TraceRoot.AI
AI agents that automatically fix production bugs with a PR
What is TraceRoot.AI? Complete Overview
TraceRoot.AI revolutionizes debugging workflows by leveraging AI agents to automatically identify and fix production bugs through pull requests (PRs). It analyzes telemetry data, source code, and repository history to pinpoint root causes efficiently. The platform integrates seamlessly with leading frameworks like CAMEL and OWL, offering structured visualization and automation for developers and enterprises. Trusted by companies such as Autosana, Autumn, and HeyBreez, TraceRoot.AI is designed for developers and teams looking to streamline their debugging process and reduce downtime caused by production issues. The tool is particularly beneficial for startups and enterprises aiming to enhance their DevOps workflows with AI-driven automation.
TraceRoot.AI Interface & Screenshots
TraceRoot.AI Official screenshot of the tool interface
What Can TraceRoot.AI Do? Key Features
AI-Powered Debugging
TraceRoot.AI uses AI agents to analyze traces, logs, and code history to automatically detect and fix bugs. The AI can create PRs to resolve issues, reducing manual debugging time significantly.
Multi-Agent Collaboration
The platform supports collaboration between AI agents (e.g., GitHub Agent, Slack Agent) to fetch contextual data from various sources like source code, Slack conversations, and Notion docs, providing comprehensive insights.
Structured Visualization
TraceRoot offers a visualization platform to explore traces and logs, helping users understand issues deeply. The UI displays source code context, making debugging intuitive.
Seamless Integrations
Integrates with GitHub, Slack, Notion, and monitoring tools, allowing users to sync their existing workflows effortlessly. Supports Python and JavaScript via PyPI and npm packages.
Auto-Triaging
The Pro and higher plans include AI agents that auto-triage production issues, categorizing and prioritizing bugs based on severity and impact.
Best TraceRoot.AI Use Cases & Applications
Production Bug Fixing
A startup uses TraceRoot.AI to automatically detect and fix runtime errors in their microservices, reducing downtime and developer overhead.
DevOps Automation
An enterprise integrates TraceRoot with their CI/CD pipeline to auto-triage and resolve issues before they escalate, improving release stability.
Team Collaboration
A distributed team leverages TraceRoot’s Slack and Notion integrations to contextualize bugs with past discussions and RFCs, speeding up resolutions.
How to Use TraceRoot.AI: Step-by-Step Guide
Install the TraceRoot SDK via PyPI or npm to capture traces and logs from your codebase.
Decorate functions with `@traceroot.trace()` to log events and errors, which are sent to the TraceRoot cloud service.
Connect your GitHub, Slack, or Notion accounts to provide context for the AI agents.
Let the AI agents analyze traces and logs to identify root causes and suggest fixes.
Review and merge the auto-generated PRs to resolve the bugs.
TraceRoot.AI Pros and Cons: Honest Review
Pros
Considerations
Is TraceRoot.AI Worth It? FAQ & Reviews
TraceRoot.AI is an AI-powered debugging tool that automates bug detection and fixing by analyzing traces, logs, and code history.
It uses AI agents to scan your codebase, identify root causes, and generate PRs with fixes. Integrations provide additional context.
Python and JavaScript via PyPI and npm, with more languages coming soon.
Yes, the STARTER plan offers a 7-day free trial.
Yes, higher-tier plans include SOC2/ISO27001 compliance and HIPAA-ready BAAs.