Authorized for federal operation FedRAMP High VA National ATO $250B in claims under analysis

The sequencing engine

A claim walks in.
A cited number
walks out.

Not a rules engine — rules are why the system is stuck. The Claims Genomics Model is a learning system: it turns every claim into a 48-feature genome, learns what normal looks like from your own data, and argues both sides before a human signs.

19µs per claim, pre-paymentVA pre-payment engine · production telemetry 95.2% accurate vs. paid historyvalidated against VA adjudicated history ~14% of our own work self-blockedself-review gate · engineering telemetry

Step 01 — Sequence

Every claim becomes a genome.

48 features.
Two strands.
One vector.

The care strand carries the clinical truth — diagnoses, trajectory, dose plausibility. The claims strand carries the financial truth — codes, charges, payer behavior. Most systems read one. The genome reads both, together.

dx cluster · I48.92 charge vs. ASP treatment trajectory MUE practitioner limit dose plausibility charge vs. MPFS episode coherence payer 835 pay-rate chart-note proximity ±3d timely-filing posture units · decimal pattern …37 more per claim

An autoencoder learns normal from tens of millions of your own claims — then flags what doesn't reconstruct. No hand-written rules. 28 novel patternsunsupervised discovery · integrated-payer engagement found this way that no rulebook contained.

Step 02 — Argue

Both sides, against ourselves, on every claim.

A claim's path across the desk.

The same handoff a denied claim walks in a real revenue-cycle shop — each stage has one owner, and payer intelligence feeds the routing the whole way.

surfaced

The genome flags it

The sensor finds the claim and its dollars.

coded

The Coder

Chart vs. billed line — dose & units plausibility.

adjudicated

The Adjudicator

Adjudicable? Cleanest legal posture; timely-filing.

routed

The Router + desk

Right CPAC, signatory & address; desk tailors posture.

audited

The Auditor

No claim without a quote. CLEARED / FIX / HELD.

decided

The Director

One payer-tailored plan; recommends go / no-go.

approved

You

A person clicks Approve & file. Nothing auto-mails.

adversarial by design — CCPRA argues the provider · CCPVA argues the payer · a human rules

Step 03 — Show the work

Glass-box, or it doesn't ship.

Every determination shows its receipts.

A risk score is an opinion. A determination is a case — cited to the contract clause, the code, the regulation in force on the date of service, and the chart. Defensible to provider, payer, and regulator alike.

The self-review gate blocks ~14% of our own work before it ships. Trust is built by what you refuse to send.

Objective value$2,847.50
Variance vs. billed−$1,113.20

Seven pillars — each cited, each independent

  • Contract — rate sheet §4.2, in force on DOScited
  • Code — CPT 99291 + MUE limitcited
  • Regulation — 38 CFR §17.1002 (layperson std.)cited
  • Chart — TIU note within ±3 days of DOSquoted
  • Payer policy — versioned by date of serviceon file
  • Human authority — reviewer signs the determinationsigned
Benefit of the doubt · never deny on ambiguity — route to a human

Step 04 — Move first

Pre-payment, not pay-and-chase.

19 microseconds.
Before the dollar moves.

Recovery is the apology; prevention is the product. The same genome that wins appeals scores every claim pre-payment — so gaming stops paying and pay-and-chase ends.

before the dollar moves
The pre-payment validation harness: 95.2% accurate, 100% consistent, 19 microseconds per claim, 100% transparent
THE HARNESS — four things a nurse trusts before it runsaccurate, consistent, fast, and memorialized — every decision auditable forever
The engine earns automation one mode at a time: shadow, then recommend, then automate
EARNED AUTONOMY — shadow → recommend → automatethe engine earns each mode with evidence — the org stays in control

Step 05 — Hunt where the waste lives

High-volume, low-value — that's where a genomic profile pays.

Everyone audits the whales.
The waste is in the krill.

Inpatient is high-dollar and well-policed — ~2% improperCMS CERT FY2024. The waste concentrates in millions of small claims a day — where rules engines can't tell a justified course of care from a non-tapering episode. Clinical signal and billing signal have to be read together.

servicebilling patternclinical signal that decides it
Behavioral healthSession-length upcoding · 90837→90834Flat functional scores; short sessions billed long
Physical therapyNon-tapering, flat trajectory · 97110AM-PAC plateau past week 16
LabComponent billing vs. panel · 80048→80053Same-day draws; 14 tests unbundled

improper-payment rate by service family · sourcesCMS CERT FY2024 · OIG A-05-14-00041 · A-09-21-03006 · A-06-23-01002

Inpatient IPPS
~2%
Home health
6.7%
Skilled nursing
15.1%
Behavioral health
58%
Physical therapy
61%
ABA (Medicaid)
100%*

Medicare FFS average 7.66% · *sampled enrollee-months with any improper line

The provider sees it before the claim goes out — not after a recoupment letter. The patient gets the right service at the right intensity. Abrasion goes down, not up.

Federal-grade, by construction

Built where the bar is highest.

Authorized against the most demanding security baseline in U.S. healthcare, running against VistA, Cerner, and Epic in production. First deployment to a national ATO in under 18 monthsVA authorization record.

FedRAMP High VA National ATO 421 NIST controls 100% HIPAA VistA · Cerner · Epic Glass-box by design

See it on your data

Bring your 837s and 835s.
We'll show you the DNA.

A scoped read of your claims — the recoverable pool by path, every number with its provenance, in weeks not quarters.