Description
On-Call Health, from Rootly AI Labs, is an open-source tool that looks for early warning signs of overload in on-call engineers so teams can act before exhaustion turns into burnout. It connects to incident and workload sources such as Rootly or PagerDuty for incident data, Linear for ticket workload, GitHub for after-hours activity and Slack for communication patterns and context.
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To complement the ingested data, On-Call Health periodically sends short, low-friction surveys in Slack so responders can share how they're doing. It then computes individual risk scores across defined bands, from maintaining balance to needing immediate action, and uses AI to analyze what changed and what's driving it so managers can make informed decisions to protect their engineers.
The tool is designed to make on-call health measurable and fair, using team and individual-specific baselines to track trends over time rather than fixed thresholds or comparisons between people. AI-generated summaries help stakeholders quickly understand trends, turning weekly incident reviews into conversations about both systems and the people behind them, so teams can rebalance rotations, add automation, pause non-urgent work or staff up early.
- CategoryAI HR Management
- Pricing ModelOpen source
- DeploymentCloud
- PlatformsWeb
On-Call Health's Core Features
Early detection of on-call overload and burnout risk
Integrations with Rootly or PagerDuty, Linear, GitHub and Slack
Periodic low-friction sentiment surveys in Slack
Individual risk scores across defined bands
Team and individual baselines to track trends over time
AI analysis of what changed and what's driving risk
AI summaries for weekly incident reviews
Open source
How to use On-Call Health?
Connect signals: Link incident data from Rootly or PagerDuty and add Linear, GitHub and Slack.
Collect sentiment: Enable periodic short Slack surveys for responders to share how they're doing.
See who's at risk: Review individual risk scores computed from the ingested data.
Act early: Use AI analysis and summaries to rebalance rotations, add automation or staff up before burnout.
On-Call Health's Use Cases
- Preventing on-call burnout
- Fair on-call measurement
- Data-informed rotation changes
- People-aware incident reviews
