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