What is TraceRoot used for?

TraceRoot is an open-source observability layer for AI agents that turns production traces into detector findings, datasets and evaluations. It is a good fit for monitoring LLM agents in production and turning trace failures into evaluation cases.

Is TraceRoot open source?

Yes. TraceRoot is open source under a custom licence. Its source code is on GitHub at traceroot-ai/traceroot and is written mainly in TypeScript.

Yes. TraceRoot is open source, so the software itself is free to use under the terms of its own licence. A managed cloud version is also available.

Can I self-host TraceRoot?

Yes. TraceRoot can be self-hosted on your own server or infrastructure.

What is TraceRoot an alternative to?

TraceRoot is an open-source alternative to Weights & Biases, LangSmith and Arize AI. Other open-source alternatives to Weights & Biases include Laminar, Opik and Arize Phoenix.

Is TraceRoot actively maintained?

Yes. The most recent commit to TraceRoot was on 2 October 2026, and the latest release is v1.1.2, published on 29 September 2026. The project has 790 stars on GitHub.

TraceRoot: open-source alternative to Weights & Biases

About TraceRoot

TraceRoot describes itself as an open-source self-improving layer for AI agents. It captures traces from production agent systems and turns them into actionable feedback and evaluations, closing a loop with your coding agent so that problems found in production lead to improvements. The project is a Y Combinator S25 company.

Its capabilities include tracing of LLM calls, tool use and agent steps with OpenTelemetry-compatible Python and TypeScript SDKs, covering inputs, outputs, latency, tokens and cost. Detectors screen incoming traces for behaviors such as hallucinations, tool failures and logic errors, with configurable sampling and judge models. Datasets and evaluations let you version test cases, score runs and compare candidate versions, while dashboards and threshold alerts track quality, latency and cost.

A CLI exports traces and findings into your coding workflow, and an in-app AI assistant can explore traces with access to your source code and GitHub context, using a hosted model or your own key. TraceRoot offers a hosted cloud and a self-hosting guide, is written in TypeScript, and its license is listed as Other.

Key features

OpenTelemetry-compatible agent tracing
Detectors that flag failures in traces
Versioned datasets and evaluations
Dashboards and threshold alerts
CLI for exporting traces and findings
In-app AI assistant with code context

Good fit for

→Monitoring LLM agents in production
→Turning trace failures into evaluation cases

Built with: TypeScript
Tags: observability; llm-observability; ai-agents; tracing; evaluations; opentelemetry; typescript; monitoring

TraceRoot: questions and answers

What is TraceRoot used for?: TraceRoot is an open-source observability layer for AI agents that turns production traces into detector findings, datasets and evaluations. It is a good fit for monitoring LLM agents in production and turning trace failures into evaluation cases.
Is TraceRoot open source?: Yes. TraceRoot is open source under a custom licence. Its source code is on GitHub at traceroot-ai/traceroot and is written mainly in TypeScript.
Is TraceRoot free?: Yes. TraceRoot is open source, so the software itself is free to use under the terms of its own licence. A managed cloud version is also available.
Can I self-host TraceRoot?: Yes. TraceRoot can be self-hosted on your own server or infrastructure.
What is TraceRoot an alternative to?: TraceRoot is an open-source alternative to Weights & Biases, LangSmith and Arize AI. Other open-source alternatives to Weights & Biases include Laminar, Opik and Arize Phoenix.
Is TraceRoot actively maintained?: Yes. The most recent commit to TraceRoot was on 2 October 2026, and the latest release is v1.1.2, published on 29 September 2026. The project has 790 stars on GitHub.