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XiFin invests in Notable Systems to accelerate agentic AI innovation across revenue cycle management

Multi-year strategic AI alliance builds on XiFin’s established AI-driven Empower RCM ecosystem by integrating Notable’s enterprise-grade agentic document intelligence.

SAN DIEGO — XiFin, Inc., a leader in AI-driven revenue cycle management (RCM), and Notable Systems, a developer of agentic AI automation for healthcare revenue cycle operations, today announced a multi-year strategic AI alliance to develop and deliver purpose-built agentic AI capabilities across the XiFin Empower AI RCM ecosystem. By combining Notable’s document intelligence with XiFin’s revenue cycle data, domain expertise, and established workflow orchestration, we are creating purpose-built AI capabilities that understand information, determine the appropriate action, and move complex work forward within our clients’ existing operations. XiFin has also made a strategic investment in Notable Systems as part of Notable’s Series B financing, to accelerate this shared innovation roadmap.

“XiFin has long applied AI, automation, and active intelligence across the revenue cycle. This alliance builds on that foundation by expanding the specialized capabilities available through XiFin Empower and accelerating our broader innovation roadmap. Our investment and multi-year commitment reflect both the importance of this work and XiFin’s continued leadership in shaping the next generation of intelligent revenue cycle management," said Lâle White, executive chair and CEO, XiFin, Inc.

The alliance applies enterprise-grade AI to the document-intensive workflows that govern how diagnostic, pharmacy, and medical device orders are processed and how healthcare claims are qualified, documented, and paid. XiFin will integrate Notable’s document intelligence into its broader AI architecture to address the unique workflow needs of XiFin’s clients.

The interoperable XiFin Empower AI ecosystem brings intelligence across the revenue cycle, from patient registration and eligibility verification to clinical documentation, billing, payment and appeals. Notable’s agents will extend that intelligence into the requisitions, prescriptions, medical records, payer correspondence, and other unstructured information that traditionally require labor-intensive handling. Together, the companies are helping reduce manual touches and improve financial outcomes in high-complexity, high-value billing environments.

In tandem with this agreement, Notable Systems is executing a strategic realignment to invest more deeply in the engineering, innovation, and embedded delivery capabilities that differentiate its AI systems for major healthcare providers. Notable’s clients today include Orthofix, National Seating & Mobility, and Advanced Diabetes Supply, a subsidiary of Cardinal Health. By concentrating its resources on the largest revenue cycle management platforms and providers, Notable is positioning to bring next-generation AI automation to a broader enterprise healthcare market.

“Our greatest successes have always come from deep, collaborative relationships with major healthcare partners. XiFin's participation in our Series B is a meaningful vote of confidence in our team and our technology, and this strategic realignment lets us invest further in the embedded partnerships that have long differentiated Notable. Our strategic alliance with XiFin provides the foundation to accelerate innovation for years to come,” added Steve Johnson, CEO and co-founder, Notable Systems.

XiFin Empower AI brings together AI-driven intelligence and automation across critical revenue cycle workflows and XiFin Empower DocExtract represents an early example of this strategy in production. DocExtract demonstrates how specialized AI can be integrated into established revenue cycle workflows to reduce manual effort and improve operational efficiency. Powered by Notable’s document intelligence, DocExtract uses AI-driven automation to extract, classify, split, label, and route inbound medical records, orders, and correspondence into the appropriate revenue cycle workflows.

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