Clear the gap to  LLM reliability

Automated benchmarks, drift detection, and real‑time alerts guide every release
Man standing on mountain looking across a gap to cliff
Man standing on top of mountain.
Cliff.
Quality Blind spots

Everyone's guessing
No one's sure

Spreadsheets stuffed with ad-hoc scores and gut-check metrics leave every result in doubt, wasting hours hunting down context across tabs.

Manual Evaluation Spreadsheet.
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Reggie
Have you tried it with claude 4? I heard it's really good so maybe...
😫 2
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Sam
No idea why it's better, it just is ...I think?
🤯 1
LLM drift

You can’t fix
what you can't see

Model quality drops quietly — your users feel it before you do. Traceloop catches the failures before they hit production.

LLM drift performance graph.
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Priya
Users are complaining it’s acting weird again
🤦 1
Slack profile picture of Alex.
Alex
Feels like it's lost some of the tone we had before.
😲 2

Take control of your LLM

Traceloop monitors what your model says, how fast it responds, and when things start to slip — so you can debug faster and deploy safely.

Trace Loop Dashboard.

Start with raw data,
end with real answers

Traceloop turns noisy LLM logs into clear insights — instantly

Start tracking in seconds

Just one line of code gets you live visibility into prompts, responses, latency, and more — no setup, no hassle.

Connect and capture a conceptual UI.

Run quality checks with zero setup

Traceloop runs trusted checks like faithfulness, relevance, and safety using built-in metrics — applied automatically to your real data. Get a baseline understanding of model quality without writing a single test.

Standard evaluators conceptual UI.

Define quality on your terms

Off-the-shelf metrics don’t always cut it. With Traceloop, you can define what quality means for your use case, annotate real examples, and train a custom evaluator that scores output the way you would.

CustomEvaluatorConceptualUI

Make quality part of the pipeline

Traceloop runs your standard and custom evaluations automatically — whether it’s on every pull request or in real time as your app runs. Catch issues early, enforce thresholds, and ship with confidence.

Automated Quality Gates Conceptual UI.

Traceloop is built for real-world teams

From startup to enterprise, cloud to air-gapped — we’ve got you covered.

Enterprise-ready by design

SOC 2 & HIPAA compliant. Deploy Traceloop in the cloud, on-prem, or air-gapped.

Enterprise ready HIPAA and SOC 2 compliance illustration.

Open standards at the core

Traceloop is built on OpenTelemetry and ships with OpenLLMetry, our open-source SDK — giving you transparency without lock-in.

Open Standards Conceptual Illustration

Works with every stack

Connect your LLMs in Python, TypeScript, Go, or Ruby using OpenLLMetry or our native OpenTelemetry-based gateway, Hub.

Works with any stack conceptual illustration.

Compatible with the tools you actually use

Traceloop supports 20+ providers (OpenAI, Anthropic, Gemini, Bedrock, Ollama), vector DBs (Pinecone, Chroma), and frameworks like LangChain, LlamaIndex, and CrewAI.

Compatible with the tools you actually use: Conceptual illustration.

Proudly open source with OpenLLMetry

Check out our GitHub repository to see contributions and perhaps make your own!