RevAIant: AI-Driven Medical Claim Scrubbing
​
RevAIant is an intelligent medical claim scrubber that analyzes and validates claims before submission — catching coding, eligibility, and payer-specific errors automatically.
Built for billing companies, laboratories, EMRs, and stand-alone practices that demand precision, compliance, and control.
AI That Learns From Your Practice
RevAIant uses adaptive intelligence to identify and prevent denials at the source. It continuously learns from your historical claim data, spotting new denial patterns and improving accuracy over time.
Coding - to - Diagnosis Inconsistencies
Automatically aligns CPT and ICD codes with medical necessity rules. When diagnosis codes don’t support the selected procedure codes, RevAIant Identifies errors instantly, preventing denials tied to clinical justification.
Modifier Misuse & Bundling Conflicts
RevAIant analyzes claim line structures to detect incorrect or missing modifiers and bundling errors that trigger payer edits. The result: accurate reimbursement and fewer costly reworks caused by inconsistent modifier logic.
Eligibility Mismatches & Inactive Coverage
RevAIant’s AI engine identifies eligibility errors before claims ever reach the payer. By cross-referencing real-time coverage data, it detects inactive plans, policy terminations, and patient mismatches—ensuring every claim is submitted cleanly the first time.
The Problem: Denials and Delays Are Draining Revenue
Traditional rule engines use static edits that can’t keep pace with payer updates or learn from your unique workflows. RevAIant changes that.
High Denial Rates at First Submission
Over 20% of healthcare claims are denied on their first pass, often due to preventable data or process errors. Each denial triggers costly rework, delays cash flow, and inflates administrative burden. The result is a system where revenue leakage is accepted as normal — but it doesn’t have to be.
Manual Rework Drains Productivity
When denials occur, staff are pulled from strategic work to chase corrections and resubmissions. Hours are lost to phone calls, portals, and paperwork that could have been avoided. Instead of managing the revenue cycle proactively, teams become reactive — trapped in an endless loop of rework and appeals.
Eligibility and Coding Errors Dominate
Most denials trace back to mismatched eligibility information or inaccurate coding. Small mistakes — an inactive policy, a missing modifier, or an ICD-CPT mismatch — can invalidate entire batches of claims. These errors slip through traditional rule engines, which struggle to keep up with payer updates and nuanced submission rules.
Intelligence Behind Every Clean Claim
RevAIant operates quietly in the background, integrating seamlessly with your existing EMR, practice management system, or clearinghouse — no disruptions, no heavy IT lift. Once connected, its AI engine goes to work, mirroring payer logic to analyze each claim in real time. It validates eligibility, identifies coding inconsistencies, and detects potential denial triggers before submission, ensuring only compliant and accurate claims move forward.
​
But RevAIant doesn’t stop there. Every processed claim feeds a continuous learning loop — refining its models to recognize emerging denial patterns and payer-specific nuances unique to your organization. The result is a system that gets smarter over time, producing fewer rejections, faster reimbursements, and data-driven insights that transform claim management from reactive cleanup to proactive precision.
Are You Ready to Accelerate Your Business?
Proven Success with PGM Billing
When PGM Billing, a national RCM leader, integrated RevAIant into its workflow, the impact was dramatic:
-
Over 50% reduction in first-pass denials
-
Average AR days reduced by 4.2 days
-
Manual review workload cut by 35%
-
$2.3M+ in additional annual revenue recovered
Irene S, Billing Manager
“Before RevAIant, our billing team spent hours every week fixing eligibility and coding rejections. Within two months, our denial rate dropped by more than half, and cash flow stabilized. The system learns from our own patterns — it feels like having a billing expert that never sleeps.”
Carola C, Revenue Cycle Specialist
"We handle multi-state anesthesia billing, and no two payers follow the same rulebook. RevAIant automatically flags modifier and bundling errors that used to take days to uncover. We’ve reduced rework and improved first-pass acceptance dramatically."
Louri R, Laboratory Manager
“For our lab network, RevAIant cut denials related to medical necessity and coverage by nearly 60%. The team trusts the platform because it keeps learning from our claims data — every week it gets smarter.”