Mechanisms that are built and running — not recovery percentages we have no customers to prove yet.
Revenue integrity
Not a claim about recovery rates — we have no customer outcomes to quote yet, and we will not invent them. What follows is a list of mechanisms that are built and running, each of which catches money that is currently leaving quietly.
The one nobody models
A patient asks for a better room. The rate difference is ₹2,000 a night. Over four nights that is ₹8,000, and the counter says yes.
It is not ₹8,000. Breach the room-rent cap and most Indian policies apply a proportionate deduction to every associated charge — surgeon fees, OT, investigations, consumables — cut in the same ratio as the room breach.
The difference is what the hospital absorbs, and what the billing manager finds out about at settlement.
Every item below is a mechanism that exists in the product today.
An ICD-10 engine built for Indian clinical shorthand. “Sugar,” “loose motions,” “koch’s,” “daad,” “kamzori” all resolve correctly. Dengue, typhoid, malaria, TB and scrub typhus are first-class, not exotic imports.
Deterministic, offline, about a millisecond. It cannot invent a code that does not exist.
Code a phrase twice and it is suggested instantly from then on. Unspecified catch-all codes are flagged — payable, but the ones TPAs query.
Coverage dashboard, accept-rate by confidence, and a report of the phrases it keeps getting wrong.
The ambient scribe extracts the diagnosis, attaches the ICD-10 code, and stamps provenance on acceptance. Hindi, Marathi and Tamil supported.
The consultation and the coding stop being two separate jobs.
24 rules across documentation, authorisation, identity, timing, money and payer history — weighted probabilistically, so scores stay separable instead of every messy claim pinning at 100.
Unknown facts never fire a rule. No tariff on file means silence, not a false accusation.
The worklist sorts by exposure — risk multiplied by amount — not raw risk. Claims sharing a cause are aggregated so one correction clears the batch.
A 12% risk on ₹4L outranks an 80% risk on ₹6,000.
Diagnosis, codes, doctor and proposed treatment pulled from what is already recorded. Incomplete sends are blocked with the missing item named.
The notification clock — 24h emergency, 72h planned — is tracked. It decides whether an admission stays cashless.
The settlement advice is parsed line by line, and the shortfall split into predicted-and-accepted versus unexplained. The second list is what you query.
Copay is excluded from “lost” — that money is collectable, not gone.
Hospital course composed from the treating doctor’s own dated notes, never a generated narrative. Abnormal results named, normal panels collapsed, discharge meds limited to what is still running.
Quality-scored, because a summary that says nothing gets queried as often as a missing one.
Rate cards imported by pasting straight from the spreadsheet. Catches billing above agreed rates, packages billed alongside their components, and unpriced codes.
Ward rates suggested from what you have already been billing.
Recurring denial reasons are mined into proposed rules with the evidence attached. Proposed, never auto-applied — a human accepts each one.
Risk weights calibrate from your own settled claims, shrinking from assumption toward measurement.
ABHA linking, FHIR R4 records and consent flows. NHCX-ready claim bundles built and validated, with a readiness check naming exactly which of six things blocks your onboarding.
We generate and validate the payload. Transmission runs through your NHA onboarding.
For groups: which of your six clinics is losing the most, and why. One payer contract set applied across every branch, one consolidated view.
A question only a group owner has, and one nobody currently answers.
A hospital that catches one exaggeration stops trusting all of it. So, plainly:
Bring one month of settled claims and we will show you what the engine would have flagged before they went out.