Narrative is ambiguous. Billing cannot be.
When clinical data is ambiguously extracted, automation compounds the error. We prevent that.
Narrative is ambiguous. Billing cannot be.
Every code tethered to the exact sentence in the note. Click any code, see the proof.
90%+ rule-based. Same note, same result, every time. Your compliance team can trace every decision.
Runs alongside existing workflows. No process change. No workflow disruption required.
We can.
Same note in, same codes out. Every time.
No sampling variance. No temperature. No drift.
Tested and verified.
Every code traces back to a sentence in the note.
No black box. Full decision trace.
AI proposes. The engine decides. The human confirms.
0% AI-decided.
“Run the same note 100 times. Get the same codes 100 times. No other AI coder can do that.”
We don't know what our system would do to your company — but you do. Play with the sliders and see.
Percentage point lift from cleaner first-pass claims
Specificity upgrades, HCC capture, OCR recovery
Fewer denials from cleaner first-pass claims
More claims per coder when search time drops 60%+
Better coded data → more downstream referrals, services, RAF
Volume pricing: higher volume → lower rate
27× return on VMC investment
30% EBITDA capture × 12× multiple
The missing layer in revenue architecture.
Automation assumes the clinical input is stable. It isn't.
We normalize the narrative into code-aligned clinical states before downstream systems execute.
Where unstable clinical states are contained.
Each artifact demonstrates a failure point that would have propagated downstream.
The note contains conflicting documentation: 'acute exacerbation' in HPI vs 'stable COPD' in assessment. The system flagged this conflict before submission, preventing a certain denial.
Unstable clinical states prevented before submission. Deterministic rule execution at production scale.
These are not optimizations. This is upstream containment — not downstream rework.
We encoded clinical instability rules into a deterministic extraction engine.
This engine executes before claims logic, not after.
Versioned. Auditable. Production-tested. Not assembled via prompt orchestration.
Because extraction is deterministic, PHI is contained at the architecture level — not by policy, by structure.
Because PHI is contained, AI reasoning can safely operate on structured clinical state — without leaking protected data.
Because it is versioned and auditable, AI becomes an assistant, not a liability.
Four lenses. One platform.
Integrates upstream of enterprise RCM platforms. No workflow disruption. No process change.
“Denials are not a payer problem. They are an extraction problem.”
Assertion conflicts are surfaced before submission. Every billed code is tethered to the exact sentence that supports it — not guessed.
“PHI cannot leave unless explicitly cleared. By architecture, not policy.”
Three-layer fail-closed egress gate. Default is block. Your security team can audit every rule before a single note is processed.
“Coder search time exists because the narrative was never normalized.”
We eliminate narrative search. The system builds a structured, evidence-linked claim draft — coders verify and approve, not hunt.
“Missed HCCs are not documentation gaps. They are linkage failures.”
HCC preservation guard prevents category collapse from specificity drift. Every recovered code is backed by documented clinical evidence.
Extraction gives you the data. This gives you control.
Your rules. Your denial learnings. Encoded as deterministic governance — not code changes.
Local rule overlays — NCCI edits, modifier requirements, linkage checks, payer-specific denial patterns — run before submission.