Artificial Intelligence | Factum AI™

Private NLP inference converts thousands of chart pages into a ranked merit score - then automatically routes each claim to the correct legal action. All processing happens inside your sovereign infrastructure. Zero PHI leaves your perimeter.

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How Factum AI Processes Every Claim

Six sovereign AI modules work in sequence from intake through litigation - each purpose-built for a specific phase of the revenue cycle.

Medical Necessity Detection

NLP scans clinical notes, ABG values, and treatment documentation to extract structured medical necessity indicators aligned with payer LCD/NCD policies.

ICD-10 ExtractionLab Value ParsingSeverity Scoring

Litigation Merit Scoring

A weighted multi-factor model computes a 0–100 merit score based on clinical evidence strength, payer friction history, and contract variance analysis.

Weighted ML ModelPayer Pattern DBContract NLP

Automated Document Review

Processes hundreds of chart pages in seconds - highlighting key passages, flagging contradictions, and structuring evidence into court-ready format.

OCR + NLP PipelineEvidence BundlingContradiction Flags

Sovereign AI Inference

All clinical data stays inside your private infrastructure. No PHI transmitted to external AI APIs. Models trained exclusively on your case history.

Private LLMZero Data EgressCustom Training

Payer Friction Intelligence

Tracks denial patterns by payer, facility, and diagnosis code. Surfaces statistical evidence of systematic underpayment for litigation leverage.

Denial Pattern DBStatistical AnalysisTrend Detection

Workflow Automation Triggers

When a claim exceeds the merit threshold, Factum AI automatically routes it to the correct workflow phase - no manual triage required.

Rule EnginePhase RoutingSLA Enforcement
Interactive Tool

Litigation Intelligence Control Room

Adjust the three scoring inputs to see the merit score update in real time, then run the AI document parser to watch clinical data get extracted and classified.

Scoring Inputs
Clinical Evidence Strength(ICD + labs + notes)
42
LowHigh
Historical Payer Friction(denial pattern score)
38
LowHigh
Contract Variance Value(underpayment delta)
29
LowHigh

Score Breakdown

Clinical (45%)
19
Payer (35%)
13
Contract (20%)
6
Merit ScoreHOLD
025507510038MERIT SCORE

Automated Action

Hold - Insufficient Evidence for Litigation

Clinical documentation does not meet minimum merit threshold. Case should be returned to billing for additional documentation or closed.

  1. 1Return to billing team
  2. 2Request complete medical record
  3. 3Document denial rationale
  4. 4Consider administrative appeal
Score 38/100 · Factum AI v4.2 · 1:59:26 PM
Unstructured Chart Feed
READY
ADMPatient admitted 03/14/2024 – acute respiratory failure, O2 sat 84% on room air.
DXPrimary: J96.01 Acute respiratory failure w/ hypoxia. Secondary: J18.9 Pneumonia, unspecified.
TXInitiated BiPAP therapy, IV Levaquin 750mg QD, methylprednisolone 125mg IV Q6H.
NOTEAttending physician note: Patient deteriorating, ICU admission warranted per severity scoring.
LABABG: pH 7.28 / PaCO2 58 / PaO2 52 / HCO3 26.4 - consistent with acute hypercapnic failure.
DENYPayer denial: UHC EOB dated 04/01/2024 - "Level of care not medically necessary, outpatient equivalent available."
POLUHC Medical Policy MP-025.19: ICU admission criteria requires PaO2/FiO2 < 200 or acute organ failure.
CNTHospital contract §4.2(b): Payer must provide written rationale within 30 days of denial; none received.
HISTCase history: Payer denied 3/3 similar ICU admissions for this facility (FY2023). All appealed successfully.
OUTExpected recovery value: $47,200. Contract rate multiplier: 2.3x per amendment dated 01/2023.
NLP Extraction Engine
Zero PHI egress
ICD-10 CodeJ96.01-
O2 Saturation84% (room air)-
ABG pHJ96.01-
Level of CareICU admission-
Denial CodeMP-025.19-
Contract Clause§4.2(b) - 30d-
Payer Friction3/3 denials-
Recovery Value$47,200-

RCM AI Embedded in Every Workflow Phase

From first intake through final case closure, Factum AI surfaces intelligence at the exact moment your team needs it - without switching context or running external tools.

01

Claims Submission

Claim scrubbing + rejection classification

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02

Payment Posting

ERA matching + underpayment detection

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03

Patient Billing

Responsibility calculation + plan scoring

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04

Denial Management

Merit scoring + appeal letter generation

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05

Continuous Model Improvement

Closed case outcomes feed back into the AI.

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