Intake AI
The front door of the hub.
Multi-channel intake that turns fax, portal, email, API, and EHR referrals into clean, structured cases — automatically.
Why Patient Access teams need this
The realities we hear from operators — the ones that don't show up in product demos.
Faxes, portals, EHR referrals, and emails arrive in every shape imaginable.
Most intake time is spent re-keying fields the system could have read.
Patients and cases get created twice — triaged by different agents.
If extraction fails silently, errors propagate downstream.
Outcomes, not algorithms
We lead with the business outcome — the mechanism sits behind a stable interface.
OCR + LLM extract fields with explicit confidence scores.
Patient and case dedup catches repeats at ingestion.
Only low-confidence items reach humans — with context attached.
Every downstream app inherits a clean, consistent case.
A controlled view of the flow
We share the stages — not the internal logic, models, or scoring methods.
The agents that run inside this solution
Each agent operates inside explicit boundaries — with confidence thresholds, audit logs, and human escalation built in.
Where this sits in Patient Access
This capability isn't a silo — it plays with every actor across the journey.
Measured against the metrics that matter
We publish outcome ranges, not point claims — every number is validated in-context.
Fits the way you work
Embed inside your platform, run alongside it, or consume through API — your call.
See Intake AI in your environment.
A focused walkthrough against scenarios that mirror your hub or SP — no theoretical decks.