Faster Revenue Recovery. Greater Precision.
AI that prioritizes, detects, and accelerates recovery.
AI Built for Results
Every AI capability in ReClaim™ is built with one mission: get the right revenue, faster — with expert review behind every output.
By the Numbers
750M+
Claims (and counting) driving every data insight
7%
Year-over-year uplift driven by ML-driven, closed-loop feedback
2X+
Acceleration in processing clinical appeals leveraging GenAI
AI at Work Across the Recovery Lifecycle.
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ML Claim Prioritization
Machine-learning (ML) models identify opportunities by probability of recovery, financial impact, and payer behavior — so specialist effort focuses on the highest-value recovery opportunities, not a linear queue.
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Workload Optimization
GenAI-driven workflows route accounts to the appropriate specialist based on claim type, complexity, and recovery profile through context-aware assistance and load balancing.
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AI-Assisted Appeals
Surfaces the most impactful clinical evidence then generates payer-specific appeal letters — reviewed, refined, and finalized by a Clinical Nurse Manager before submission.
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Emerging Pattern Detection
ReClaim continuously analyzes recovery outcomes across the client network to detect emerging payer behaviors before they scale — updating detection rules and alerting clients earlier than static rule sets or manual auditing can.
How Revecore Governs AI Use
Every AI capability in ReClaim is designed to complement our market-leading internal claims expertise — automating everyday processes while harnessing the power of our data.
Human-in-the-Loop Validation
At Revecore, AI and human expertise work in tandem. AI accelerates recovery efforts while qualified experts ensure every client deliverable meets the standard of a seasoned specialist. No AI-generated output reaches a payer or produces a client deliverable without qualified human review.
Transparency
Clients are informed of where and how AI is used in their service delivery with AI-assisted outputs clearly distinguished from human-generated conclusions.
Accuracy and Defensibility
Recovery actions pursued through ReClaim are held to the same standard of clinical accuracy and payer compliance as fully manual processes. AI assists in preparation while human expertise ensures defensibility.
Continuous Improvement
Recovery outcomes feed back into AI models and identification rules continuously — improving detection accuracy, refining prioritization logic, and allowing the system to adapt as payer behavior and regulatory requirements evolve.
Frequently Asked Questions
Will Revecore use our patient data to train Al models?
Revecore tokenizes PHI so it is not part of model training. No PHI is used in any system that could generate new model parameters.
How do we know Al-generated appeals or recommendations are accurate?
Recovery actions are held to the same standard of clinical accuracy and payer compliance as fully manual processes. Al assists in preparation; experts ensure defensibility.
Who is accountable when Al gets something wrong?
No Al-generated output reaches a payer or produces a client deliverable without qualified human review.
Will we know when Al was used on our claims?
Clients are informed where and how Al is used, with Al-assisted outputs clearly distinguished from human-generated conclusions.
Are payers using Al against us? How does Revecore's Al compare?
Payers are using Al to issue denials and underpayments faster, at greater scale. Revecore uses Al to sharpen prioritization, detect payer trends, and accelerate appeals.
What Al is in production today versus on a roadmap?
Every Al capability described on these pages is in production today. To discuss what's next on our roadmap, connect with our team.
See How AI-Powered Recovery Performs at Scale
Connect with a Revecore specialist to learn how AI-driven capabilities within ReClaim are improving recovery outcomes for health systems nationwide.