RevIntegrity: AI-Powered Healthcare Revenue Recovery & Underpayment Detection Platform

RevIntegrity is an underpayment detection platform powered by AI that helps hospital billing teams recover revenue lost to payer-side processing errors. AI Contract Intel reads payer contracts and automatically flags claims underpaid against contracted CPT rates, streamlining the appeal lifecycle from generation through resolution tracking.

Client Testimonial
doug Lee

Jorge Zapatier

RevIntegrity

revIntegrity screen

OVERVIEW

Project Overview

Hospital billing teams often spend hours cross-checking claims against payer contracts to catch underpayments, then drafting appeals manually. Although RCM platforms are used across healthcare organizations, only a few connect underpayment detection directly to appeal generation, leaving billing teams to bridge that gap manually every time.

RevIntegrity leverages AI to bring underpayment detection, claims comparison, and appeal management under one connected workflow. Each claim is checked against the rates outlined in the payer contract, and once an underpayment is confirmed, the appeal is tracked from creation through to resolution, with a complete record kept at every stage.

RevIntegrity is designed as a revenue integrity workspace, not a standalone claims tool. Underpayment detection and recovery work together in one place, giving hospitals and medical groups a defensible way to recover revenue.

Key Features

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01.

AI-Powered Contract Intel

Billing teams upload payer contracts in PDF, DOC, or DOCX format, regardless of how each one is structured. Contract Intel uses LLM-based analysis to identify CPT rates, modifier rules, and reimbursement conditions within the contract. This dense language is converted into structured, comparable data, giving billing teams an accurate reimbursement reference for every payer relationship without manual contract review.

02.

Claims & Variance Amount Detection Using AI

Claims and remittance files, including UBRA, EOB, and ERA formats, are compared directly against the rates Contract Intel has already captured. Underpaid claims are identified as part of this comparison, with the variance amount calculated and displayed for each one. Billing teams see exactly where revenue is being lost, without cross-checking claims manually.

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03.

One-Click Appeal Generation

Billing staff trigger Generate Appeal directly from an underpaid claim, and the system moves straight into the appeal builder with that claim already selected. The letter arrives pre-filled with contract references and financial data, while auto fetch files brings in supporting evidence automatically. Staff review and finalize a ready-made appeal instead of building one from scratch.

04.

Appeal Lifecycle Tracking

Every submitted appeal moves through the appeal tracker, progressing from draft to submitted, pending, paid, or denied. Timestamped appeal notes log each update along the way, building a complete history of the appeal's progress. Billing teams can check recovery status at a glance, without switching between systems.

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revIntegrity

05.

Role-Separated Dashboards

Billing team users and administrators are routed to dashboards built around their role. Billing staff track 4 operational KPIs tied to daily claim recovery, while administrators view performance across 8 platform-wide KPIs and charts. Each team works from the data relevant to its own responsibilities.

Features at a Glance

  • revIntegritySecure role-based authentication with OTP password reset

    revIntegrityBoard-ready, filterable claim & payment reports

    revIntegrityAppend-only audit trail with 6-year retention

    revIntegrityHIPAA-compliant data encryption at rest and in transit

    revIntegritySecure file handling with virus scanning on upload

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The Challenges and Their Solutions

1. Parsing Inconsistent Contract Formats

Challenge

Payer contracts arrived as PDF, DOC, and DOCX files, each with different layouts and clause structures. Extracting CPT rates and reimbursement conditions accurately meant the parsing logic couldn't rely on one fixed template.

Solution

An LLM-based extraction pipeline was built into Contract Intel. It identifies rate tables and reimbursement clauses regardless of document structure, producing consistent, structured data without manual template mapping for each payer.  

2. Calculating Variance at Scale

Challenge

Claims needed to be compared against contracted rates without delay. The variance calculation had to stay accurate across large claim volumes, while handling different CPT codes and modifier combinations at once.

Solution

A variance engine was developed to run comparison logic the moment claims and contracted rates are both available and matches each claim line to the correct CPT code and modifier combination before calculating the payment gap.

3. Auto-Populating Accurate Appeal Letters

Challenge

Pre-filling appeal letters required pulling the correct contract citation and financial data for each specific claim. The letter still needed to stay editable, without risking mismatched or outdated references.

Solution

We designed an appeal builder to pre-fill each letter using the exact contract clause and data tied to the flagged claim. Auto fetch files retrieves supporting evidence automatically, reducing manual drafting to a review step.

4. Building a Tamper-Proof Audit Log

Challenge

Financial operations needed a logging system that recorded every action without allowing later edits. It also had to meet HIPAA's 6-year retention rule without slowing down daily platform use. 

Solution

An append-only audit architecture was implemented which logs the user, action, timestamp, and record ID for every financial operation, with 6-year retention enforced automatically, keeping the trail complete and unaltered.

Technology Stack

React

Powered the web application, giving billing teams and administrators a responsive interface for uploading contracts, reviewing claims, and managing appeals.

Node.js / Python

Handled the backend API layer, powering business logic, contract processing workflows, and integrations across the platform.

LLM-Based Contract Intel

OpenAI GPT-class model enabled automated CPT rate extraction and reimbursement rule summarization directly from uploaded payer contracts, replacing manual contract review.

PostgreSQL

Managed structured claims, contract, and appeal data, supporting fast queries across large claims volumes.

Encrypted Object Storage

Implemented for efficient tracking, campaign execution, and marketing optimization without affecting page speed or AMP compliance.

AWS (HIPAA-Eligible Services)

Provided the scalable, compliant cloud infrastructure underpinning the platform, with CI/CD pipelines supporting reliable delivery.

TLS 1.2+, bcrypt/Argon2, RBAC

Secured data in transit, protected credentials with strong password hashing, and enforced role-based access control at both the UI and API levels.

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Sanjeev Verma

Leader of the Effort

Sanjeev Verma has been actively conceptualizing and creating software solutions for the past 20 years in the IT domain. He has worked on technical leadership positions with Marriott Vacations, Disney, MasterCard, Statefarm, and Oracle. He has been a key player in developing, implementing, and monitoring Digital Solutions ranging from IoT solutions & products, Mobile and Web Development, and Digital Marketing to Full Stack Development and CMS solutions.

Ready to Recover Revenue Your Billing Team Is Currently Missing?

We turned manual underpayment detection into a governed, AI-driven recovery workflow for hospital billing teams.

We can do the same for your organization.
Call Us Now

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