Abstract & Details
Description
Award ID: 49100425C0010 - Phase 2
In the U.S., more than 40,000 small and rural water systems face mounting challenges from aging infrastructure, staffing shortages, water quality degradation and increased regulatory pressure. Many of these systems lack the tools to detect issues early, retain institutional knowledge or ensure consistent compliance. The integrated team behind Aquaspec delivers a cutting-edge, artificial intelligence-powered decision support platform designed specifically for water and wastewater systems. Aquaspec combines predictive analytics, machine learning and a custom-trained large language model (LLM) to help operators improve water quality, reduce compliance violations and combat non-revenue water loss without requiring expensive infrastructure upgrades. Aquaspecs development is led by Delta Bravo AI, in collaboration with the South Carolina Department of Environmental Services, and several public utilities and academic experts. In Phase 2, the Aquaspec team will expand deployment to communities across South Carolina and the Midwest, working directly with operators to refine system recommendations and optimize real-world impact. The team will also enhance Aquaspecs LLM to tailor training, standard operating procedure guidance and operational support to individual operator skill levels and local system needs. Scenario-based simulations built from local datasets will help accelerate onboarding and certification pathways, addressing workforce shortages and knowledge gaps. The funded team will finalize a scalable go to-market plan and deepen partnerships with state agencies, water authorities and training institutions. Aquaspec strengthens water system resilience by giving operators and leadership teams predictive visibility, faster decision-making and operational continuity. Real-time data analysis empowers these systems to stay ahead of equipment failures, contamination risks and regulatory demands. The platform equips under-resourced communities with advanced digital tools to deliver safe, clean water, while building local workforce capacity for the future of infrastructure management.
NSF Program Director: Richard Farnsworth
In the U.S., more than 40,000 small and rural water systems face mounting challenges from aging infrastructure, staffing shortages, water quality degradation and increased regulatory pressure. Many of these systems lack the tools to detect issues early, retain institutional knowledge or ensure consistent compliance. The integrated team behind Aquaspec delivers a cutting-edge, artificial intelligence-powered decision support platform designed specifically for water and wastewater systems. Aquaspec combines predictive analytics, machine learning and a custom-trained large language model (LLM) to help operators improve water quality, reduce compliance violations and combat non-revenue water loss without requiring expensive infrastructure upgrades. Aquaspecs development is led by Delta Bravo AI, in collaboration with the South Carolina Department of Environmental Services, and several public utilities and academic experts. In Phase 2, the Aquaspec team will expand deployment to communities across South Carolina and the Midwest, working directly with operators to refine system recommendations and optimize real-world impact. The team will also enhance Aquaspecs LLM to tailor training, standard operating procedure guidance and operational support to individual operator skill levels and local system needs. Scenario-based simulations built from local datasets will help accelerate onboarding and certification pathways, addressing workforce shortages and knowledge gaps. The funded team will finalize a scalable go to-market plan and deepen partnerships with state agencies, water authorities and training institutions. Aquaspec strengthens water system resilience by giving operators and leadership teams predictive visibility, faster decision-making and operational continuity. Real-time data analysis empowers these systems to stay ahead of equipment failures, contamination risks and regulatory demands. The platform equips under-resourced communities with advanced digital tools to deliver safe, clean water, while building local workforce capacity for the future of infrastructure management.
NSF Program Director: Richard Farnsworth
| Status | Active |
|---|---|
| Effective start/end date | 06/06/25 → 06/05/28 |
Funding
- Other Programs (Technology): $4,986,559.00
Active Fiscal Year
- FY2028
- FY2027
- FY2026
- FY2025
Start Fiscal Year
- FY2025
TIP Programs
- Other Programs (Technology)
Key Technology Areas
- Artificial Intelligence
- (confidence score: 100%)
- Data and Cybersecurity
- (confidence score: 93%)
- Disaster Prevention and Mitigation
- (confidence score: 100%)
Technology Foci
- Natural disaster prevention and mitigation
- (confidence score: 96%)
- Data Management / Databases
- (confidence score: 97%)
- Machine Learning Training Data
- (confidence score: 100%)
- Machine Learning (ML)
- (confidence score: 96%)
Current Congressional District
- District n. 05 of South Carolina
United States
- South Carolina
Core Based Statistical Area (CBSA)
- Charlotte-Concord-Gastonia, NC-SC
County
- County: York, SC
EPSCoR Jurisdiction
- Yes
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