Illustrative outcomes. Metrics in this case study reflect a representative deployment composite, not a single named client. Real client data is available under NDA on request.
A 12-provider clinic deployed Scribe, Aria, and Welcome to absorb documentation, scheduling, and patient intake. After 90 days: clinician admin time dropped from 2.5 hours per day to 35 minutes, same-day chart completion rose from 40% to 94%, no-show rate fell from 22% to 14%, and provider satisfaction climbed from 5.2 to 8.1 out of 10. Clinicians stopped taking work home.
A 12-provider clinic was losing providers to burnout. Clinicians spent 2.5 hours per day on documentation. No-show rate was 22%. New patient intake required 25 minutes of in-appointment paperwork.
We placed three AI employees into the clinic's existing EHR and scheduling stack. Each was scoped to a specific role, with clinical review built into every workflow.
Transcribes voice recordings into structured clinical notes — SOAP format for GPs, DAP for psychologists — and assigns ICD-10 codes. Notes are waiting in the EHR within minutes of dictation, so clinicians review and sign off in 2–3 minutes instead of taking documentation home. Scribe never stores raw audio.
Manages appointments, sends context-aware reminders, handles cancellations, and works the waitlist. Reminders reference the patient’s provider, appointment type, and any required prep — the specificity that turns a generic nudge into one patients actually act on, cutting no-shows.
Guides patients through digital registration, insurance upload, medical history, and consent forms before the visit. In-appointment intake dropped from 25 minutes of paperwork to about 5 minutes, and intake data is processed in an encrypted pipeline with no persistent storage of unprocessed PHI.
Measured against the same clinic's prior-quarter baseline.
Clinicians stopped taking work home. Notes are waiting in the EHR within minutes of dictation. Review and sign-off takes 2–3 minutes per chart, down from the evening documentation sessions that used to follow clinicians home.
Aria's no-show reduction was driven by personalized, context-appropriate reminders, not generic messages. The specificity of the communication, referencing the patient's provider, appointment type, and any prep required, made patients feel recognized rather than processed.
Provider satisfaction climbed from 5.2 to 8.1 out of 10 over a single deployment quarter.
All agents operate on HIPAA-compliant infrastructure. The privacy model was designed so that no unprocessed PHI is ever persisted.
All agents operate on HIPAA-compliant infrastructure. Scribe does not store raw audio — recordings are transcribed and discarded, and only the structured note persists in your EHR.
Welcome processes intake data in an encrypted pipeline with no persistent storage of unprocessed PHI. Data is de-identified before any content reaches the language model.
Every AI-drafted note is reviewed and signed by a licensed clinician before it enters the record. The AI drafts; the provider remains the author of record.
If your clinicians spend more than an hour a day on documentation, or your no-show rate sits above 15%, there's a good chance a healthcare AI workforce would pay for itself inside the first quarter, on HIPAA-compliant infrastructure, with a clinician reviewing every note.
Book a workforce discovery sessionYash Vibhandik is co-founder of 100xforce. He works directly with operations leaders and founders to design and deploy AI employees across e-commerce, healthcare, legal, accounting, real estate, recruitment, and SaaS workflows. He writes about what actually works (and what does not) when AI is deployed inside real teams.
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