Healthcare AI agents,
explained by people who ship them.

Healthcare AI agents are software agents — typically built on large language models grounded in clinical criteria — that handle specific clinical or administrative jobs in healthcare workflows. Examples: an eligibility agent checks beneficiary enrollment; a criteria agent evaluates medical necessity; an evidence agent assembles clinical documentation; a member navigation agent answers patient questions. The defining trait is decomposition — agents are specialists, not generalists.

A chatbot generates conversational text. An agent makes decisions, calls tools, takes actions. A healthcare AI agent can verify eligibility (call an API), evaluate criteria (run a deterministic rule pack), assemble evidence (extract structured data from clinical documents), and produce an audit packet — all in a single workflow. Most production healthcare AI today involves agents, not chatbots.

It depends entirely on the architecture. Agents that wrap a single LLM call are not safe for clinical decisions. Agents grounded in deterministic rule packs, with explicit evidence chains and human-in-the-loop on adverse decisions, are safe enough for production CMS Medicare deployment — which is exactly what Aether One™ does. The architectural pattern matters more than the model choice.

HIP One's prior authorization workflow uses 7 agents in sequence: Intake, Eligibility, Duplicate Request, Criteria, Evidence, Auto-Affirmation, and Non-Affirm Research. PES One's patient engagement workflow uses additional agents for member identity, intent classification, knowledge retrieval, and conversation orchestration. The Aether One™ substrate as a whole orchestrates more than 30 distinct agents across HIP One and PES One.

Aether One™ agents are designed for HIPAA compliance: PHI never leaves the customer environment in sovereign deployments, model inference can run on-premises or in government cloud, audit logs are HIPAA-grade, and PHI is never used for model training. Compliance also requires the surrounding governance — which is what CPS One provides for AI systems handling PHI.

Yes. Aether One™ Sovereign is the on-premises deployment of the Aether One™ substrate, including all agents. Knowledge Containment Architecture (KCA) keeps weights, knowledge, and decisions inside the customer perimeter — a requirement for federal health programs and high-security payer environments that cannot send PHI to commercial cloud.

Several vendors build healthcare AI agents at production scale: Genzeon Platforms (Aether One™ for PA, UM, patient engagement, privacy), Cohere Health (PA), Abridge (clinical documentation), Hippocratic AI (member-facing), Glass Health (clinical reasoning). The architectural patterns vary. Genzeon's distinguishing pattern is domain-decomposed agents, sovereign deployment, and patent-protected methodology — 10 patents filed across the substrate.