TraceRoot.AI is an open-source, AI-enhanced production debugging platform that automatically identifies, analyzes, and helps fix production issues by combining logs, traces, code context, and team discussions.

This agentic debugging platform ties all your context together and helps development teams get to the root cause through AI agents that automatically summarize issues and trace logs, spans, and GitHub context into a single execution tree.

The platform visualizes complex production data in interactive tree structures, making it easier to understand how distributed services interact and where problems originate. Rather than manually sifting through countless log entries, developers can ask the AI agent natural questions about bugs and receive contextual insights.

TraceRoot's AI agents actually do the work by pulling together logs, traces, code, and related context into one place, explaining the problem, and linking every insight back to the original data for trustworthy analysis. The system can even draft potential fixes and open GitHub issues automatically.

Integration happens seamlessly through lightweight SDKs that capture structured traces and logs without impacting application performance. The platform connects with existing tools, including GitHub, Slack, and other development infrastructure, to provide comprehensive context during debugging sessions.

The platform integrates into your development workflow, providing real-time trace and log analysis, code context understanding, and intelligent assistance. Teams get a 7-day free trial through TraceRoot Cloud to experience the full capabilities.

The open-source nature ensures transparency and community-driven improvements while maintaining enterprise-grade debugging capabilities for distributed systems and microservices architectures.

Features



• AI Agent Analysis: Autonomous agents that summarize issues, analyze traces, and provide contextual debugging insights automatically
• Interactive Execution Trees: Visualizes logs, traces, and function calls in structured tree formats for easier problem identification
• Multi-Source Context Integration: Combines GitHub PRs, issues, Slack discussions, and code context for comprehensive debugging
• Lightweight SDK Integration: Captures structured traces and logs with minimal performance impact on production systems
• Automatic Fix Generation: AI agents can draft potential solutions and create GitHub issues for identified problems
• Real-Time Analysis: Provides immediate trace and log analysis with intelligent assistance during debugging sessions