Roll-Up Radar: How AI Identifies, Underwrites, and Scales Investable Clinic Platforms

This episode digs into a practical playbook for building healthcare roll-up platforms using AI. Guests include an operator who used machine learning to source and screen dozens of clinic acquisition targets and a lender or PE partner who financed a platform built from small practices. We unpack how AI accelerates target discovery, creates repeatable underwriting templates from disparate historical data, and drives operational standardization that turns variable clinic revenue into predictable, financeable cashflow. Listeners will get concrete steps for prioritizing acquisition targets, structuring earnouts and performance covenants, sizing working capital needs, and presenting an AI-generated diligence package that speaks to lenders and strategic buyers. The conversation balances technical tools with human-led integration: change management, clinician alignment, and regulatory guardrails. Designed for founders, operators, investors, and CRE sponsors, this interview delivers an actionable framework to build a buy-and-scale healthcare platform that attracts capital and creates recurring value.