AI-powered clinical documentation and diagnosis support for healthcare providers
Regard builds AI-powered documentation tools for physicians and hospitals, surfacing diagnoses and clinical context directly within EHR workflows. The stack—Python, TypeScript, FastAPI, PostgreSQL, Kubernetes on AWS—reflects a backend-heavy, API-first architecture optimized for real-time clinical data processing. Leadership-level hiring across engineering, sales, and marketing signals aggressive scaling into the ambulatory provider segment, with active projects focused on generative AI integration and GTM expansion rather than core-product maturation.
Notable leadership hires: Executive Director
Regard is a healthcare AI company based in New York that develops clinical documentation solutions integrated with major EHR systems (Epic, Cerner). The platform uses machine learning to suggest diagnoses, extract relevant clinical context, and auto-draft clinical notes, reducing documentation burden on physicians. The company operates in a complex, regulated sales environment targeting ambulatory practices and health systems. Recent hiring focus and project roadmap emphasize generative AI capabilities and entry into the ambulatory vertical—a distinct market segment from their initial positioning.
Regard uses Python, TypeScript, FastAPI, and Flask for backend services; PostgreSQL and Redis for data; Kubernetes and AWS (EKS, SQS, SNS) for infrastructure; GitLab for version control and CI/CD; Datadog and Sentry for observability; and OpenTelemetry for tracing.
Current projects include generative AI integration for clinical documentation, launching a go-to-market strategy for ambulatory practices, account-based marketing workflows, engineering roadmap definition for AI systems, and physician-facing product features.
Regard's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.