Annual AI Water Leak Survey - Event No. 11842

The City of Savannah will be conducting an Annual AI Water Leak Survey, soliciting electronic bids through their Purchasing Division Supplier Portal for Event No. 11842. The procurement is specifically focused on water infrastructure leak detection and analysis, likely utilizing advanced artificial intelligence technologies to identify and assess potential water system vulnerabilities. Interested vendors must submit proposals electronically at www.savannahga.gov/bids by 1:30 PM on Tuesday, September 30, 2025. A mandatory pre-bid conference is scheduled for Tuesday, September 16, 2025, at 9:00 AM, located at the Floyd Adams, Jr. Complex, 20 Interchange Drive in Savannah, Georgia. This conference will provide an opportunity for potential bidders to ask questions, clarify requirements, and gain additional insights into the project's scope and expectations. The procurement covers Chatham County and involves comprehensive water leak detection services that likely require advanced technical capabilities, data analysis skills, and specialized AI-driven assessment methodologies.

The City of Savannah expressly promotes equal opportunities for all vendors in municipal purchases, suggesting an open and inclusive procurement process. While specific set-aside designations are not explicitly detailed, the language implies a commitment to diverse vendor participation. The Board of Purchase reserves the right to reject any and all proposals and to waive formalities, providing flexibility in the selection process. Although specific budget ranges are not provided, water infrastructure surveys typically represent significant municipal investments requiring sophisticated technological solutions. The procurement appears designed to encourage competitive bidding from qualified technology and water infrastructure assessment firms with demonstrable AI-driven leak detection capabilities. Potential respondents should be prepared to demonstrate advanced technical competencies, proven track records in municipal water infrastructure analysis, and robust AI-enabled surveying methodologies.