The best way to launch AI agents
in healthcare

Purpose-built healthcare SLMs

Small language models tuned on clinical workflows, delivering higher accuracy, lower cost, and lower latency on benefits interpretation, care-gap reasoning, and clinical logic than general-purpose models.

Certified golden datasets

An expert-authored answer key that codifies clinical judgment and sets the bar an agent must clear before it ships, doubling as the human-review record regulators increasingly expect.

Evals

Customers can author their own test cases, which agents use to continuously optimize performance against real-world scenarios and prove that they repeatedly took the right action.

Synthetic Populations

Proprietary synthetic data sets, privacy-preserving by design, that let teams test agents against thousands of realistic scenarios, including vulnerable populations and edge cases.

Healthcare-grade governance, safe by default

PHI-aware access, clinical guardrails, and grounded reasoning that constrains agents to approved sources, so an agent cannot invent a coverage or clinical answer it was never given. Built to HITRUST r2, SOC 2 Type II, HIPAA, PIPEDA, and GDPR standards.

Performance monitoring

See completions, escalations, and accuracy tracked by use case, with agents benchmarked — where data-sharing terms permit — against anonymized, opt-in results from peer organizations across the League network.