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For payers and TPAs

Medical record review AI for payers and TPAs.

YIRA MedSense reads the medical records behind every claim and pre-authorisation, from histories and discharge summaries to lab reports and itemised bills, and gives clinical reviewers a structured file with diagnoses, ICD-10 codes, medications, flagged lab values and prior-record matches. Built for health plans, insurers and TPAs worldwide, including the US.

1 lakh+documents parsed
5,000+fraud cases flagged for review
100+insurance operations

Medically reviewed by Dr. N. S. Santosh Varma, MBBS, FIIM, FIDM, FICCM · Medical Officer, YIRA MedSense · Updated 13 October 2026

MedSense · Record review summaryReady
{
  "documents": 14,
  "diagnoses": ["…"], "icd10": ["…"],
  "medications": ["…"],
  "lab_flags": [ { "test": "ALT", "flag": "High" } ],
  "bill_lines": "extracted",
  "prior_record_match": "flagged",
  "next": "clinical reviewer"
}
Illustrative structure.
See it work
Lab report to structured, flagged data · TEST DATA Demo documents only, not real patients.
Prior-record matching for fraud review · TEST DATA Demo documents only, not real patients.
Trusted in production byHealth Assist Insurance TPA Pvt Ltd
ISO 9001:2015SOC 2HIPAAGDPRFTCCI member
The problem

Clinical reviewers spend their day reading, not reviewing.

Medical record review sits behind pre-authorisation, claim review, payment integrity and audits. Most of the time goes into finding facts in long, inconsistent records.

Long records

Dozens of pages per claim, many scanned or handwritten.

Inconsistent formats

Every provider and lab formats records differently.

Hidden signals

Reused documents, abnormal values and billing gaps are buried in the pages.

Expensive reviewers

Nurses and medical officers spend hours on data entry instead of judgement.

How it works

From record pile to review-ready file.

Step 1

Ingest

Records arrive by API, mobile app or bulk scanner portal: PDFs, scans, handwritten notes and photos.

Step 2

Extract

Clinical NLP identifies diagnoses, ICD-10 codes, medications, procedures, lab values and bill lines.

Step 3

Check

Lab values are flagged against reference ranges, documents are matched against prior records, and the member's photo can be compared with the hospital photo.

Step 4

Deliver

A structured JSON file goes to your review, claims or payment-integrity system by API.

Use cases

One engine, four review workflows.

WorkflowWhat MedSense does
Prior authorisation / pre-authSummarises the clinical history and supporting reports for the requested treatment
Claim reviewStructures the record and bill so reviewers check facts instead of finding them
Payment integrityFlags reused documents, identity mismatches and bill lines that do not match agreed rates
Audit and SIURe-reads past claims at scale and surfaces records that match earlier files
Why MedSense

Built for claims, not generic OCR.

Clinical understanding

ICD-10 codes, medications and lab flags, not just text.

Fraud signals included

Prior-record matching and facial verification in the same file.

Human in the loop

MedSense prepares the review; your clinicians decide.

Deploy your way

Cloud API or client-managed deployment inside your own infrastructure.

Proof and rollout

In production, at scale.

MedSense runs in production at Health Assist Insurance TPA Pvt Ltd. It has parsed more than 1 lakh (100,000+) medical documents, flagged over 5,000 fraud cases for review and supported 100+ insurance operations.

Week 1

Sandbox

Test MedSense on your own sample documents.

Week 2

Provision

Set up document types, fields and rules.

Weeks 3–4

Integrate

Connect by API to your claims or payer system.

Week 4–5

Go live

Run in parallel, then switch over.

Timing depends on scope, data access and integration readiness. Client-managed deployment is available, so MedSense can run inside your own infrastructure.

FAQ

Questions from claims teams

What is medical record review AI?

Software that reads medical records, such as histories, discharge summaries, lab reports and bills, and turns them into structured data so clinical reviewers at health plans, insurers and TPAs can make decisions faster. YIRA MedSense also adds fraud signals such as prior-record matching and facial verification.

Is MedSense available for US health plans and TPAs?

Yes. MedSense is offered to payers and TPAs worldwide, including the US. It is built to SOC 2, HIPAA and GDPR requirements and supports client-managed deployment.

Does MedSense make coverage or medical-necessity decisions?

No. MedSense prepares and structures the record and raises review signals. Clinicians and reviewers make every decision.

Which codes does MedSense extract?

MedSense identifies diagnoses and ICD-10 codes, along with medications, procedures, lab values and billing line items.

Can MedSense read handwritten and scanned records?

Yes. Scanned PDFs, photos and handwritten medical histories are converted into structured fields.

How does it connect to our systems?

Structured JSON is delivered by API to your claims, utilisation-management or payment-integrity platform.

How long does implementation take?

About 4–5 weeks from sandbox to go-live, depending on scope, data access and integration readiness.

Get started

Book your demo today.

See MedSense on the documents and fields that matter to your claims team.