Procode AI Launches with $4M for Medical Billing

Procode AI has launched from stealth with $4 million in funding to tackle revenue cycle management (RCM) for surgeons. As part of its launch, the company also acquired The Auctus Group, a top US biller for plastic surgeons and dermatologists.

Procode AI's founding team consists of Jeff Cripe, Dr. Kameron Rezzadeh, and James Baez-Silva. The recent $4 million in funding was led by Story Ventures, with participation from CHAP Health Ventures, Progression Fund, and Dmitry Shevelenko, the Chief Business Officer of Perplexity. The company's mission is to provide smaller surgical practices with the same level of AI-powered coding technology that has typically been accessible only to large healthcare systems. Procode AI, short for "Procedural Coding," specifically targets the complexities of billing for surgical procedures. The acquisition of The Auctus Group is a strategic move to combine Procode AI's technology with established industry expertise. Founded in 2012, The Auctus Group has built a strong reputation for providing billing, operational, and financial management services to plastic surgery and dermatology practices. This focus on aesthetic medicine is significant as these fields often involve complex billing codes and a high volume of out-of-pocket patient payments, areas where AI can significantly improve efficiency and accuracy. The Auctus Group was founded by John Gwin and has been recognized as a "Great Place to Work," with a team of around 11-50 employees before the acquisition. The broader market for AI in medical billing is projected to grow significantly, driven by the need to reduce errors, streamline workflows, and manage increasingly complex compliance requirements. Private practices, in particular, face challenges with claim denials, delayed payments, and the administrative burden of prior authorizations, issues that AI-driven platforms are designed to address. Procode AI's platform is designed to integrate directly with electronic health records (EHR) to automate the process of pulling and coding records, checking for errors, and submitting charges for human review. This automation is intended to increase the capacity and accuracy of medical billing teams.

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