Charting ate into patient time and kept nurses late. Ambient listening now captures notes in real time as they move room to room.
One of the largest healthcare systems in the United States, operating more than 50 hospitals and nearly 1,000 care sites across five states, with approximately 15,000 nurses providing direct patient care.
Growing electronic medical record requirements pushed nurses to spend significant portions of their shifts on charting, often working overtime to...
“Documentation has been one of the biggest sources of friction for our nurses.”
Multi-state health system operating hospitals and specialty clinics.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Mercy's Nursing documentation is part of this use case:
Related implementations across industries and use cases
Clinicians spent 1-2 hours after shifts typing notes. Now, AI drafts records from natural dialogue, restoring eye contact with patients.
Heavy charting forced clinicians to type during visits or after hours. Now, ambient AI drafts EHR notes, restoring patient connections.
Clinicians spent evenings buried in manual notes. AI now generates charts from audio, scaling from primary care to oncology.
Clinicians spent 1-2 hours after shifts typing notes. Now, AI drafts records from natural dialogue, restoring eye contact with patients.
Heavy charting forced clinicians to type during visits or after hours. Now, ambient AI drafts EHR notes, restoring patient connections.
Manual EHR reviews and false alarms overloaded clinicians. Now, AI delivers plain-language patient summaries and early-warning alerts.
Typing notes broke eye contact and caused late nights. Now, AI drafts records from spoken exam findings so vets stay present.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
Quality reviews dragged for weeks, gated by a handful of specialists. Now employees build agents that move them through in about an hour.
Charting ate into patient time and kept nurses late. Ambient listening now captures notes in real time as they move room to room.
One of the largest healthcare systems in the United States, operating more than 50 hospitals and nearly 1,000 care sites across five states, with approximately 15,000 nurses providing direct patient care.
Growing electronic medical record requirements pushed nurses to spend significant portions of their shifts on charting, often working overtime to...
“Documentation has been one of the biggest sources of friction for our nurses.”
Multi-state health system operating hospitals and specialty clinics.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Mercy's Nursing documentation is part of this use case:
Related implementations across industries and use cases
Clinicians spent 1-2 hours after shifts typing notes. Now, AI drafts records from natural dialogue, restoring eye contact with patients.
Heavy charting forced clinicians to type during visits or after hours. Now, ambient AI drafts EHR notes, restoring patient connections.
Clinicians spent evenings buried in manual notes. AI now generates charts from audio, scaling from primary care to oncology.
Clinicians spent 1-2 hours after shifts typing notes. Now, AI drafts records from natural dialogue, restoring eye contact with patients.
Heavy charting forced clinicians to type during visits or after hours. Now, ambient AI drafts EHR notes, restoring patient connections.
Manual EHR reviews and false alarms overloaded clinicians. Now, AI delivers plain-language patient summaries and early-warning alerts.
Typing notes broke eye contact and caused late nights. Now, AI drafts records from spoken exam findings so vets stay present.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
Quality reviews dragged for weeks, gated by a handful of specialists. Now employees build agents that move them through in about an hour.