Intro

Guests

• Jennifer Deal – SVP of Product Development, Healio
• Casey Utley – Senior UX Designer, Healio
• Matthew Skepner – VP of Technology, Healio

What we cover in this episode:

• Why physicians need AI at the point of care—and how they actually use it (hint: it's preparation, not bedside)
• The surprising discovery that physicians wanted help with patient communication and empathy, not just clinical answers
• Building a working prototype in a weekend with Cursor after starting with Figma mockups
• How Healio's RAG system combines lexical search, vector search, and semantic search across multiple trusted sources
• Why "just use PubMed" isn't simple—five different ways to access the same data, each with trade-offs
• Designing citations that physicians trust: subscripts, hover states, and progressive disclosure
• Serving contextual ads while the LLM processes queries—a practical monetization approach
• HIPAA compliance and input guardrails for masking personal health information
• Eight LLM judges for evals: safety, medical accuracy, faithfulness, relevancy, completeness, reasoning, clarity, and overall quality
• Why physician feedback trumps LLM-as-judge feedback in high-stakes medical contexts
• The role of the Healio Innovation Partners in ongoing discovery and validation

Resources & Links

• Healio — Medical news, education, and clinical guidance for healthcare professionals
• PubMed — Database of biomedical literature
• Cursor — AI-powered code editor used to build the prototype

Chapters 00:00 Introduction to Healio Team 01:00 Overview of Healio's Services 01:57 Introducing Healio AI 03:39 Addressing Physician Needs with AI 05:45 Building Trust in AI Solutions 13:56 Prototyping and Testing Healio AI 18:02 Refining the AI Product 21:48 Technical Architecture and Advertising Integration 25:16 Balancing Speed and Accuracy in AI Responses 26:30 Ensuring Credible and Trustworthy Content 27:41 Challenges in Data Integration and Web Crawling 29:00 Optimizing Search Strategies for Different Data Types 31:09 User Interface and Trust Building 34:31 Human Feedback and Continuous Improvement 35:41 Guardrails and Evaluations for Reliable AI 39:11 Experimenting with LLM as Judges 45:13 Future Directions and User-Centric Design