future-agi/traceai

traceAI is an open-source tool that helps teams see exactly what happens inside their AI applications. When an AI agent gives a wrong or unexpected answer, this project lets you trace back through every step the agent took, every prompt sent, every document retrieved, every tool called, every token used, so you can pinpoint where things went wrong instead of guessing. At a high level, it works by adding a small piece of code to your existing application that silently watches what your AI tools do. You keep using your normal libraries (OpenAI, LangChain, Anthropic, Pinecone, and many others) exactly as before, and it automatically captures the details of each operation in the background. Those captured details are sent as structured "traces" to whatever monitoring dashboard your team already uses, Datadog, Grafana, Jaeger, or others, so you don't need to adopt a new vendor or learn a new interface. The people who would use this are teams building AI-powered features or products who need to debug and monitor them in production. For example, if you have a customer support bot that sometimes gives incorrect answers, this lets you see whether the problem was the retrieved context being stale, the LLM misinterpreting the prompt, or a tool returning bad data. It is aimed at developers working in Python, TypeScript, Java, or C# who want visibility without reworking their codebase. What stands out is how broad the integration list is, over 50 supported frameworks and providers across four languages, combined with the fact that it is built on OpenTelemetry, an industry-standard way of tracking what happens inside software systems. That means it is vendor-neutral: you are not locked into a specific monitoring platform, and the traces follow a consistent format regardless of which AI provider or agent framework you use.