traceAI

traceAI

Open-source LLM tracing that speaks GenAI, not HTTP.

280upvotes
Launched April 1, 2026

About traceAI

traceAI is an open-source, OTel-native tracing tool designed specifically for Large Language Models (LLMs) and Generative AI applications. It seamlessly integrates with existing observability stacks like Datadog, Grafana, and Jaeger, providing detailed insights into prompts, completions, tokens, retrievals, and agent decisions. What sets traceAI apart is its adherence to GenAI semantic standards, ensuring accurate and meaningful tracing across diverse AI workflows. Compatible with multiple programming languages—including Python, TypeScript, Java, and C#—and supporting over 35 frameworks like OpenAI, LangChain, and CrewAI, it offers a quick setup with just two lines of code. As an open-source project under the MIT license, traceAI appeals to developers seeking robust AI observability without vendor lock-in or added dashboard complexity. Its focus on transparency and compatibility makes it a powerful tool for AI teams aiming to optimize performance, debug issues, and enhance model transparency.

Screenshots

traceAI screenshot 1
traceAI screenshot 2
traceAI screenshot 3

Pros

  • Open-source with full transparency and community support
  • Easy integration—just two lines of code to instrument entire applications
  • Supports a wide range of frameworks and languages for versatility
  • Compatible with any OTel backend—Datadog, Grafana, Jaeger, etc.
  • Accurate adherence to GenAI semantic conventions

Cons

  • Requires some familiarity with observability and tracing concepts
  • Limited to users who need detailed LLM and AI pipeline tracing
  • Potential setup complexity for very large or complex systems

Use Cases

1Monitoring and debugging LLM-based chatbots and virtual assistants
2Tracing token usage and performance bottlenecks in AI workflows
3Auditing and compliance for AI-generated outputs
4Improving model performance through detailed observability
5Integrating AI traceability into existing observability dashboards
6Optimizing retrieval-augmented generation (RAG) systems

Pricing

Open-source and free to use, with no licensing costs. Users can deploy and customize it at no charge, though enterprise support or hosting options may involve additional costs depending on deployment choices.

Quick Info

Upvotes280
Comments32
Launched4/1/2026

Topics

Open SourceDeveloper ToolsArtificial IntelligenceGitHub

Alternatives

OpenTelemetry (OTel) with custom instrumentation
Grafana Loki with tracing integrations
Datadog APM for AI pipeline monitoring
Jaeger or Zipkin for distributed tracing of AI applications
LangChain's built-in observability tools

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