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Catch burnout signals 3-6 weeks before they become resignations. Hear analyzes Slack patterns to surface early warning signs that managers miss.
Managers miss burnout detection signals every day. The engineer who stops joining optional meetings. The one whose messages get shorter and later. The senior dev who withdraws from social channels. These are all early warning signs — and they happen in Slack long before anyone raises a flag.
Response lag increases. Message length shrinks. After-hours spikes become the norm. Withdrawal from social channels accelerates. By the time burnout surfaces in a 1:1 or exit interview, you've lost weeks of intervention time — and often the person entirely.
Traditional tools can't catch this. Pulse surveys measure what people choose to report, not what they actually signal. And most managers are too busy shipping to notice the subtle shifts in team health that precede a resignation. The cost? Losing your best people to problems that were visible months ago — if you knew where to look.
Hear monitors communication patterns across all public Slack channels — message frequency, response times, thread participation, and engagement trends — to detect behavioral shifts that signal disengagement.
Track when your team is working outside normal hours. Sustained after-hours activity is one of the strongest predictors of burnout. Hear flags teams and individuals trending toward unsustainable patterns.
AI-powered sentiment analysis tracks how your team's tone evolves over time. Declining sentiment across messages is an early warning that shows up weeks before a burnout conversation happens.
When multiple signals converge — declining engagement, after-hours spikes, sentiment drops — Hear sends private alerts to managers so they can intervene early and protect employee retention.
Hear turns Slack communication into burnout detection intelligence. No surveys. No guesswork. Just signal.
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