Hub AI
The AI intelligence layer across the suite.
A shared AI platform that powers intake, risk, NBA, copilots, data quality, and HITL across every AccessHub app — with model registry, prompt studio, and audit built in.
Why Patient Access teams need this
The realities we hear from operators — the ones that don't show up in product demos.
Each app ships its own model — governance becomes impossible.
AI in intake can't talk to AI in denial prediction.
Prompts, models, and rules drift without versioning.
Every team builds its own review queue, poorly.
Outcomes, not algorithms
We lead with the business outcome — the mechanism sits behind a stable interface.
Intake AI, Risk, NBA, Routing, GenAI Copilot, Data Quality — reusable across apps.
One review-queue framework powers every app.
Versioning, A/B testing, rollback across the stack.
Outcomes route back into retraining and rule tuning.
A controlled view of the flow
We share the stages — not the internal logic, models, or scoring methods.
Hub AI in the case workspace
AI services surfaced directly inside case work — copilots, risk scores, and next-best-action without leaving the flow.
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.
Where this fits in the solution family
See Hub AI in your environment.
A focused walkthrough against scenarios that mirror your hub or SP — no theoretical decks.