Airbrake is a leading error monitoring and performance management platform that helps teams identify and resolve application issues in real-time.
Enhance your error management with AI Agents that can automate incident response and optimize application performance.
Airbrake provides real-time error tracking and performance monitoring. Relevance AI transforms this data into intelligent action through AI Agents that can automatically detect, analyze and respond to application issues.
Proactive Error Resolution
The agent can automatically detect and resolve errors before they impact users.
Intelligent Performance Insights
The agent analyzes performance data to suggest optimizations for enhanced efficiency.
Automated User Feedback Analysis
The agent categorizes user feedback and correlates it with error reports for prioritized fixes.
Relevance AI gives you access to Airbrake's error monitoring and performance management capabilities within your AI-powered workflows.
What you’ll need
You don't need to be a developer to set up this integration. Follow this simple guide to get started:
- An Airbrake account
- A Relevance AI account with access to your project settings
- Authorization (you'll connect securely using API keys—no sensitive info stored manually)
Security & Reliability
The integration uses secure OAuth authentication, ensuring only authorized workflows access your Airbrake error monitoring data. Relevance AI handles API operations in the background while managing error tracking, notifications, and project analytics—so you don't have to worry about implementation details or rate limits.
Built-in validation and error handling ensure your error monitoring workflows run reliably, with automatic formatting of error data and stack traces.
No training on your data
Your data remains private and is never utilized for model training purposes.
Security first
We never store anything we don’t need to. The inputs or outputs of your tools are never stored.
Best Practices for Non-Technical Users
To get the most out of the Airbrake + Relevance AI integration without writing code:
- Configure error grouping: Set up meaningful error grouping patterns for better organization and analysis.
- Use proper environments: Separate development and production error tracking for cleaner monitoring.
- Set notification rules: Configure targeted alerts to avoid notification fatigue and focus on critical issues.
- Implement error context: Add relevant user and system data to make debugging more efficient.
- Monitor rate limits: Stay within API request limits to ensure consistent error tracking and reporting.
