From pilot to scale: Making agentic AI work in health care

LLMs excel at understanding nuanced context, performing instinctive reasoning, and generating human-like interactions, making them ideal for agentic tools to then interpret intricate data and communicate effectively. Yet in a domain like health care where compliance, accuracy, and adherence to regulatory standards are non-negotiable--and where a wealth of structured resources like taxonomies, rules, and clinical guidelines define the landscape--symbolic AI is indispensable. By fusing LLMs and reinforcement learning with structured knowledge bases and clinical logic, our hybrid architecture delivers more than just intelligent automation--it minimizes hallucinations, expands reasoning capabilities, and ensures every decision is grounded in established guidelines and enforceable guardrails. Ensemble's agentic AI approach includes three core pillars: The team has decades of data aggregation, cleansing, and harmonization efforts, providing an exceptional environment to develop advanced applications. To power our agentic systems, we've harmonized more than 2 petabytes of longitudinal claims data, 80,000 denial audit letters, and 80 million annual transactions mapped to industry-leading outcomes.