GreatNorthCollective/greatnorth-us-federal-ai-inventory huggingface dataset:
US federal AI use case: Genius AI
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Genius AI Detection is a computer-aided detection and diagnosis (CADe/CADx) software device. It is intended to be used with compatible digital breast tomosynthesis (DBT) systems to identify and mark regions of interest, including soft tissue densities (masses, architectural distortions and asymmetries) and calcifications in DBT exams from compatible DBT systems, and provide confidence scores that offer assessment for Certainty of Findings and a Case Score. The device intends to aid in the interpretation of digital breast tomosynthesis exams in a concurrent fashion, where the interpreting physician confirms or dismisses the findings during the reading of the exam.
Purpose and benefits: Support mammographic image analysis.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Implementation of a Severe COVID-19 Risk Prediction Tool
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: CVI42
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: VA Chat Copilot Meta Pilot
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Development stage: Retired
US federal AI use case: Discharge Predictive Model
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
US federal AI use case: Optimizing Renin Angiotensin System Blocker Use for Kidney Disease
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
US federal AI use case: CT CoPilot
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: CT CoPilot is intended for use in automating post-acquisition quantitative analysis of computed tomography (CT) images of the brain for patients aged 18 or older. CT CoPilot performs automatic reformatting, labeling, and quantification of segmentable structures from a set of CT images.
Purpose and benefits: Accelerate image analysis workflows. This software is intended to automate the current manual process of identifying, labeling, and quantifying structures identified on CT images of the brain and to provide automated registration and reformatting of data.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Cranial Navigation, Navigation Software Cranial, Navigation Software Craniofacial, Cranial EM System, Automatic Registration iMRI
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Cranial EM is intended as an image-guided planning and navigation system to enable neurosurgery procedures. The device is indicated for any medical condition in which a reference to a rigid anatomical structure can be identified relative to images (Computed Tomography (CT), Computed Tomography Angiography (CTA), X-Ray, MR, Magnetic Resonance Angiography (MRA) and ultrasound) of the anatomy.
Purpose and benefits: Support neurosurgery planning.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Aquilion ONE with AiCE
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: ECG/EKG Machines- Interpretation of Results
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: CellaVision DM1200 with the body fluid application
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: CellaVision DM 1200 with the body fluid application automatically locates and presents images of nucleated cells on cytocentrifuged body fluid preparations. The body fluid application is intended for a differential count of white blood cells.
Purpose and benefits: Accelerate counting and recognition of blood cells.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Appointment Comments Categorization
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Development stage: Retired
Risk category: High-impact
US federal AI use case: Nediser Reports QA
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Nediser is a continuously trained artificial intelligence "radiology resident" that assists radiologists in confirming features in radiology images, including x-ray. It helps with workflow efficiency and quality. The program fills in the comparison date, identifies the joint for the appropriate template, performs measurements, and grades arthritis. The output is sent to the radiologist as a draft report. The radiologists use this to save time and improve accuracy. No output is sent to the EHRM or used by other providers.
Purpose and benefits: - Promote standardization of radiology reports as currently their inherent unstructured and narrative style can be subjective, leading to variability. 
- Promote quantitative reporting
- Reduce errors of transcription, such as laterality or no. of views, which the Radiologist has to manually dictate without this software.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: CARTO 3 EP Navigation System Software V8.0 (FG-5400-00, FG-5400-00U)
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The CARTO 3 EP Navigation System V8.0, is a catheter-based atrial and ventricular mapping system designed to acquire and analyze navigation catheter’s location and intracardiac ECG signals and use this information to display 3D anatomical and electroanatomical maps of the human heart. The intended use of the CARTO 3 System is catheter-based cardiac electrophysiological (EP) procedures.
Purpose and benefits: Supports identification of and viewing heart activity patterns.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Care Assessment Needs (CAN) Score
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Identify patients at potential risk for 90 day hospitalization and 90 day mortality: CAN 3.0 is a pair of logistic regression models that risk stratify Veterans by their likelihood of 90-day mortality and 90-day hospitalization
Purpose and benefits: Help providers care for patients - the outputs of the AI systems is an additional resource for care providers
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Cartesion Prime (PCD-1000A/3) V10.15
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The system is intended to acquire PET images of any desired region in the whole body and CT images of the same region (used for attenuation correction or image fusion) to detect the location of positron emitting radiopharmaceuticals in the body with the obtained images.
Purpose and benefits: This information can assist with the research, detection, localization, evaluation, diagnosis, staging, restaging, and follow-up of diseases and disorders as well as their therapeutic planning and therapeutic outcome assessment.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: VA CART SYNTAX Risk Model
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The VA CART SYNTAX risk model predicts 30-day post-Percutaneous Coronary Intervention (PCI) mortality, using a combination of clinical and anatomic variables. The model is available to facilitate personalized informed consent discussions and appropriate preparation for high-risk PCI cases.
Purpose and benefits: More informed personalized discussions with patients: The model is available to facilitate personalized informed consent discussions and appropriate preparation for high-risk PCI cases
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Cardiac CT Function Software Application
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: It is designed to support physicians in the visualization, evaluation, and analysis of the heart function through the calculation of parameters, such as volume and mass. The device is intended to be used as an aid to the existing standard of care and does not replace existing software applications that physicians use.
Purpose and benefits: Automate volume and mass calculations to support physicians in the visualization, evaluation, and analysis of the heart function.
Topic area: Health and Medical
Development stage: Deployed
US federal AI use case: Fall Prediction Tool
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The Morse Fall Scale (MFS), as it is currently utilized, often fails to accurately assess fall risk, highlighting the need for more precise and timely fall risk assessment tools to prevent falls.
Purpose and benefits: The goal is to provide a more accurate fall assessment score than the existing Morse Fall Score which could improve patient safety outcomes. Better assessing fall risk and applying proper fall prevention interventions would also translate to cost avoidance and savings.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: VA CART Mortality Model
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The VA CART mortality risk model is based on logistic regression using baseline clinical and procedural variables to predict post-PCI 30-day mortality. The model is available to facilitate risk stratification at the point of care.
Purpose and benefits: More informed personalized discussion with the patient - the outputs of the AI system is an additional resource for care providers
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Pact Act Co-Pay Exemption Prediction Tool
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: VA CART Nephropathy Risk Model
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The VA CART nephropathy risk model is based on logistic regression using baseline clinical and procedural variables to predict Post-Percutaneous Coronary Intervention (PCI) acute kidney injury (AKI). The model is available to facilitate risk stratification at the point of care. In operations and maintenance.
Purpose and benefits: More informed personalized discussions with patients
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Purchase Order Filing
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Filing purchase orders and documents related to them is time consuming for pharmacy staff and the paper files take up floor space.
Purpose and benefits: Having the AI file the documents online saves staff time and makes it easier to find the documents we need in the event of an audit.
Topic area: Admin Functions
Development stage: Deployed
US federal AI use case: Brainlab Elements Image Fusion, Contouring (4.5);Image Fusion (4.5);Fibertracking (2.0);BOLD MRI Mapping (1.0);Image Fusion Angio (1.0)
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Brainlab Elements are software applications indicated for the processing of medical image data to support the intended user group to perform image guided surgery and radiation treatment planning. The Brainlab Elements 6.0 are applications that transfer Digital Imaging and Communications in Medicine (DICOM) data to and from picture archiving and communication systems (PACS) and other storage media devices. They include modules for 2D & 3D image viewing, image processing, image co-registration, image segmentation and a 3D visualization of medical image data for treatment planning procedures.
Purpose and benefits: Accelerate imaging workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: VA CART Myocardial Ischemia NLP
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Extracts myocardial ischemia information in VistA using Natural Language Processing (NLP) of Radiology report.
Purpose and benefits: Helps providers to care for patients
Topic area: Health and Medical
Development stage: Deployed
US federal AI use case: VA CART Ejection Fraction NLP
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The model is available to facilitate risk stratification at the point of care. It extracts ejection fraction (EF) information in VistA using Natural Language Processing (NLP) of Echocardiogram TIU report text.
Purpose and benefits: This use case will enable a more informed personalized discussion with patients
Topic area: Health and Medical
Development stage: Deployed
US federal AI use case: BioPlex 2200 ANA Screen with Medical Decision Support Software for Use with BioPlex 2200 Multi-Analyte Detection System
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The BioPlex 2200 Medical Decision Support Software (MDSS) is a pattern recognition algorithm that can enhance the performance of the Antinuclear Antibody (ANA) Screening associated diagnostic patterns, among its multiple assay results.
Purpose and benefits: Support antibody screening procedures.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: GE AMX Portable X-ray Machines
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: VA CART Bleeding Risk Model
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The VA CART bleeding risk model is based on logistic regression, using baseline clinical and procedural variables to predict post-Percutaneous Coronary Intervention (PCI) in-hospital bleeding events. The model is available to facilitate risk stratification at the point of care. It is in operations and maintenance.
Purpose and benefits: The model is available to facilitate risk stratification at the point of care. The outputs of the AI systems is an additional resource for care providers.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Biograph Vision, Biograph MCT Family Of PET/CTs
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The Biograph Vision and Biograph mCT systems provide registration and fusion of high-resolution metabolic and anatomic information from the two major components of each system (Positron emission tomography (PET) and computed tomography (CT)). These systems are designed for whole body oncology, neurology and cardiology examinations.
Purpose and benefits: Accelerate imaging workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Rythm Express
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
US federal AI use case: AutoContour Model RADAC V3
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: AutoContour is intended to assist radiation treatment planners in contouring and reviewing structures within medical images in preparation for radiation therapy treatment planning.
Purpose and benefits: Accelerate radiation therapy treatment planning workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Forescout: AI Behavioral Anomaly Detection w/ Automated Enforcement
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: Leverage AI/ML models to learn normal behavior patterns across endpoints, IoT, and OT devices. Identify zero-day threats, insider attacks, or lateral movement by compromised devices that are missed by point-in-time tools within the network.

Use these patterns to detect anomalies in real time. When an anomaly (unusual data transfer, unauthorized protocol, lateral movement) is detected Forescout automatically enforces a response policy—such as quarantining the device, notifying SOC security teams, or triggering an orchestration workflow.
Purpose and benefits: Benefits include real-time response to unknown threats, reduced time to detect and respond, eliminates manual correlation with siloed tools.
Topic area: Cybersecurity
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Computer Vision Framework (CVF)
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: aPROMISE X
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: Ask Sage – Generative AI Platform for VA Administrative Efficiency
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: VA staff often spend significant time searching for information, drafting communications, and compiling documentation. These tasks can be repetitive, time-consuming, and prone to inconsistencies when performed manually. Ask Sage addresses this by providing a secure, conversational interface that can quickly produce draft materials, summarize complex information, and retrieve relevant guidance, enabling staff to focus on higher-value work.
Purpose and benefits: Increased administrative efficiency through faster document drafting and information retrieval.

Greater consistency and quality in written materials and policy summaries.

Reduced workload for staff, allowing more focus on mission-critical duties.

Cost savings from reduced staff time spent on repetitive, manual tasks.

Improved timeliness and responsiveness in internal and external communications.
Topic area: Admin Functions
Development stage: Pilot
US federal AI use case: Aplio i900, Aplio i800 and Aplio i700 Software V8.1 Diagnostic Ultrasound System
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The Diagnostic Ultrasound System Aplio i900 Model TUS-AI900, Aplio i800 Model TUS-AI800, Aplio i700 Model TUS-AI700 are indicated for the visualization of structures and dynamic processes within the human body, using ultrasound, and to provide image information for diagnosis in the following clinical applications: fetal, abdominal, intra-operative (abdominal), pediatric, small organs (thyroid, breast and testicle), trans-vaginal, trans-rectal, neonatal cephalic, adult cephalic, cardiac (both adult and pediatric), peripheral vascular, transesophageal, musculo-skeletal (both conventional and superficial), laparoscopic and Thoracic/Pleural. This system provides high-quality ultrasound images in the following modes: B mode, M mode, Continuous Wave, Color Doppler, Pulsed Wave Doppler , Power Doppler and Combination Doppler, as well as Speckle-tracking, Tissue Harmonic Imaging, Combined Modes, Shear wave, Elastography, and Acoustic attenuation mapping. This system is suitable for use in hospital and clinical settings by physicians or legally qualified persons who have received the appropriate training. In addition to the aforementioned indications for use, when the Endoscopic Ultrasound (EUS) transducer GF-UCT180 is connected, Aplio i800 Model TUS-AI800/E3 provides image information for the diagnosis of the upper gastrointestinal tract and surrounding organs.
Purpose and benefits: Accelerate ultrasound workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Alignment System Cranial, Alignment Software Cranial, Cirq Alignment Software Cranial Biopsy, Cirq Alignment Software Cranial sEEG, Varioguide Alignment Software Cranial
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Alignment System Cranial is intended to support the surgeon in planning and achieving a trajectory with surgical instruments during cranial stereotactic procedures. The indications for use are biopsy of intracranial lesions and placement of stereoelectroencephalography (SEEG) electrodes.
Purpose and benefits: Accelerate surgery planning workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Dental - Dentsply Sirona CERE
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: Fusion 2024
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: Assist users with low or no vision with interpreting graphs that were not properly provided alternative text descriptions.
Purpose and benefits: Increased efficiency and cost savings as sighted assistance is not required to describe what is being displayed.
Topic area: Admin Functions
Development stage: Deployed
US federal AI use case: Acumen Hypotension Prediction Index - EV1000 Clinical Platform, Acumen Hypotension Prediction Index - Hemosphere Advanced Monitoring Platform, Acumen Hypotension Prediction Index, Hemosphere Advanced Monitoring Platform - Pressure
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The Edwards Lifesciences Acumen Hypotension Prediction Index feature provides the clinician with physiological insight into a patient’s likelihood of future hypotensive events (defined as mean arterial pressure < 65 mmHg for at least one minute in duration) and the associated hemodynamics. The Acumen HPI feature is intended for use in surgical or non-surgical patients receiving advanced hemodynamic monitoring. The Acumen HPI feature is considered to be additional quantitative information regarding the patient’s physiological condition for reference only and no therapeutic decisions should be made based solely on the Hypotension Prediction Index (HPI) parameter.
Purpose and benefits: Support hypotension monitoring.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Xtract WDS - OSLE
Agency: Department of Veterans Affairs - OSP: Office of Operations, Security, and Preparedness
Problem addressed: Heat map detection for weapon detection software.
Purpose and benefits: The AI assisted Weapon Detection System will be used to detect weapons and alert staff. This would aid in ensuring the area is safe and secure for Veterans, Visitors, and Employees.
Topic area: Law Enforcement
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: TeraRecon
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: Abridge Ambient Scribe
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: This solution is intended to solve the following problems: 
- Clinician burnout by decreasing clinical documentation burden which is resulting in 
- Clinicians focusing on their computer rather than the Veteran during the visit by reducing clinical documentation during patient visits
- Poor quality and unstandardized clinical documentation
Purpose and benefits: - Reduced clinician burnout 
- Improved Veteran satisfaction with healthcare experiences 
- Future: Improved billing/coding which can provide financial benefit to the VA
Topic area: Health and Medical
Development stage: Pilot
Risk category: High-impact
US federal AI use case: Avigilon Camera/Search Function - OSSO
Agency: Department of Veterans Affairs - OSP: Office of Operations, Security, and Preparedness
Problem addressed: A search function in a security video surveillance system that searches for points of interest in the video.
Purpose and benefits: The integration of artificial intelligence (AI) into VA Police operations has significantly enhanced efficiency and response capabilities. Traditionally, personnel were required to manually review recorded video and images which was a time-consuming process. With AI, these records can now be autonomously searched, drastically reducing manpower hours.

Moreover, during emergent situations, AI has proven instrumental in locating persons of interest, such as missing individuals or patients. This capability has greatly improved the VA Police’s ability to respond swiftly and effectively, ultimately enhancing safety and operational readiness.
Topic area: Law Enforcement
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Pension Optimization Initiative (POI)
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: VBA’s POI is a transformative effort that seeks a Managed Services Provider (MSP) to convert an existing manual business process into automated processing of Pension, Dependency Indemnity Compensation (DIC), and Burial claims. This effort is focused on dramatically improving the Veteran Experience while significantly reducing costs. POI automation will process Pension, DIC, and Burial claims more quickly, consistently, and efficiently.
Purpose and benefits: Reduced average days to complete claims processing. Reduced claims inventory. Reduced amount of manual claims processing hours to accomplish mission.
Topic area: Benefits Processing
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Limited Use of Azure Speech Services in PETALS Platform
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Azure speech services allow the Interactive Voice Response (IVR) system to detect if the IVR should leave a voicemail or continue to a voice prompt to engage the end user.
Purpose and benefits: Azure speech services allows the optimization of reducing burden on the veteran and enhancing research and outreach efforts to engage the Veteran.
Topic area: Health and Medical
Development stage: Deployed
US federal AI use case: CareCentra Next Level Personalized AI Health Coach
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
US federal AI use case: Medallia Software as a Service (SaaS) - VSignals and ESignals
Agency: Department of Veterans Affairs - VEO: Veterans Experience Office
Problem addressed: Ability to take concrete action to address the concerns and pain points of Veterans by case-managing and undertaking service recovery on input/commentary provided by Veterans about their VA experiences in VSignals free text comments.
Purpose and benefits: Systems redesign improvements by VA administrations based on actional input from Veterans, family members, caregivers, and survivors.
Topic area: Service Delivery
Development stage: Deployed
US federal AI use case: E2 HelpBot
Agency: Department of Veterans Affairs - Office of the Deputy Secretary of VA
Problem addressed: EEO Users browse through documents like the User Guides or knowledge articles to understand E2 functionality. Additionally, many Help Desk Tickets are entered for support on E2 functions as well. We plan to develop an internal HelpBot using an LLM model (GPT 4.0) that can assist users to ask the Help Bot questions, reducing user frustration and time to figure out how to perform a task. This use case will provide a knowledgebase to assist users to get information on EEO processes.
Purpose and benefits: Increased Efficiency
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: AI Microlearning (OttoLearn)
Agency: Department of Veterans Affairs - OALC: Office of Acquisitions Logistics, and Construction
Problem addressed: The VA Acquisition Academy’s (VAAA) Acquisition Intern Program (AIP) trains 1102 contract specialists. The 12-month program (including one-month post training support) consists of face-to-face and virtual classroom training at the VA Acquisition Academy and On-The-Job Training (OJT) at contracting sites across the United States. Periods of academic training are followed by longer periods of OJT. Unfortunately, due to the dynamic nature of the acquisition field offices, interns are often not able to focus on the acquisition lifecycle steps and content they learned during the previous classroom training block. With the introduction of a comprehensive national certification exam (FAC-C/P exam) in 2023, we needed to help our interns better retain the information they learned during the academic training blocks while out on OJT. This use case is intended to combat learning loss during long periods of OJT, which may have a severely negative impact on interns’ ability to pass the FAC-C/P certification exam.
Purpose and benefits: Increased first time pass rate of taking the FAC-C/P certification exam. 
During the pilot year, the interns that used the software the most passed the certification exam at a rate of 94%, while those in the same class who used the software the least passed at a rate of 76%.
Topic area: HR
Development stage: Deployed
US federal AI use case: Pathology and Laboratory Medicine SharePoint Chatbot - Quincy
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The current SharePoint page has a tremendous amount of information. Using the Chatbot helps the field search for information without having to contact the office directly.
Purpose and benefits: The chatbot will increase efficiency of time it takes for individuals to find important information and free up program staff to concentrate on quality and safety issues for the clinical laboratory care of the Veteran.
Topic area: Other
Development stage: Pre-deployment
US federal AI use case: Healthcare Text Anonymizer
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: This application reduces the manual processing time for anonymization and improves the accuracy of removing identifiable information in healthcare text. This is important because one of the applications of this project is to publicly release data on the medical impact of the new electronic health records system, Oracle. As Oracle gets rolled out to more facilities, there is a need to release more anonymized incident reports of Oracle's impact on patient health. Manually anonymizing all of these reports is not scalable nor sustainable, which is why this AI application helps.
Purpose and benefits: Increased efficiency and increased security of patient Personally Identifiable Information (PII)
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: OpenAI Embedding Generation for Future Vector Search of Banking Data
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The current design of a long term document for a banking partner consists of cloud blob storage which are registered into a database with metadata. A future phase will require full-text document search. We can OCR this information now, and implementing vector embeddings would dramatically help individuals find the specific documents. PNC bank will save documents for 7 years and wants to be able to find specific documents.
Purpose and benefits: Increased efficiency of document retrieval in long term document archive.
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: VistA Records Accessed by SQL (VRAS)
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The VistA Records Accessed by SQL (VRAS) is a transformative initiative aimed at modernizing data accessibility and analytics within the Department of Veterans Affairs (VA).  By eliminating reliance on costly middleware and reducing process overhead, VRAS enables real-time, SQL compatible data access directly from Vista.  

This initiative establishes a seamless, efficient data pipeline, enhancing reporting capabilities, reducing infrastructure complexity, and supporting data-driven decision-making across all VistA instances.  With improved accessibility to high-quality data, VA users can generate timely, accurate insights that drive operational efficiency and better outcomes for departments that directly affect veteran care.
Purpose and benefits: Full AI access to each VistA instance via ODBC/JDBC.
Topic area: Health and Medical
Development stage: Pilot
US federal AI use case: Ask VA Inquiry Automated Category Classification System
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: Primary Problem - Manual Categorization Burden: Veterans and their families currently manually navigate complex category, topic/subtopic selection fields when submitting inquiries through AskVA. This creates barriers to accessing VA services and can result in incorrect categorization that delays or misdirects their requests.

Scale and Efficiency Problem: The VA processes over 106M inquiry records, with 35.1M completed inquiries requiring manual review and routing. Manual categorization at this volume creates significant processing delays and resource strain on both veterans submitting requests and VA staff managing the workflow.
 
Consistency and Accuracy Problem: Manual categorization leads to inconsistent classification across inquiries, with approximately 11.3M potential misclassifications identified where topics appear under multiple categories. This inconsistency results in inquiries being routed to incorrect service teams, causing delays in resolution and poor customer experience.

Resource Allocation Problem: Incorrect or inconsistent categorization prevents optimal allocation of VA staff and resources across the 18 standardized service areas (disability compensation, education benefits, healthcare, housing assistance, etc.), leading to inefficient service delivery.

The AI solution mitigates these problems by providing automated, consistent, and accurate categorization that improves both veteran experience and VA operational efficiency.
Purpose and benefits: For Veterans and the General Public:
- Improved access to VA services by eliminating complex manual category selection barriers
- Enhanced customer experience with streamlined AskVA submission process
- Reduced frustration and time burden when seeking VA assistance

For VA Agency Mission:
- Increased operational efficiency in processing 106+ million inquiry records
- Improved resource allocation with accurate categorization enabling better workload distribution
- Reduced processing delays and backlogs through automated classification at 83.38% accuracy
Topic area: Service Delivery
Development stage: Pre-deployment
US federal AI use case: Report Anomalous VIEWS CCM User Behavior
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The AI protects VA sensitive information from insider threat scenarios. Sensitive information includes the unauthorized disclosure of information such as financial records, Veteran information, and employee records stored in the Salesforce application titled "VA Integrated Enterprise Workflow Solution (VIEWS)." AI scans a CRM Analytics database consisting of Salesforce-generated log files to locate patterns of unusual end-user behavior (such as excessive after-hours logins and large, keyword searches (whistleblower, investigation, DD214, discharge, and similar terms) irregular database download attempts) and to automatically report such incidents to an email distribution group for action.
Purpose and benefits: The main benefit of this AI project is to provide improved, early incident detection for protecting VA employee and Veteran sensitive information, including PHI, PII, and Sensitive But Unclassified information stored in VIEWS.
Topic area: Cybersecurity
Development stage: Pre-deployment
US federal AI use case: Power Platform Solutioning Chatbot
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The intention of the tool is to speed up the time taken between users identifying that help is needed for a solution and resolving what would be required to implement the solution as a citizen developer on the Microsoft Power Platform.
Purpose and benefits: The tool will provide a convenient way for citizen developers on the Microsoft Power Platform to be able to ask questions regarding the kind of application or solution they are trying to build and have the chatbot respond with the technologies that can be employed to get the solution completed as well as any licensing details that the user needs to be aware of. The tool is intended to speed up the time between users identifying that help is needed for a solution and resolving what would be required to implement the solution as a citizen developer on the Microsoft Power Platform. This tool would also help identify any potential issues regarding the solution that may need to be handled along the way, like licensing needs.
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: VA AI Assist
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: Reviewing information about a patient prior to an upcoming encounter is an important way in which clinicians prepare for an effective visit. Clinicians are challenged to effectively complete this review prior to encounters, given time constraints and the manual effort required to navigate electronic health record systems to seek the information. This results in a lower effectiveness of the visit and increased clinician burnout.
Purpose and benefits: There is a significant opportunity for AI-powered search and summarization of clinical information to assist clinicians with efficiently and effectively reviewing a patient’s record prior to an encounter.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: EEO Consultation and Guidance
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: As you see a decrease in the amount of EO program managers within the VA, it'd be helpful to utilize AI to manage and analyze employee complaints, including those related to Equal Employment Opportunity (EEO).  We want to have 24 hour EEO response to employee questions surrounding discrimination and harassment.  The AI tool will not be equipped to provide legal or counseling services. It can receive Complaint Intake and Triage, provide Data Analysis, Sentiment Analysis, and Providing Information and Resources.
Purpose and benefits: Providing useful information in a timely manner. This is not legal advice.
Topic area: HR
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Tachyon AI
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: Tachyon "1E Intelligence" is expected to provide deeper and more meaningful insights into the digital experience of VA employees and customers, including better visibility into the performance of endpoint devices. It is also expected to enhance the Software Asset Management features and increase the effectiveness of User Sentiment gathering.  This version will include additional features like “1E Intelligence”, which leverages various types of AI (predictive, causal, generative, cloud, edge, “Digital Twin”) to enhance insights into the digital employee experience, device performance, and software reclamation.
Purpose and benefits: Helps to transform complex data into clear and actionable insights, ensuring digital workplace leaders can make informed decisions that boost uptime, increase operational efficiency, and ultimately result in improved patient care.
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: Smart Claim Check
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: Smart Claim Check (SCC) reduces avoidable claims processing errors by addressing the problem of manually reviewing extensive documentation by Veterans Service Representatives (VSRs) to identify and resolve issues. Claims processing errors that can be avoided in the claims process leads to extended wait times for Veterans to receive the benefits to which they are entitled. SCC leverages natural language processing (NLP) and machine learning (ML) to analyze past deferral data and identify common patterns and themes.
Purpose and benefits: By leveraging these technologies described in #12, Smart Claim Check can automatically review claim documentation, identify common patterns, and offer structured recommendations, including context-specific guidance from the M21-1 manual, confidence scores, and links to relevant sections, thereby expediting the claims review process and reducing avoidable re-work and extended processing times.
Topic area: Benefits Processing
Development stage: Pre-deployment
US federal AI use case: Deduplication in Record Management
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: - Reduce manual process of opening record for review.
- Triage urgent veteran follow up needs by recognizing urgent or routine in boxes. 
- Kick back record requests missing important clerical details like signatures, names, or ICD 10 codes.
- Summarize Physical Therapy (PT) care records for VA practitioners to act on.
- Reduce clinical errors and manpower / manual resources in clinically evaluating forms
- Reduce clinical manpower and cloud storage in uploading duplicate documents
Purpose and benefits: - Decrease clerical and clinical costs related to record management.
- Increase Registered Nurse (RN) licensure to provide direct care. Too many RNs are pulled into record management, which takes them away from frontline needs.
- Decrease Veteran harm or death
- Increase Veteran satisfaction
- Decrease burnout
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Articulate 360: AI Assistant
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: The ability to efficiently and quickly create interactive and engaging eLearning for VBA claims processors. Engaging eLearning helps reduce instructor burden and time in traditional classroom settings, which increases productivity. Efficient training development also helps reduce instructional design burden, especially amidst decreased hiring abilities.
Purpose and benefits: The Articulate AI Assistant helps build more engaging eLearning courses in a timely manner. The AI assistant can help generate text to voice audio, create images, create outlines, create polls/quizzes, etc. This enhances the end-user experience of training and increases efficiency in training development, which in turn provides cost savings related to the amount of time taken to develop training.
Topic area: HR
Development stage: Deployed
US federal AI use case: Continuous Glucose Monitoring Summary
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Reduce work hours associated with manually scouring Ambulatory Glucose Profile metrics and reduce transcription errors while copying and pasta data between medical tools and platforms.
Purpose and benefits: Provide a holistic view of patient data and improve medical providers' efficiency in caring for patients.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Loan Guaranty Lender’s Handbook Chatbot
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: Loan Guaranty Service (LGY) has many policy and procedural documents that are difficult to know and retrieve information for. This AI tool is designed to make the knowledge retrieval process more efficient and improve consistency.
Purpose and benefits: Increase efficiency and consistency in knowledge retrieval from source documents (manuals, SOPs, other policy & procedural documents).
Topic area: Service Delivery
Development stage: Pre-deployment
US federal AI use case: Automated Ratings Summarization
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: We are attempting to reduce the claims backlog and processing time. Additionally, there is a large volume of documentation on a Veteran's record - this tool is intended to reduce the amount of time a claim processor spends sorting through documentation relevant to a Veteran's claimed issue.
Purpose and benefits: - Increased efficiency and lower time to decision on a benefits claim for a Veteran
- Improve the quality of decisions, which can ultimately result in a decrease in appeals
Topic area: Benefits Processing
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Summit AI Assistant
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The AI is intended to reduce the time required to extract rich and relevant information from a corpus of documents pertaining to a specific business domain. A combination of keyword and vector search methods deliver precise and relevant information from a specific business domain's knowledge base.
Purpose and benefits: The AI increases efficiency within a business process, especially in business processes that involve sifting through large amounts of information/knowledge captured in documents.
Topic area: Admin Functions
Development stage: Deployed
US federal AI use case: SIM VOX for training nursing scenarios
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: AI is intended for teaching and clinical training to improve nursing clinical decisions by putting them through a simulated scenario that they may encounter in real life. SIM VOX is an AI Software used to for simulation scenarios on nursuing competencies with mannequins.
Purpose and benefits: Improving clinical and patient outcomes.
Topic area: Health and Medical
Development stage: Pre-deployment
US federal AI use case: Service Period Validator (SPV) POC
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: Validate Veterans' service periods more accurately and quickly. This will ultimately save time and increase the quality of Veterans' decisions.
Purpose and benefits: Increase efficiency of benefits delivery and provide an accurate and timely automation of benefit eligibility decisions (original claims) by proactively assessing and correcting data quality of Veteran service period.
Topic area: Benefits Processing
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: CarestreamCS 9600
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: CS 9600 is an extraoral system intended to produce two-dimensional and three-dimensional digital X-ray images of the dento-maxilofacial, ENT (Ear, Nose and Throat), cervical spine and wrist regions at the direction of healthcare professionals, as diagnostic support for pediatric and adult patients.
Purpose and benefits: Accelerate dental imaging workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact