Try Demo
AI Claims Decision Intelligence Infrastructure

See the Risk Behind Every Healthcare Claim.

An explainable AI decision layer for health insurers, TPAs, and public health schemes. LiceronTech ingests unstructured hospital bills, clinical notes, discharge summaries, and policy tariffs to detect financial leaks, synthetic documents, and coordinated fraud networks before money leaves the door.

Launch Live Claims Sandbox Calculate Preventable Leakage
ABDM M1-M3 Ready
100% Grounded Evidence Cards
DPDP Act 2023 Compliant
Live Stream Ingestion
Claim #CLM-2026-8891 (₹4,82,600)
Evaluating 8 Gates
1. Multimodal Parsing (32 files) Passed
2. Identity & ABDM Registry Check Matched
3. Policy Coverage & Exclusions Covered
4. Tariff & Contract Verification ₹86,600 Discrepancy
5. Network Anomaly & FraudGraph™ Cluster Detected
Recommended Adjudication
Medical + Financial Review
Inspect Evidence
1.28M+
Health Claims Ingested
Across public schemes & private health insurers
₹42.8 Cr
Preventable Leakage Flagged
Unbundled tariffs, synthetic bills & duplicate claims
99.2%
Investigator Precision
Zero hallucination via grounded deterministic rules
18.4x
Average Enterprise ROI
Net annual loss recovery versus platform deployment fee
Financial Loss Attribution

Where Health Insurers Lose Money

Fraud is only one source of claims loss. LiceronTech eliminates financial leakage across the complete claims lifecycle: hospital overcharges, network collusions, duplicate services, and narrative contradictions.

₹18.2 Cr Exposure 42.5%

Hospital Tariff Deviations

Hospitals billing unbundled line items (e.g. Catheter Kits, OT consumables) that are already included in negotiated package agreements.

TariffGuard™ module compares every line item against contracted rate cards in 200 milliseconds.
₹9.4 Cr Exposure 22.0%

Coordinated Fraud Rings

Organized networks of doctors, diagnostic laboratories, and insurance brokers submitting repeated synthetic claims with matching document templates.

FraudGraph™ engine maps cross-entity links to uncover clusters invisible to single-claim checks.
₹6.7 Cr Exposure 15.6%

Clinical & Narrative Inconsistencies

Contradictions between initial emergency calls, casualty admission logs, and operative doctor summaries that mask Medico-Legal or exclusion issues.

Clinical Consistency Model cross-evaluates multimodal text, speech, and medical ICD/CPT coding.
₹4.2 Cr Exposure 9.8%

Duplicate & Overlapping Claims

Identical diagnostic scans, pharmacy invoices, and nursing charges billed across multiple policies or different family member health cards.

₹2.8 Cr Exposure 6.5%

Policy Sub-Limit Non-Compliance

Room rent proportionate deductions, waiting period exclusions, and procedure ceilings calculated incorrectly by manual claims teams.

Net Recovery Total

₹42.8 Cr Annual Savings

Total preventable losses captured across 1.28M claims with automated STP pass-through for 42% of clean submissions.

Unified Claims Intelligence

Not Just a Fraud Score — Complete Decision Intelligence

Generic AI tools output dangerous, black-box "Fraud Scores" that claims officers cannot defend. LiceronTech evaluates every claim across 4 transparent, auditable dimensions.

01

Medical Validity

Does the clinical diagnosis match the submitted diagnostic telemetry, lab reports, imaging DICOM metadata, and procedural notes?

02

Contractual Eligibility

Does the treatment fall cleanly within policy terms, waiting periods, room-rent sub-limits, pre-existing condition (PED) clauses, and co-pays?

03

Financial Accuracy

Is the billed amount accurate against negotiated hospital tariffs, packaged room charges, unbundled consumables, and pharmacy MRP databases?

04

Fraud & Network Risk

Does the claim contain suspicious relationships, recycled templates, doctor-broker nexus patterns, or provider billing anomalies?

Enterprise Pipeline

The 8-Gate Adjudication Architecture

Every claim passes through 8 deterministic and domain-grounded gates. Hard legal constraints and tariff tables are guaranteed by deterministic rule engines, preventing LLM hallucination.

1
Document Ingestion & OCR
Multimodal parsing of handwritten notes, itemized bills, lab scans, and discharge summaries across Indian languages.
2
Entity Resolution & ABDM
Matching patient ABHA ID, doctor NMC/state council registration, hospital ROHINI code, and policy history.
3
Policy & Coverage Gate
Extracting waiting periods, disease sub-limits, proportionate deductions, and pre-authorization terms.
4
Clinical Consistency
Cross-validating diagnosis against clinical protocols, ICD/CPT coding standards, and medical necessity.
5
TariffGuard™ Financials
Verifying every billed item against contracted hospital tariff rate cards and capping overcharges.
6
ProviderIQ™ Anomaly Check
Benchmarking hospital billing behavior and length of stay against regional peer distributions.
7
FraudGraph™ Network Check
Detecting circular doctor-broker referrals, template reuse, and coordinated syndicate patterns.
8
Evidence Cards & Decision
Generating itemized Evidence Cards, calculating recommended payable amounts, and routing to STP / SIU.
Explore Full Technical Architecture Documentation →
Explainable Decisioning

"Why This Amount?" — Complete Financial Auditability

Claims officers should never have to guess how an approved amount was calculated. LiceronTech presents an immutable audit breakdown where every single rupee adjustment is linked to a contract clause or forensic finding.

Original Hospital Bill (Apex Heart) ₹4,82,600
Tariff Adjustment (Unbundled Stent Consumables) −₹86,600
Policy Room Rent Proportionate Limit −₹21,000
Patient Policy Deductible & Co-Pay −₹15,000
Recommended Payable Amount ₹3,60,000
Try Interactive Adjudication Learn How Evidence Cards Work
Tariff Deviation Potential Tariff Overcharge Detected
Confidence: 96.8%
Finding: ₹86,600 Excess
Contract Ref: Section 4.2 Tariff
Billed: ₹4,82,600
Hospital charged line items "Catheterization Kit (₹48,000)" and "Guide Wire Set (₹38,600)" as separate billable consumables. Under Insurer-Provider MOU Section 4.2, package CARD-04 expressly covers all diagnostic catheter accessories.
Network Risk High Frequency Provider Cluster
17 Related Claims
Apex Heart & Dr. A. Verma have submitted 17 similar dual-stent procedures via Broker Z within 30 days, representing a 340% surge over regional baseline.
Network Moat

FraudGraph™ — Detecting Coordinated Healthcare Syndicates

Single-claim scrutiny fails when fraud rings coordinate across hospitals, diagnostic labs, doctors, and brokers. LiceronTech constructs an interconnected network graph across your entire portfolio.

Active Ring Detected

Apex Heart Cluster

Click any node to inspect relationship degree and historical claim volume.

Hospital Doctor / Lab Patient Broker
Explore Full Network Graph Architecture →
DocForensics™ Engine

Beyond OCR — Pixel-Level Document Authenticity Forensics

Fraudulent claims often use recycled discharge summaries, altered doctor signatures, and synthetic bill templates. DocForensics™ extracts hidden digital artifacts, PDF creation metadata, font kerning variations, and image copy-paste footprints.

Identifies when a discharge summary or radiology report matches a previous patient's submission by >90% structural similarity, catching cross-hospital recycled templates.
Extracts author tags, software editing history (e.g. Adobe Photoshop modifications), camera serial numbers, and creation timestamps that contradict admission dates.
Cross-evaluates the patient's initial tele-claim narrative against casualty register records and doctor surgical notes to spot conflicting trauma causes.
Forensic Anomalies Found
Discharge_Summary_MetroLife.pdf
METRO LIFE CARE HOSPITAL — DISCHARGE SUMMARY
[FLAG: FONT MISMATCH & CUT-PASTE ARTIFACT]
Patient Name: Sunita Devi | Reg: #MLC-88491
Diagnosis: Severe Osteoarthritis (Grade IV)
Procedure: Total Knee Replacement (Left)
[FLAG: REUSED DOCTOR SIGNATURE METADATA]
Signature Timestamp: 14-Aug-2026 18:30 (Matches Claim #CLM-2025-48291)
AI Forensic Assessment: 94% template similarity with past claim #CLM-2025-48291. Digital signature hash is identical to previous submission.
Provider Intelligence

ProviderIQ™ — Real-Time Hospital Risk & Outlier Scoring

Identify hospitals with abnormal length of stays, excessive procedural billing, and anomalous referral patterns against regional specialty baselines.

Hospital & Specialty Avg Claim Value Avg Stay Anomaly Rate Risk Tier Action
Apex Heart & Multispeciality
Mumbai • Cardiology
 ₹4,82,000 5.8 days 14.8% High Outlier (+41%) Enhanced Audit
Metro Life Care Hospital
Delhi NCR • Orthopedics
 ₹3,40,000 6.2 days 18.4% High Outlier (+36%) SIU Active
Apollo Health City
Hyderabad • Multi-Specialty
 ₹1,45,000 3.9 days 2.1% Benchmark Valid Green Channel
CareMax Super Speciality
Bengaluru • Neurology
 ₹3,10,000 5.1 days 3.4% Benchmark Valid Green Channel
Open Comprehensive Provider Benchmarking Hub →
Frequently Asked Questions

Enterprise Claims Intelligence FAQ

Everything health insurance executives, Chief Claims Officers, and TPAs need to know about LiceronTech deployment.

LiceronTech deploys as a frictionless API/webhook layer between your incoming claim ingestion pipeline and your claims management system (e.g. Guidewire, SAP Insurance, Instanda, MediAssist, Vidal, or bespoke PAS). Claims are sent via REST APIs or FHIR bundles, evaluated in under 2 minutes, and returned with structured Evidence Cards.
No. In strict accordance with IRDAI guidelines and enterprise risk governance, LiceronTech does not blindly automate rejections. The system categorizes claims into 🟢 Straight-Through Processing (STP Auto-Approve for 100% compliant claims), 🟡 Claims Officer Review, and 🔴 Special Investigation Unit (SIU) Referral with fully auditable evidence citations.
We utilize a deterministic dual-pipeline architecture. Hard legal rules, waiting period calculations, and hospital tariff caps are computed by a mathematical deterministic rules engine. The LLM is restricted to grounded multimodal information extraction where every extracted value is anchored with exact character bounding boxes.
Yes. LiceronTech is designed around ABDM M1, M2, and M3 standards, enabling consent-based health data retrieval via the ABDM Gateway, Ayushman Bharat Health Account (ABHA) resolution, and seamless interoperability across digital registries (HPR & HFR).
Yes. We offer fully isolated, air-gapped on-premises Kubernetes deployments as well as single-tenant private cloud VPC deployments (AWS India, Azure India, or GCP Mumbai) adhering strictly to the Digital Personal Data Protection (DPDP) Act 2023.

Ready to Protect Your Claims Portfolio from Preventable Loss?

Schedule a confidential executive briefing with the Liceron Technologies leadership team and simulate your claims portfolio risk on historical test data.

Try Interactive Sandbox