On-Premises AI Analytics Implementation Project

Ferris State University is seeking proposals from qualified vendors to provide consulting, implementation, and training services to support the development and operationalization of an on-premises artificial intelligence (AI) research environment. The primary objective of this project is to design, implement, and operationalize a lightweight, secure, and sustainable AI workflow capable of supporting clinical and healthcare data analytics. The selected vendor will provide end-to-end consulting, implementation, and training services to support the deployment of an on-premises AI workflow. The scope includes planning and design, AI pipeline development and implementation, integration and deployment, training and knowledge transfer, and deliverables. • Identify and deploy appropriate AI models compatible with local hardware constraints • Develop a scalable and reproducible pipeline for data processing and AI-driven outputs • Integrate AI outputs into existing institutional analytics environments • Provide training and documentation to ensure long-term sustainability and internal capability The University’s goal is to establish a practical, production-ready minimum viable AI workflow (MVP) that can be expanded in future phases while maintaining data security, efficiency, and operational feasibility within an on-premises environment.