deep breath
deep breath
Deep Breath turns high-resolution ICU data into actionable, transparent insights aligned with local clinical workflows.
ICU teams are already drowning in continuous streams of alarms, measurements, waveforms, and clinical data. Too many of these alerts are non-actionable, fueling alarm fatigue and obscuring the clinically meaningful changes that actually require attention.
Deep Breath generates notifications based on repeated patterns, persistent trends, and clinically relevant changes — not isolated single values. Because every ICU has its own protocols, staffing models, and escalation pathways, the decision support logic can be configured to match local clinical practice instead of forcing a one-size-fits-all approach.
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Deep Breath goes beyond delivering notifications. It also captures what happens afterward — whether clinicians responded, how quickly, what actions were taken, and whether local protocols were followed.
This creates a closed feedback loop that helps hospitals continuously refine decision support, improve protocol compliance, strengthen clinical training, and identify workflow bottlenecks. When connected to the Deep Breath Research platform, these structured event data become a valuable foundation for quality improvement initiatives and real-world clinical studies.
Closed feedback loop
Deep Breath is built as a clinician-grounded platform that can safely integrate hospital-owned or validated third-party AI models into real clinical workflows.
Because it was co-developed with ICU teams, the system provides the necessary clinical context and — crucially — continuous performance, bias, and drift monitoring to keep integrated models trustworthy over time.
Book a walkthrough of workflow-aware decision support — or tell us about your ICU data and clinical workflows.
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