League Labs

League Labs is League's applied AI research home for healthcare-native models, evaluation, and trustworthy deployment patterns.

We publish open methodology, benchmarks, and evidence for domain-specific AI systems while protecting sensitive data, model assets, and customer privacy. Our work focuses on de-identified data practices, task-specific evaluation, safer healthcare language behavior, lower-latency model serving, and deployment options for regulated environments.

We believe healthcare AI should be measured against the real work it supports: clear reasoning, safe boundaries, privacy-preserving learning, and reliable performance in real world scenarios that target what a person's health journey is actually like.

Follow along for research notes, evaluation artifacts, and public resources from League's AI teams.