Traceloop
OpenTelemetry-native tracing for LLM applications
Traceloop is profiled here as a Prompt Management tool for engineering teams. Read about features, pricing, and how it compares to related options in the tools directory.
Description
Traceloop is an LLM observability company founded by Nir Gazit and Gal Kleinman, best known for OpenLLMetry, its open-source instrumentation built on OpenTelemetry. A few lines of setup emit traces for every prompt, completion, token count, and tool call, and because the data follows the OpenTelemetry standard it lands in whatever backend a team already runs. The hosted platform adds quality monitoring on top of the same traces. Instrumentation covers OpenAI, Anthropic, Bedrock, LangChain, LlamaIndex, and a long list of other providers and frameworks.
Key Capabilities:
OpenLLMetry auto-instrumentation for major LLM providers and frameworks
Standards-based traces exportable to Datadog, Grafana, Honeycomb, and others
Prompt, completion, token, and cost tracking per request
Workflow and agent tracing across multi-step chains
Quality monitors for hallucination and output drift on the hosted platform
Apache 2.0 SDKs for Python and TypeScript
Alternative tools
- W&B Weave
Trace, evaluate, and monitor LLM applications systematically
- LangChain
The standard open-source framework for LLM applications
- Portkey
AI gateway with routing, guardrails, and prompt management
- Freeplay
Prompt management, evals, and observability for product teams
- DSPy
Declarative framework for programming and optimizing LLM pipelines
- MLflow
Track experiments, manage models, and evaluate LLM applications across the full ML lifecycle