From Months to Minutes: AI EHR Connectivity Live Case Study

Healthcare AI has matured rapidly, yet most solutions struggle to deliver value once they meet the reality of EHR integration. Long timelines, fragmented systems, inconsistent FHIR implementations, and compliance concerns often prevent AI from moving beyond controlled pilots. This Expert Insight session centers on a live showcase demonstrating how AI-first interoperability can overcome these barriers in real production environments.

In this session, Mindbowser and Maia present a live case study of how Maia, an AI-powered revenue cycle management platform for orthopaedic practices, successfully embedded AI workflows directly inside EHR systems using ConnectHealth. Ayush Jain, CEO & Co-Founder of Mindbowser, opens by outlining the industry-wide integration challenges that slow AI adoption and set the context for why interoperability has become the critical enabler of scalable healthcare AI.

Zach Ruhl, Founder & CEO of Maia, then shares the operational challenges Maia faced while deploying AI across multiple orthopaedic practices. Although Maia’s AI improved documentation quality and billing accuracy, onboarding new practices and integrating AI into day-to-day revenue workflows remained a bottleneck due to manual processes and EHR complexity.

The session’s core focus is a live demonstration of ConnectHealth, showcasing how AI-first interoperability reduces integration timelines from months to days. Attendees will see how ConnectHealth enables secure SMART on FHIR-based access, workflow orchestration inside the EHR, and built-in compliance guardrails, allowing Maia’s AI to function seamlessly within existing revenue cycle workflows.

Zach concludes by sharing real-world outcomes from Maia’s deployment, including faster onboarding, reduced administrative burden, cleaner workflows, and AI that is actively used by healthcare teams. The session closes with key takeaways on how live, production-ready interoperability platforms can turn AI innovation into measurable operational impact.

Attendees will leave with a clear, practical understanding of how AI-first interoperability, demonstrated live, can make healthcare AI work inside the systems providers already depend on.