WATCH THE ON DEMAND SESSIONAI Built for HEOR Research

Many AI tools are built for chat, dashboards, and demos, not research. In HEOR, that gap shows up fast: fragmented data, opaque models, and manual workflows that break the moment a payer or peer reviewer asks how an answer was produced. This session breaks down healthcare-native AI built for defensible evidence, from a curated data foundation to an AI engine that shows its code and names its limits.

In this on demand webinar, you’ll:

• See why general-purpose AI falls short of HEOR standards for data quality, transparency, and scientific rigor
• Learn the three parts of healthcare-native AI: the data foundation, the research architecture, and an AI engine built for audit
• Understand what each safeguard protects, from visible code to cost imputation to representativeness
• Find the HEOR use cases where feasibility and cohort building take minutes, not weeks, and the science still holds up