Sentinel is an AI-powered on-call agent that automates incident diagnosis and response for engineering teams. It reduces alert noise and system downtime by performing root cause analysis and surfacing intelligent insights to accelerate investigations.
Funding
Funding not disclosed
Founders
Product
Problem
Current observability platforms generate excessive telemetry and alerts, overwhelming engineering teams without providing actionable solutions for incident resolution. This leads to increased alert fatigue and prolonged system downtime.
Solution
Sentinel is an AI-powered on-call agent designed to automate incident diagnosis and response, thereby reducing alert noise and system downtime. It continuously monitors system alerts, performs parallel root cause analysis using historical data and internal knowledge, and surfaces intelligent insights to accelerate human investigations. Sentinel also automates post-mortem documentation and suggests preventative measures. By integrating with existing telemetry stacks, Sentinel acts as an autonomous investigator, enabling engineering teams to resolve issues faster and focus on development.
Target Audience
Sentinel targets DevOps, SRE, and engineering teams responsible for maintaining system uptime and reliability in complex production environments.
Features
- Continuous, 24/7 monitoring of system alerts for immediate incident detection.
- Parallel hypothesis generation leveraging historical data and organizational knowledge.
- AI-driven investigation to autonomously surface intelligent insights and accelerate human analysis.
- Automated root cause analysis with supporting evidence and comprehensive data analysis.
- Automated generation of incident reports and actionable remediation suggestions.
- Read-only integration with existing telemetry stacks.
- Configurable data exposure and access permissions, mirroring new engineer onboarding.
- Proprietary ML models fine-tuned with organizational best practices.