Corti

Corti listens to the emergency call stream.

AI identifies agonal breathing patterns using acoustic models.

Visual alert pops up on dispatcher's screen.

Dispatcher initiates CPR instructions immediately.

Physician activates Corti during the patient visit.

Corti captures the dialogue and filters out small talk.

AI structures findings into a SOAP note format.

Physician reviews and signs off in the EHR.

Patient describes symptoms over video call.

Corti cross-references symptoms with clinical protocols.

AI suggests appropriate level of care (Self-care, Urgent Care, ER).

Nurse confirms the triage recommendation.

Calls are automatically transcribed by Corti.

NLP engine flags calls where protocols were bypassed.

Managers review a dashboard of 'at-risk' interactions.

Training is targeted to specific staff members based on data.

Corti analyzes the clinical encounter record.

AI suggests relevant ICD-10 and CPT codes.

Medical biller verifies and submits the claim.

System learns from corrections to improve accuracy.

Corti tracks key health markers mentioned in verbal check-ins.

AI generates a trend report for the clinician.

Provider adjusts treatment plan based on longitudinal data summaries.

Notes are updated to reflect the new care plan.

Corti monitors calls for specific linguistic markers of crisis.

AI triggers immediate supervisor notification for high-risk cases.

System provides resource links for the operator to share.

Call is documented with risk-level flags.