AI use-case explorer
AI use cases
Search and filter every reported use case. Open a record for the agency's full description, governance answers and source provenance.
Columns (7)
| Use case | Agency | Stage | High-impact | Topic area | AI classification | Sourcing |
|---|---|---|---|---|---|---|
| Rangeland Condition Monitoring Assessment and Projection (RCMAP) [2024 INV#WO0000000107126] DOI-0171 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| use of random forest for species distribution modeling DOI-0161 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Global food-and-water security-support analysis data (GFSAD) project [2024 INV#WO0000000107073] DOI-0095 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Frog vocalization recognition from digital recordings DOI-0092 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Patterns in the Landscape – Analyses of Cause and Effect DOI-0090 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Submersed Aquatic Vegetation Vulnerability Evaluation Application (SAVVEA) DOI-0081 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| U.S. Wind Turbine Database DOI-0080 · USGS | DOI | Deployed | Not high-impact | Energy and the Environment | Computer vision | Developed in-house |
| Machine learning in remote sensing-based wildfire and natural resource risk assessments DOI-0072 · USGS | DOI | Deployed | Not high-impact | Emergency Management | Classical / predictive ML | Developed in-house |
| Telemetry Analysis Learning Algorithm (TALA) DOI-0070 · USGS | DOI | Deployed | Not high-impact | Other | Classical / predictive ML | Developed in-house |
| LANDFIRE DOI-0069 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| DocketScope DOI-0040 · FWS | DOI | Deployed | Not high-impact | Administrative Functions | Natural language processing | Purchased from vendor |
| Hanford Ai Liaison (HAL) 1.1 DOE-469 · RL - Hanford - Richland Operations Office - Hanford (EM) | DOE | Deployed | Not high-impact | Administrative Functions | Generative AI | Developed in-house |
| GitHub Co-Pilot DOE-571 · RL - Hanford - Richland Operations Office - Hanford (EM) | DOE | Deployed | Not high-impact | Information Technology | Generative AI | Purchased from vendor |
| LivChat DOE-613 · LLNL - Lawrence Livermore National Laboratory (LFO) | DOE | Deployed | Not high-impact | Information Technology | Generative AI | Developed in-house |
| Invoice Scanning System DOE-632 · RL - Hanford - Richland Operations Office - Hanford (EM) | DOE | Deployed | Not high-impact | Procurement and Financial Management | Classical / predictive ML | Developed in-house |
| Deep Learning based image segmentation [2024 INV#WO0000000107975] DOI-0175 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Foundation Models to Advance Earth Science [2024 INV#WO0000000107153] DOI-0172 · USGS | DOI | Pilot | Not high-impact | Science | Generative AI | Developed in-house |
| CHS Q Business AI Assistant (theKraken) DOI-0169 · USGS | DOI | Pilot | Not high-impact | Administrative Functions | Generative AI | Developed in-house |
| LLM-Assisted Volcanic Alert Monitoring DOI-0109 · USGS | DOI | Pilot | Not high-impact | Science | Natural language processing | Developed in-house |
| Reducing elevation error in coastal wetland digital elevation models DOI-0088 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Developing land cover maps for barrier islands using satellite imagery DOI-0087 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Invasive Carp Harvest Predictive Model DOI-0061 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Flor-AI: Developing a Remotely Sensed Image Classification Method for Inventory and Monitoring of Flora in Digital UAS Imagery DOI-0079 · USGS | DOI | Pilot | Not high-impact | Energy and the Environment | Computer vision | Developed in-house |
| Automating the Detection and Classification of Wildlife in Aerial Imagery [2024 INV#WO0000000109409] DOI-0075 · USGS | DOI | Pilot | Not high-impact | Energy and the Environment | Computer vision | Developed in-house |
| Automated identification of ducks from hunter-submitted photos using deep learning models DOI-0074 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Automated photographic identification of Eastern box turtles DOI-0073 · USGS | DOI | Pilot | Not high-impact | Science | Computer vision | Developed in-house |
| Pathogen identification in salmon DOI-0071 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Microsoft Co-Pilot DOE-518 · RL - Hanford - Richland Operations Office - Hanford (EM) | DOE | Pilot | Not high-impact | Administrative Functions | Generative AI | Purchased from vendor |
| Ask CAS DOE-522 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Other | Generative AI | Developed in-house |
| Ask Alan DOE-569 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Information Technology | Generative AI | Developed in-house |
| DIRECTIVES DOE-587 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Administrative Functions | Generative AI | Developed in-house |
| FindMATID DOE-604 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Procurement and Financial Management | Generative AI | Developed in-house |
| Ask IT DOE-615 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Information Technology | Generative AI | Developed in-house |
| ChatSRS DOE-638 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Administrative Functions | Generative AI | Developed in-house |
| UNSPSC Codes DOE-642 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Procurement and Financial Management | Generative AI | Developed in-house |
| Hanford Ai Liaison (HAL) 2.0 DOE-653 · RL - Hanford - Richland Operations Office - Hanford (EM) | DOE | Pre-deployment | Not high-impact | Administrative Functions | Generative AI | Developed in-house |
| Ask HR DOE-704 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Human Resources | Generative AI | Developed in-house |
| mass3 DOE-707 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Science | Generative AI | Developed in-house |
| Crickets DOE-723 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Cybersecurity | Classical / predictive ML | Developed in-house |
| AccessAI DOE-725 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Administrative Functions | Generative AI | Developed in-house |
| Data-driven approaches to filling missing time-series data within the San Francisco Bay-Delta [2024 INV#WO0000000107683; INV#WO0000000107488] DOI-0174 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Machine Learning based shoreline detection and sea ice dynamics using coastal cameras [2024 INV#WO0000000108008] DOI-0166 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Tsunami Hazard Analysis [2024 INV#WO0000000108470] DOI-0165 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Determining the resource potential of critical minerals in seafloor massive sulfide deposits [2024 INV#WO0000000109311] DOI-0163 · USGS | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Developed in-house |
| Poseidon DOE-544 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Procurement and Financial Management | Other | Developed in-house |
| Sindri DOE-695 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | Procurement and Financial Management | Agentic AI | Developed in-house |
| Neptune DOE-724 · SRS - ESB - Savannah River Site - Enterprise System Boundary | DOE | Pre-deployment | Not high-impact | International Affairs | Other | Developed in-house |
| Lead attribution model DOI-0152 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Not reported |
| Feature extraction and characterization for update of The National Map DOI-0131 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Not reported |
| Supervised learning for phycocyanin estimation from Sentinel-2 MSI in inland waters with independent validation DOI-0130 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Not reported |
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