What is Relvy?
Relvy offers an agentic AI assistant specifically designed to accelerate the debugging process for alerts and incidents. By learning and collaborating with users, it aims to significantly reduce the Mean Time To Resolution (MTTR). The tool is built to identify the root cause for a substantial percentage of issues autonomously, improving its accuracy over time through user feedback and interactions.
Unlike black-box solutions, Relvy emphasizes transparency by clearly explaining its reasoning process. This collaborative approach helps teams not only resolve issues faster but also build confidence in the AI's capabilities. It adapts to existing debugging workflows without compromising data privacy, as user data is not utilized for model fine-tuning.
Features
- Agentic AI Debugging: Utilizes agentic AI to assist in troubleshooting alerts and incidents.
- Collaborative Learning: Learns from user questions, feedback, and interactions to improve accuracy.
- Root Cause Identification: Aims to accurately identify the root cause for over 70% of alerts or incidents.
- Transparent Reasoning: Shares its analysis process openly, avoiding a black-box approach.
- Adaptive Workflow Integration: Adapts to existing team debugging processes.
- Privacy Focused: Does not use customer data for model fine-tuning.
Use Cases
- Accelerating incident root cause analysis.
- Reducing Mean Time To Resolution (MTTR) for system alerts.
- Assisting engineering teams in debugging complex issues.
- Improving system reliability by identifying issues faster.
- Collaborating on troubleshooting within development and operations teams.
