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Revenue cycle management (RCM) firm Procode AI has raised $10 million in series A funding, led by Health Velocity Capital, to accelerate its AI-powered surgical billing solutions for private practice surgeons.
Procode AI, an artificial intelligence-driven revenue cycle management (RCM) company, has secured a $10 million Series A funding round. Led by Health Velocity Capital, this investment will support the expansion of Procode AI’s platform into private practice surgery and ambulatory surgical centers (ASCs). The company's AI coding copilot translates operative reports into billing and diagnostic codes, reducing manual coding time and minimizing downstream denials.
Co-founder Jeff Cripe told Fierce Healthcare that Procode AI's strategy involves acquiring and vertically integrating AI technologies within companies rather than selling standalone products. This approach has already proven successful with the acquisition of The Auctus Group, a provider of RCM services for plastic surgery and dermatology practices. Since the acquisition, Procode AI has more than 350 providers under its umbrella and has raised $14 million in venture funding to date.
Cripe stated, "We’re on track to double The Auctus Group’s revenue and quintuple its EBITDA margin." This growth is significant because Procode AI operates on a contingency basis-payment is contingent upon successful billing for their clients. Cripe added, "Our growth is proof that our AI is putting more dollars in providers' pockets, not just automating paperwork."
The newly announced funding will back two additional acquisitions aimed at accelerating Procode AI’s expansion into all surgical specialties and ASC billing. These strategic moves are designed to address the complex and fragmented nature of RCM for private practice surgeons, who often lack the technological resources available to larger health systems.
Large health systems have benefited from advanced technology companies addressing their most pressing issues for years. Procode AI aims to bring similar innovations to the vast, underserved market of RCM companies serving private practice surgeons. Cripe emphasized, "We’re proud to innovate on behalf of this massive, long-tail market."

The company's AI coding copilot is a key component of its strategy. By translating operative reports into accurate billing and diagnostic codes, it significantly reduces the time and errors associated with manual coding. This not only streamlines the billing process but also enhances revenue capture for providers.
For investors, Procode AI’s growth trajectory presents an attractive opportunity in a rapidly evolving market. The company's focus on contingency-based billing aligns with the growing trend of performance-driven solutions in healthcare technology. As more private practice surgeons seek to optimize their revenue cycles, Procode AI is well-positioned to capture a significant share of this market.
The additional acquisitions planned with the Series A funding will further solidify Procode AI’s position as a leader in AI-powered RCM for surgical billing. These strategic moves are expected to drive continued revenue growth and margin expansion, making Procode AI an increasingly compelling investment prospect.
Procode AI's $10 million Series A funding round marks a significant milestone in the company's mission to revolutionize RCM for private practice surgeons. With a proven track record of success and ambitious expansion plans, investors should keep a close eye on this emerging player in the healthcare technology landscape.
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Procode AI secures $10M series A for AI-powered RCM for surgical billing
↗ https://www.fiercehealthcare.com/finance/procode-ai-secures-10m-series-ai-powered-rcm-surgical-billing
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Marcus began tracking AI's market implications in 2016, noticing AI-related patent filings accelerating ahead of earnings upgrades before most of the sell-side had caught on. A former fixed-income quantitative analyst, he spent two decades building models that priced risk across emerging markets before pivoting to cover the economic impact of AI full-time. His writing translates opaque technical developments into clear risk/reward terms — and he's rarely diplomatic about the gap between AI valuations and underlying fundamentals. He believes most market participants still underestimate AI's long-run deflationary effect on knowledge work.
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