and eval scores are first-class — not custom attributes you have to define and maintain yourself.
Only if you want the vault. Keys are encrypted, project-scoped, and never logged in traces. You can also keep keys in your own environment and use Trail purely for observability, prompts, and evals.
Traces are yours. You control retention per project, can redact fields before they leave your app, and can self-host if your policy requires it. We're SOC 2 ready and never train on customer data.
Yes — the free tier includes the full platform with a monthly trace allowance, no credit card required. Paid plans add longer retention, more seats, and higher volumes as you scale.
Bring your agents under observation.
Start with full trace visibility today, and add evaluation, experiments, and human review whenever you are ready.