Generative AI Procurement Tools

Solicitation # RFI3170103588
Posted 2/5/25, 1:00 AM
No Updates
Due 3/28/25, 3:00 PM
Source
No public source available
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The State of Tennessee, specifically the Finance & Administration - Strategic Technology Solutions department, is seeking Generative AI (GenAI) procurement tools through a Request for Information (RFI #31701-03588) focused on Davidson County. The procurement aims to identify innovative software solutions that can assist state procurement professionals in streamlining contract scope definition, automating RFP generation, and efficiently analyzing vendor responses. Key deliverables include comprehensive AI tools capable of enhancing procurement efficiency, reducing manual effort, and minimizing potential risks. The RFI requires detailed vendor information about AI/ML experience, technical capabilities, security measures, implementation approaches, and pricing models. Critical dates include vendor questions due by 2/20/2025, state responses by 3/12/2025, RFI responses due by 3/28/2025, review completion by 4/11/2025, and virtual demonstrations scheduled for 4/28/2025-4/30/2025.

The procurement opportunity has specific restrictions, including a requirement that all state data must remain within the United States, with access limited exclusively to US-based resources. Software applications from foreign adversaries, particularly China, are explicitly prohibited. The state may proceed with a no-cost Proof of Concept (POC) phase to demonstrate capabilities in a real-world environment. Vendors must provide comprehensive pricing information, including subscription models, usage-based pricing, perpetual licenses, implementation costs, training fees, and any limitations on usage, data storage, or user numbers. While no specific budget range is mentioned, the RFI suggests the state is seeking flexible, scalable solutions that can be evaluated through a thorough technical and financial assessment. The procurement appears open to multiple vendors, with potential for phased implementation and further evaluation based on initial RFI responses and subsequent demonstrations.

Generated 3/2/25, 9:29 AM