Post-acute care software for regulatory compliance and billing optimization
Simple is a Netsmart solution serving 8,500+ healthcare providers with analytics and workflow automation for long-term care operations. The stack reveals an ML-forward engineering organization — TensorFlow, PyTorch, scikit-learn, MLflow, and Weights & Biases sit alongside core healthcare data tools (FHIR, HL7, Netsmart EHR) — paired with active modernization projects (microservices, cloud migration, CI/CD) and accelerating hiring weighted toward senior engineers. This suggests a shift from maintenance-mode compliance software toward AI-driven decision support and operational intelligence.
Simple builds post-acute care software designed for long-term care facilities, skilled nursing homes, and health systems managing regulatory complexity and reimbursement. The product suite spans MDS transmission, CMS reporting, billing optimization, and state-specific automation (Texas Medicaid, PASRR, MCO workflows). Founded in 2003 and acquired by Netsmart, Simple operates at scale — serving over 8,500 providers — while simultaneously modernizing its platform architecture with microservices, cloud infrastructure, and machine learning capabilities. Active projects signal movement toward clinical decision support and automated test frameworks, indicating a product roadmap expanding beyond compliance into operational optimization.
Java, C#, .NET, Python, Angular, TypeScript on AWS, Azure, and GCP. ML: TensorFlow, PyTorch, scikit-learn, MLflow. Healthcare data: FHIR, HL7, Netsmart EHR. Infrastructure: Docker, Kubernetes, Kafka, Prometheus, Grafana, Apache Airflow.
Overland Park, Kansas. Simple operates as a privately held Netsmart solution and is hiring in the United States and India.
Simple, a Netsmart solution'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.