Your revenue cycle shouldn't run on 2am overtime.
A private AI that reads charts, scrubs claims, and works denials before they age.
Private model. Your data stays yours.
What the week actually looks like in Healthcare & RCM
Charges posted late because coding queues back up
Denials worked only after they age past appeal windows
Eligibility checked manually across a dozen payer portals
Documentation gaps found after the claim is already out
AR follow-up prioritized by whoever shouts loudest
Payer rule changes discovered through rejections
Month-end reporting rebuilt by hand in spreadsheets
None of this is a people problem. It's work that never should have needed a person.
A private AI model, trained on your business, put to work on the grind.
Trained on your material
Your files, templates, and rules — so output arrives already in your format and voice.
Runs on your side of the wall
Private cloud or on-premise. Nothing leaves for a public model.
Humans stay in the loop
The model drafts and checks. Your team approves and ships.
Four weeks from first call to work coming off your plate.
- STEP 01
We watch the work
One discovery call plus a short workflow review. We map where hours actually go — not where an org chart says they go.
- STEP 02
We train on your business
Your documents, templates, tone, and rules become the model's training set. About a week, no engineering lift from your team.
- STEP 03
We wire it into the day
The model sits where the work already happens — inbox, drive, or your line-of-business system — and produces drafts your team approves.
- STEP 04
We tune it on real output
Two free weeks on live work. Corrections feed straight back into the model, so week two is measurably better than day one.
What changes in the first month.
Hours back, every week
The repetitive drafting and re-keying stops being a person's job.
Faster cycle times
Work moves in minutes instead of waiting on someone's queue.
Fewer errors and rework
Checks run on 100% of items, not on the sample somebody had time for.
Capacity without headcount
Volume grows without another hire, another desk, another ramp.
Consistent output
Every document reads like your best person wrote it, every time.
Your people on real work
Judgment, clients, and growth — not clerical throughput.
Why private beats a public chatbot subscription.
Your data never trains someone else's model
No public API, no shared tenancy, no vendor learning from your business.
Hosted your way
Private cloud or on-premise on your own hardware. You choose where the model lives.
One-of-one, not a generic assistant
The model is trained on your files, your rules, your wording — it isn't a prompt on top of a chatbot.
Small models, sane economics
A focused model that does your ten jobs beats a giant one billed per token forever.
More on the reasoning: why small private models win.
Where we'd start in Healthcare & RCM
Automated claim scrubbing against payer-specific rules
Denial triage with drafted appeal letters
Eligibility and benefits summaries before the visit
Coding support from clinical documentation
AR worklists prioritized by recoverable dollars
Payer-mix and denial-trend reporting on demand
Fifteen minutes to find the first workflow worth automating.
One discovery call. One week of training. Two free weeks on your real Healthcare & RCM work — then you decide.