Revenue
Shield

An AI-powered coding and charge capture platform that transforms clinical documentation into optimized, payer-ready claims

Product Overview

RevenueShield is an AI-powered coding and charge capture platform that transforms clinical documentation into optimized, payer-ready claims. RevenueShield autonomously reads progress notes and generates accurate ICD-10, CPT codes and modifiers in order to reduce cost, identify missed revenue opportunities, prevent denials before submission and improve compliance.

Automated Coding

Autonomously reads progress notes and generates complete coding (i.e., ICD, CPT, modifiers)

Revenue Maximization

Identifies under-coding and missed charge opportunities pre-bill

Denial Prevention

Learns from historical denial patterns to avoid codes that will be rejected

How RevenueShield Works

AI Module 01

ChartAI

Real-time documentation assistant embedded in the EHR that prompts for completeness and medical necessity as providers document.

EMBEDDED_ASSISTANT_ACTIVE...
AI Module 02

AutoCoder AI

Ingests structured notes to generate accurate CPT/ICD codes using specialty-specific logic, complete with confidence scores and rationale.

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Key Product Features

Coding Node

AI-Powered Documentation & Coding

Complements DenialShield by fixing upstream clinical data—reducing rework and denial risk.

AI Transparency

Explainable AI

Transparent confidence scores and rationale to build trust with coders and compliance teams.

Workflow Node

Scalable Workflow

Reduces coder workload while increasing throughput; full audit trails and payer logic facilitate compliance. Clinicians/coders can review, override, or accept suggestions.

Value Creation Opportunity

Clinical Documentation Gap
Up to 70%
Notes lack sufficient specificity for CPT/ICD codes
Manual Coding Friction
15-20%
Average Error Rate in Manual Workflows
AI Precision Benchmark
98%
Code Accuracy using Predictive NLP
Inefficiency Breakdown
Provider Correction Time 16-20m
Coder Chart Review Time 20-30%
Workflow Scalability Low
Systemic Bottleneck: Human-only workflows scale poorly.
NLP models prove 98% accuracy in real-world trials.
Analysis: Clinical Documentation & Coding Compliance Metrics
v5.2025 // Predictive NLP Core
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