Prior authorization automation platform connecting providers and payers
Humata automates prior authorization workflows by integrating with EHR systems (Epic, Cerner, Athenahealth) and payer networks. The stack—Python, Go, TensorFlow/PyTorch, Kubernetes on AWS/GCP/Azure—reflects a machine-learning-first approach to workflow automation in a regulated environment. Active hiring skews toward mid-level engineering roles, while project work centers on AI-driven approval workflows and model versioning, indicating the company is scaling both infrastructure and the AI engine itself rather than just the sales motion.
Humata Health operates a healthcare automation platform focused on streamlining prior authorization—the clinical clearance process that determines whether payers will cover requested treatments. The platform connects providers (hospitals, health systems, practices) to payers using deep EHR integration, real-time payer connectivity, and PolicyMatch, an AI engine that automates approval decisions. The company is based in Winter Park, Florida and operates in the 51–200 employee range. Current work centers on backend service reliability, analytics infrastructure, and improving the quality of AI-driven approval workflows in a highly regulated healthcare environment.
Humata integrates with major EHR platforms including Epic, Cerner, and Athenahealth. The backend runs on Python and Go with Kubernetes orchestration across AWS, GCP, and Azure. Machine learning models use TensorFlow and PyTorch for AI-driven workflows.
Current projects include AI-driven prior authorization workflows, backend service APIs, model versioning and feature store infrastructure, customer success planning, and analytics reporting to support revenue cycle optimization and denials management.
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