San Francisco, October 4 — On October 1, 2026, Payerset launched an AI-powered research assistant designed to help health systems benchmark payer rates by normalizing and analyzing healthcare pricing transparency data. Here’s what it means: the tool unifies negotiated rate data, claims, policy, and market benchmarking into a single platform, drawing on 20 trillion rate records retained since 2024, with over 10 trillion additional records processed each quarter.
Think of it like having a dedicated team of researchers at your fingertips, ready to answer complex questions about market position and reimbursement trends in real time. Since 2022, federal price transparency rules have required health insurers to publish negotiated hospital rates, but the resulting machine-readable files are often large, inconsistent, and error-prone, with a single payer’s file containing billions of rows.
A recent provider survey found nearly 40% of organizations report limited or no meaningful use of Transparency in Coverage data when preparing for payer negotiations. Payerset, founded in 2022 by Jerry DiMaso and Jacob Little, both former healthcare consultants, built the infrastructure to normalize this data across formats. The research assistant allows health systems to ask plain-English questions about their market position and receive instant, data-backed answers without needing analysts, data teams, or specialized training.
Jerry DiMaso, Payerset co-founder and CEO, described the tool as ‘like having extra researchers on your team.’ Providers use the data primarily to strengthen contract negotiations by comparing reimbursement rates against competitors, while employers and benefits brokers use it to assess health plan competitiveness and independently reprice claims. The tool has evolved from a contract negotiation aid into a broader market intelligence platform that helps analyze reimbursement trends, compare contract structures, identify payer behaviors, and investigate issues like down-coding patterns and reimbursement disparities.
The research assistant builds on Payerset’s existing products: Rate Explorer for direct rate comparison and Data Lake for API access. The company also offers a free employer benchmark tool enabling searches across more than 129,000 self-funded employers to compare plan rates with other carriers and Medicare. Payerset plans to launch a consumer-facing AI tool allowing patients to upload hospital bills to verify claim processing and appropriate charges.
The research assistant is available in two forms: a Model Context Protocol (MCP) server for integration with enterprise AI tools like Claude and ChatGPT, and a companion portal product offering a chat-style experience within Payerset’s platform. Both formats enable users to ask strategic questions—such as how their rates compare to peer systems, which states offer strongest reimbursement for a service line, or where fee schedule gaps cost revenue—and receive instant, data-backed answers.
