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Avelis Health

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Avelis Health offers an AI-driven solution designed to enhance payment integrity for Third-Party Administrators (TPAs) and health plans, aiming to reduce annual plan expenditures by 2-7%. By auditing every medical claim through advanced machine learning models and clinician reviews, Avelis identifies and recovers hidden billing, coding, and contract errors, ensuring comprehensive oversight and substantial cost savings. Key Features and Functionality: - Comprehensive Claim Auditing: Utilizes AI to audit 100% of medical claims, not just high-dollar ones, ensuring no errors are overlooked. - Advanced Error Detection: Machine learning models detect nuanced billing discrepancies, while clinician-in-the-loop reviews minimize false positives. - AI-Powered Medical Record Parsing: Instantly parses unstructured clinical notes to verify medical necessity against billing codes, facilitating faster claim resolutions. - Automated Post-Payment Recovery: Proprietary voice AI agents autonomously handle the entire recovery process, from initiating provider calls to resolving disputes, with human-like empathy and machine-level persistence. - Seamless Integration: Connects securely with existing workflows without implementation fees, accepting raw claims data in various formats and normalizing it without additional IT work. - Real-Time Savings Dashboard: Provides detailed, claim-by-claim reporting to track recovered funds and monitor savings trends over time. Primary Value and User Solutions: Avelis Health addresses the critical issue of erroneous medical claims that lead to unnecessary expenditures for TPAs and health plans. By leveraging AI and clinician expertise, Avelis ensures thorough claim audits, identifies hidden errors, and automates the recovery process, resulting in significant cost savings and improved plan management. This comprehensive approach not only enhances financial efficiency but also supports compliance with fiduciary responsibilities, ultimately benefiting both plan administrators and members.

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