Sagify describes its project as a way to work with large language models and machine learning more easily.
traceAI
traceAI provides open source tracing for AI applications and frameworks using OpenTelemetry.

About traceAI
traceAI is an open source tracing framework for AI applications. It records the steps of an AI workflow, including LLM calls, prompts, token counts, retrieval steps, tool calls, and agent decisions, as structured OpenTelemetry traces. This makes it possible to see where an incorrect answer originated, such as a retrieval step that missed or a tool that returned stale data.
The traces are sent to any OpenTelemetry-compatible backend. The homepage names Datadog, Grafana, Jaeger, and Future AGI as examples. Instrumentation is available for more than 50 AI frameworks in Python, TypeScript, Java, and C#. The quickstart examples use the Future AGI setup, which requires Future AGI API and secret keys. Pricing is not stated in the source.
Key features
- Maps AI workflows to consistent OpenTelemetry spans and attributes
- Drop-in instrumentation for more than 50 AI frameworks
- Semantic conventions for LLM calls, agents, tools, retrieval, and vector databases
- Captures prompts, completions, token counts, model parameters, and tool calls
- Sends traces to any OpenTelemetry-compatible backend
- Async support, streaming, and error handling
- Open source, with the code available in a public GitHub repository
- Built on OpenTelemetry, so traces can go to existing observability backends
- Setup is described as adding about 3 lines to existing code
- The quickstart examples require Future AGI API and secret keys
- Supported languages are Python, TypeScript, Java, and C#
traceAI at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
traceAI alternatives
Tools and sites you could use instead, ranked by how closely they match.
DeepLake provides multimodal data infrastructure for AI agents, including retrieval and training.
OptiMate is a collection of libraries for optimizing AI model performance; the repository is marked as a legacy project.
FastChat offers an open platform for training, serving, and evaluating large language models, and hosts release repositories for Vicuna and Chatbot Arena.
Helicone provides open-source observability for LLM applications, with tools to monitor, evaluate, and experiment.
Kitaru provides agent traces that teams can run and inspect during application workflows.
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