GreatNorthCollective/greatnorth-us-federal-ai-inventory huggingface dataset:
US federal AI use case: Veteran Rehabilitation Services
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Make the connection of veterans to rehabilitation services streamlined and more efficient. Gather information over multiple platforms and create a timeline of service to better inform care and delineate access to additional services.
Purpose and benefits: By gathering information over multiple platforms and creating a service timeline to better inform care and delineate access to additional services, we can streamline care processes, efficiently deliver services, and ensure veterans are not lost in transitions of care.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Limited Payability Letter Automation
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The re-issuance of a benefits payment following Limited Payability currently relies on manual steps that take an undetermined amount of time. Using AI will allow VA to automate the re-issuance of benefits, accelerating the delivery of those re-issued payments to beneficiaries and reducing manual errors during the process.
Purpose and benefits: Increased efficiency, increased accuracy, and quicker delivery of benefits payments to beneficiaries.
Topic area: Benefits Processing
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Image Quality Control Tool
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Currently, patients submit images to My VA Images, then a provider reviews the images. If a patient submits a low quality image, they must await a response from the provider, who must then request that the patient submit another image. This causes unnecessary delays in patients receiving care regarding their dermatological conditions.

If the image is low quality (blurry, too light, too dark, too far, too close, not centered, or distracting background), this model will prompt patients to submit another image immediately following their submission.
Purpose and benefits: Increased efficiency due to immediate review and qualification of images submitted to My VA Images, simplifying the process for both patients and providers. Improved relations with patients and lower patient frustration with the overall process due to the simplified process.
Topic area: Service Delivery
Development stage: Pre-deployment
US federal AI use case: Disability Benefits Document Classifier
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: As a Veteran submitting documents to support a claim, I want the VA to automatically classify my uploads so that I can avoid confusing dropdowns and feel confident my evidence will be reviewed and processed correctly. The burden currently rests with Veterans to classify/label their documents on VA.gov after manually uploading them. As a result:
- Veterans face confusing submission experiences
- Veterans overuse the "other/correspondence" document label
- Veteran Service Representatives (VSRs) waste time opening mislabeled files in the Veterans Benefits Management System (VBMS) eFolder
- Automation systems ignore incorrectly labeled evidence or misroute it (causing delays of up to 26 days)
Purpose and benefits: Automating this manual task saves time for Veterans applying for benefits, VSRs processing claims, and increases throughput and accuracy of downstream automation systems.
Topic area: Benefits Processing
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Freed AI Medical Scribe
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Increase efficiency of our Primary Care providers. The AI scribe records the Veteran and provider conversation during an exam - it eliminates unnecessary parts of the exam conversation and provides a written report for the provider to edit and copy into the Veterans chart. The AI does not make a diagnosis, it just provides the written summary that the provider uses to complete their encounter and note.
Purpose and benefits: - Increased efficiency by having a written record of the exam. 
- Enhanced patient outcomes as the scribe records things that a provider might have missed in the conversation or coming back to the note/encounter the next day. 
- Lower missed opportunities for the provider.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ARANZ Medical Silhouette Wound Management System
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Evaluate parameter, depth, and area of a wound (image): The ARANZ Medical Silhouette system is employed in the VA for monitoring and tracking wounds.
Purpose and benefits: Enhance patient outcome by providing non-biased wound metrics and healing data. Automatically
detecting wounds in this manner can save the user time and improve the consistency
of wound detection and the measurements that result.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Improve Care for Opioid Use Disorder
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: It is designed to improve treatment retention among veterans receiving medication treatment for opioid use disorder.
Purpose and benefits: The hope is the AI will improve treatment retention, and therefore, patient outcomes such as decreased overdose rates and improved quality of life.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: AI for Monitoring Veterans' Diagnoses
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Providing Timely care to veterans.
Purpose and benefits: This AI tool will ensure timely care for veterans especially when there's a new diagnosis for a chronic condition, and it needs much improved coordination of care between facilities and community care. This will reduce readmissions, hospitalizations and enhance quality of care and life expectancy for veterans. This will save VA in millions of dollars spent in ER care, acute care, readmissions and hospitalizations.
Topic area: Health and Medical
Development stage: Pre-deployment
US federal AI use case: Artificial Intelligence Assisted Procurement Tools (AIAPT)
Agency: Department of Veterans Affairs - OALC: Office of Acquisitions Logistics, and Construction
Problem addressed: The Artificial Intelligence Assisted Procurement Tools initiative is designed to address problems within the procurement processes of VA:
1. Workforce Efficiency: Procurement staff face significant workloads and complexity in managing procurement processes, especially with staff shortages and changing environments
2. Inefficiencies in System Integration: Current procurement systems are often fragmented, leading to a lack of seamless integration between various tools and platforms
3. Workflow Automation: Many procurement tasks are manually intensive, leading to delays, errors, and increased workload for procurement staff
4. Policy Compliance: Ensuring adherence to Federal Acquisition Regulation, Veterans Affairs Acquisition Regulation, and other relevant policies can be complex and error-prone
5. Data Management and Analysis: The vast amount of procurement data available is often underutilized due to challenges in managing, analyzing, and extracting actionable insights
6. Governance and Transparency: Maintaining transparency and accountability in procurement processes is challenging, leading to potential issues in governance and stakeholder trust
7. Scalability and Flexibility: Existing procurement systems may lack the flexibility to adapt to evolving needs and scalability to handle increasing workloads
8. Knowledge Management: Inefficient knowledge sharing and management can hinder the effectiveness of procurement processes
Purpose and benefits: Faster and more efficient procurement of medical supplies and services ensures that healthcare providers have timely access to the resources needed for patient care.
Reduced Operational Costs: Automation of repetitive and administrative tasks reduces the need for manual labor, resulting in significant cost savings.
Minimized Waste and Overhead: Improved forecasting and inventory management prevent over-ordering and reduce waste, further contributing to cost reduction.
Faster Procurement Cycles: Automation and streamlined workflows reduce the time required for procurement processes, enabling faster acquisition of goods and services.
Enhanced Decision-Making: AI-driven insights and predictive analytics provide procurement staff with data-driven recommendations, improving decision-making efficiency and effectiveness.
Reduced Administrative Burden: Automation of routine tasks allows procurement staff to focus on higher-value activities, increasing job satisfaction and reducing burnout.
Enhanced Public Trust and Accountability
Scalability and Future-Proofing: The modular and customizable AI framework ensures that the VA’s procurement systems can scale and adapt to future needs, providing long-term value and sustainability.

By providing these outputs, the AIAPT initiative will significantly enhance the VA’s procurement processes, driving greater efficiencies, improving compliance, and delivering superior services to Veterans.
Topic area: Procurement and Finance Mgmt
Development stage: Pre-deployment
US federal AI use case: Venous Care Pathway Improvement
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Care pathways for venous diseases (e.g. deep vein thrombosis, pulmonary embolism, post thrombotic syndrome, superficial venous insufficiency, phlebolymphedema, and venous leg ulceration) are inconsistent and inefficient, leading to poor clinical outcomes and losing economic value statements for health payers and providers. Impact Health will work directly with VHA employees to standardize care protocols for selected venous diseases and implement a digital platform for Veterans, care providers, and hospital executives to support and view results of the improved protocol.
Purpose and benefits: The digital platform empowers Veterans and providers with tools that include but aren’t limited to: track clinical outcomes, view longitudinal venous care progress, communicate remotely, manage care tasks for Veterans, access educational resources, prioritize Veterans based on status updates, collect research-grade clinical and economic data, and provide analytics of clinical and economic benefit of improved VHA venous pathways compared to the historical standard of care in VHA health systems. Hospital executives will also have access to a dashboard that demonstrates the Veteran population with venous diseases, population-level clinical outcome progress, recruitment statistics, facility economics, and more. Streamlining protocols for diagnosis, stratification, referrals, treatment, and post-treatment care will reduce health worker burden, create economic efficiencies, and significantly improve Veteran health outcomes. Providing a digital health platform that reinforces the protocols will facilitate better provider support for Veterans, empower Veterans to manage their own diseases, and will collect real-world data to validate the benefit of the improved protocol.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Clinical Trial Matching
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The trial matching rate at the VA is very low. Many patients aren't aware of the possible trial opportunities. National Oncology Program has clinical trial coordinator manually reviewing patients' information and trial information to decide which trials are potential matches for the patients that are interested. This process is very time consuming, usually takes over an hour per patient. We intend to use AI to speed up the process and recommend potential trials, so that the trial coordinator is able to help more patients with the same amount of time. The tool will match patients with clinical trials that they are potentially eligible for.
Purpose and benefits: This tool can enhance patient outcomes, save cost, and increase efficiency. Patients are more likely to enroll in clinical trials, the trial coordinator would be able to help more patients with the same amount of time, and clinical trials could receive a higher enrollment rate.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: VASQIP Mortality Calculator
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Tracking Surgical Outcomes: Collecting data on surgical procedures and outcomes, such as complications, morbidity, and mortality rates.

Benchmarking Performance: Comparing surgical outcomes at VA facilities against national standards and best practices to identify areas where performance can be improved.

Quality Improvement Initiatives: Implementing targeted interventions and quality improvement projects based on the analysis of collected data to enhance patient care.

Reporting and Accountability: Providing regular reports on surgical outcomes and quality metrics to promote transparency and accountability within the VA healthcare system.
Purpose and benefits: Increase Veteran safety for surgical procedures. Enhance patient outcomes by rigorously collecting and analyzing surgical data, identifying areas for improvement, and implementing evidence-based practices.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Frailty Risk Analysis
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Define frailty in surgical patients: screen for potential frailty in pre-surgical patients
Purpose and benefits: Alignment of recommended therapies with patient goals. There is a single threshold for a Risk Analysis Index (RAI) score over which severe frailty is considered to exist and that prompts clinicians to have additional discussions of goals of care with Veterans. There is no required action or mandated restriction of care.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Automated AI review for Competitive Procedures
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Provide guidance, while maintaining human in the loop, for various aspects of the reviewing processes where competitive procedures include multiple objective and subjective metrics (with potential application to R & D grants and contracts).  This enables faster processes, unbiased and additional perspectives for competitive review processes.
Purpose and benefits: Provides cost savings, increased efficiency, and process enhancements
Topic area: Science
Development stage: Pre-deployment
US federal AI use case: Categorization and Labelling Administrative Requests
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The categorization and labeling functionality is intended to support functions such as administrative intake requests. This is intended to support use cases such as rapid triage of Information Technology intake requests. This solves the problem of manual data entry.
Purpose and benefits: Increased efficiency.
Topic area: Admin Functions
Development stage: Pilot
US federal AI use case: ML Model for medication prediction
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Pharmacy inventory management
Purpose and benefits: - Removes ambiguity for users by guiding them through eligibility and next steps.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Customer Sentiment
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: Proactively identify drops in customer service as perceived by the customer.
Purpose and benefits: Data assists in the proactive identification of ways to change customer service that can positively impact customer experience with teams.
Topic area: HR
Development stage: Deployed
US federal AI use case: Leveraging Acoustic-Linguistic Analytics and Social Determinants to Enhance Suicide Prevention Efforts in Veterans Crisis Line Interventions
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: This project leverages machine learning (ML) and data analytics to enhance suicide prevention efforts by improving risk prediction, crisis intervention effectiveness, and understanding of social and environmental factors influencing Veteran suicide risk. It will develop a data processing pipeline to extract and analyze VCL call data directly from call audio recordings, enabling multimodal ML models that integrate linguistic, acoustic, and contextual features to identify imminent suicide risk. Additionally, it will evaluate crisis intervention effectiveness and link VCL call data with external datasets to assess environmental stressors such as noise pollution. Finally, models will be validated on a larger dataset within the Veterans Affairs (VA) Cloud to ensure scalability and internally-sustainable integration into VCL workflows, delivering artificial intelligence (AI)-driven decision-support tools and actionable policy insights to improve crisis response strategies.
Purpose and benefits: Improve VCL protocols and procedures; improve suicide prevention efforts; increase efficiency; enhance patient outcomes.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Butterfly iQ3 Ultrasound System
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The Butterfly iQ3 Ultrasound System is indicated for use by qualified and trained healthcare professionals to enable diagnostic ultrasound imaging and measurement of anatomical structures and fluids of adult and pediatric patients for the following clinical applications: Peripheral Vessel (including carotid, deep vein thrombosis and arterial studies), Small Organs (including thyroid, scrotum and breast), Cardiac, Abdominal, Lung, Procedural Guidance, Urology, Fetal/Obstetric, Gynecological, Musculoskeletal (conventional), Musculoskeletal (superficial) and Ophthalmic.
Purpose and benefits: Accelerates ultrasound workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Paid & Due Auto Calculation
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The Paid & Due Audit calculation is currently a manual process that is both complicated and time consuming. However, the use of Agentic AI will allow VA to automate portions of the data collection and audit calculation process, accelerating the results of each Paid & Due Audit and lessening the impact of manual errors.
Purpose and benefits: Accelerated data collection, increased accuracy, and quicker results for each Paid & Due Audit calculation.
Topic area: Benefits Processing
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: VA FSC AI ChatHelper
Agency: Department of Veterans Affairs - OM: Office of Management
Problem addressed: Customer Service Representatives (CSR’s) can ask their VA Financial Services Center (FSC) AI ChatHelper questions and receive policy and standards-based answers (e.g., Top Resolution Scripts, Historical Case Notes or Resolutions, Reference Links, Text, or Visual instructions) to converse with Customers through assistance from their VA FSC AI ChatHelper until achieving a final satisfactory resolution per the Customer and being able to provide feedback on the relevance and accuracy of VA FSC ChatHelper responses. This solves the problem of a standards-based knowledge source for FSC's help desk CSRs.
Purpose and benefits: Increasing help ticket capacity for additional volume, increased efficiency and cost avoidance
Topic area: Procurement and Finance Mgmt
Development stage: Pilot
US federal AI use case: CareView Patient Safety System
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: It monitors patient movement to watch out for fall risks.
Purpose and benefits: Enhance patient outcomes and safety
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: ValidateNow
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: AI is used to help inventory managers and purchasing agents locate the right products from the 
Medical/Surgical Prime Vendor (MSPV) catalog that can be substituted for recent Government Purchase Card (GPC) purchases. It enables efficient management of expenses and ensures purchase correctness by surfacing untriaged items and comparing them to MSPV contracted items.
Purpose and benefits: Reduced GPC spend, increased MSPV utilization, and overall increased compliance with Executive Order mandates to curb GPC spend.
Topic area: Procurement and Finance Mgmt
Development stage: Deployed
US federal AI use case: Screen for Esophageal Adenocarcinoma
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Veterans disproportionately have many of the important risk factors for esophageal adenocarcinoma (EAC), and research has demonstrated that Veterans are a substantial gap in the prevention of EAC. Healthcare providers can utilize Kettles Esophageal and Cardia Adenocarcinoma prediction tool (K-ECAN) to guide decision-making and identify potential patients who should be offered screening for EAC.
Purpose and benefits: If EAC is identified at the earliest stage (intramucosal cancer without metastases), the 5-year survival with surgery is greater than 85%, and at least as good with endoscopic therapy alone. Implementation of such an intervention would bridge the gap between population-health screenings and personalized management in a manner that would minimize the impact on payer budget and resources. Since individuals are more commonly up to date for colorectal cancer screening (for instance, with colonoscopy), it is particularly suitable to harness the missed opportunity of EAC screening at the time of screening for colorectal cancer. Also, when an EAC screening with upper endoscopy is performed simultaneously with colonoscopy, it is much less expensive. This project will also serve as a roadmap for how such precision approaches to screening can be applied to other rare cancers.
Topic area: Health and Medical
Development stage: Pilot
Risk category: High-impact
US federal AI use case: Veteran Experience Office Retention/Trust Models in Customer Experience Insights
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The models reside in Customer Experience Insights. The inputs are CDW VISTA data and CX Insights data. The outputs are predictions of veteran trust and retention given veteran experience inputs. The purpose of the models is to predict whether a veteran would say they trust the VA (Trust) and whether they would continue to receive care with VA (Retention) based on their experiences with VA. The intended use is to understand drivers of these important metrics. The problem to be solved is to programmatically identify drivers of veteran experience to inform methods of improving experience metrics such as retention and trust.
Purpose and benefits: Improved veteran experience, improved veteran trust, improved veteran retention.
Topic area: Other
Development stage: Deployed
US federal AI use case: Augmented Reality and Virtual Museum
Agency: Department of Veterans Affairs - OALC: Office of Acquisitions Logistics, and Construction
Problem addressed: AI will enable visitors to submit queries regarding the VA's history and be presented the most suitable information within the VA's curated public domain historical information database.
Purpose and benefits: Utilization of AI will enable the VA to present the most relevant information to the general public with the easiest access, eliminating the need for them to otherwise search the VA Virtual Museum's extensive catalog of publicly available information. It will provide Veterans, employees and the public with accurate information that illustrates the VA's service to veterans.
Topic area: Other
Development stage: Pre-deployment
US federal AI use case: VetsEZ Middleware Development
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The HDM middleware environment supports large-scale, secure health data transport across VA systems, but much of its underlying codebase is legacy (e.g., MUMPS, Java, .NET Framework) and complex, with inconsistent documentation and a heavy reliance on senior SMEs.

This leads to: Ongoing technical debt as well-functioning but aging middleware components require careful, phased modernization; Longer onboarding times when new developers need to interpret complex, high-value legacy code without comprehensive documentation; Resource dependencies where mid-tier developers require more direct SME involvement for certain modernization and refactoring tasks; Variation in code patterns that can affect consistency in security, performance, and maintainability across platforms; Slower adoption of modern architectures such as containerized microservices and FHIR integrations.

How AI Solves It: Explain legacy code in plain language, creating complete documentation for knowledge preservation and onboarding; Refactor code for maintainability, performance, and security, reducing technical debt; Generate standardized, efficient middleware code aligned with VA modernization goals; Produce AI-augmented unit tests to detect defects earlier (“shift-left” testing) and increase coverage; All outputs will still undergo human review, VA security scanning, and governance to ensure compliance with Federal Information Security Management Act (FISMA) High standards and VA TRM policy.
Purpose and benefits: For the VA’s Mission: Faster code modernization – AI-assisted refactoring and generation will help transition middleware components from older platforms (MUMPS, Java, .NET Framework) to secure, containerized microservices. 
Improved developer efficiency – By automating repetitive coding & documentation tasks, developers can focus more on high-value modernization work and less on manual rework. 
Knowledge preservation – AI-generated code explanations and documentation reduce the risk of key-person dependency and improve continuity across teams.
Higher code quality  – AI-augmented unit tests and standardized patterns will strengthen maintainability and alignment with FISMA High requirements.
Accelerated delivery cycles – With AI enabling mid-tier developers to work more independently, releases can move through the DevSecOps pipeline faster while maintaining quality and compliance.
For the General Public / Veterans:
Improved reliability of VA systems – Modernized, better-tested middleware helps ensure health and benefits data flows securely and consistently.
Faster implementation of new services – Reduced development cycle times allow Veterans to benefit sooner from new integrations, such as Fast Healthcare Interoperability Resources (FHIR)-based interoperability with community care providers.
Sustained continuity of operations – Documentation and knowledge capture ensure that mission-critical systems can be maintained and improved even as staff transitions occur.
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: iFAMS CSR Assistant
Agency: Department of Veterans Affairs - OM: Office of Management
Problem addressed: The pilot deployment will simplify retrieval of knowledge content to resolve user support requests and enable the customer support representative (CSR) to confirm accuracy of steps presented to improve knowledge content. It will be internal facing in pilot to assess usability, efficiency, and correctness with CSR representatives.
Purpose and benefits: Improved customer satisfaction, cost efficiency, consistency of communication, reduced human error.
Topic area: Procurement and Finance Mgmt
Development stage: Pre-deployment
US federal AI use case: EDU Synthetic Test Data POC
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: To generate mock data which allows VBA education service to leverage non-prod, non-pii environments for more robust testing.
Purpose and benefits: Faster, automated testing is a key outcome of being able to generate life-like yet identity-obscured data.
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: Pyramid Analytics Generative AI Options
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: Pyramid Analytics is a scalable business intelligence application/platform that uses VA data sources for building and maintaining data reporting content. The application/platform has several tools, including dashboard and report creation tools and has 57,000+registered users at VA.
Purpose and benefits: Increased efficiency in finding information faster
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: AICES
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: 1. Reduce the backlog and processing times, minimize unnecessary in-person exams, and address workflow inefficiencies.
2. Reduce the burden of travel on veterans and expedite the time required for claims processing. 

During the period of performance, this effort will demonstrate the effectiveness of the proposed solution to develop Disability Benefits Questionnaire (DBQs) through Acceptable Clinical Evidence (ACE).
Purpose and benefits: This initiative aims to:
1. Reduce the backlog and processing times by more efficiently using Acceptable Clinical Evidence (ACE), minimizing unnecessary in-person exams and addressing workflow inefficiencies.
2. Reduce VA costs due to reduced in-person exams.
3. Improve the Veteran experience by reducing the burden of travel on veterans and expediting the time required for claims processing.
Topic area: Benefits Processing
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: MetricSage
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: We intend to build a machine-learning model to optimize cost for the Claim Evidence API within VBMS. The input data will be system metrics collected by Dynatrace, such as CPU and memory usage, and the output will be projected usage and optimal sizing of resources based on that usage. VA Project Managers and Benefits Integrated Platform engineers will use this system to determine the resources to provision and the expected cost of those resources. This use case will be used to anticipate future cost in compute based on claim workload.
Purpose and benefits: proper forecasting will allows us to right size our compute resources.
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: Federal EHR End User Peer Support Chatbot
Agency: Department of Veterans Affairs - OEHRM: Office of Electronic Health Record Modernization
Problem addressed: Federal EHR end user support meets peak in the first three months after roll-out. The current model of super user support is not sustainable when EHRM-IO restarts deployment with an accelerated schedule (i.e., 13 sites in 2026). This tool will alleviate the burden on super users by answering the basic, frequently asked questions by a Retrieval-Augmented Generation (RAG) over LLM model, allowing the super users to address the more complex questions.
Purpose and benefits: This use case will lead to increased efficiency, staff satisfaction, enhanced patient outcomes, and help successfully accomplish the VA secretary's strategic goal of Federal EHR deployment
Topic area: Service Delivery
Development stage: Pre-deployment
US federal AI use case: VAHC CRM- Veteran Self-Service
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The Clinical Contact Center (CCC) receives 45 million calls per year. At this time the CCC has a queue abandonment rate of 9.4% which is significantly higher than the national average for contact centers. AI reduce the number of abandoned calls.
Purpose and benefits: The CCC receives 45 million calls per year. At this time the CCC has a queue abandonment rate of 9.4% which is significantly higher than the national average for contact centers. AI will allow Veterans to get answers to commonly asked questions and access basic services which will allow Medical Service Assistants (MSAs) to answer more complex calls, reducing hold times for Veterans and reducing the number of abandoned calls.
Topic area: Admin Functions
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Healing in Your Hands Wellness Tools for VA Staff and Veterans
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: This AI wellness tool is designed to close a real gap in the VA: the lack of quick, easy-to-access emotional support for both staff and Veterans in the moments they need it most.

Right now, if a nurse finishes a high-stress call or a Veteran walks into the clinic feeling anxious, there’s no immediate, built-in way to help them calm down, refocus, or reset before moving forward. Most wellness efforts happen after the fact—or are generic resources that people have to go looking for.

This project changes that by putting wellness directly in their hands—through a simple QR code they can scan anywhere in the building. From there, they can instantly access calming tools like breathing exercises, affirmations, or therapeutic coloring pages—customized for staff or Veterans—without logging in, downloading an app, or navigating a complex system.

It solves the problem of accessibility, timing, and relevance—giving people the right kind of support exactly when and where they need it.
Purpose and benefits: To develop a set of interactive, AI-supported wellness tools that can be deployed across VA facilities and remotely, enhancing daily emotional health, reducing burnout, and supporting mental wellness for both staff and veteran populations.
Topic area: Health and Medical
Development stage: Pre-deployment
US federal AI use case: VA Health Connect (VAHC) Customer Relationship Management (CRM) - contact quality analysis
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: There are very few tools available to evaluate the content of a Clinical Contact Center (CCC) Contact to provide insight into the purpose, tenor of the call, satisfaction of the Veteran, and identify Medical Support Assistant (MSA) training opportunities. AI will provide a window into the overall quality of the call based on the purpose, content, and resolution of the contact.
Purpose and benefits: Improved insight into the quality of cases received by the CCC to identify training opportunities, trends, identify opportunities to provide Veteran self-service options.
Topic area: Admin Functions
Development stage: Pre-deployment
US federal AI use case: Evidence, Policy, and Implementation Center (EPIC) QUERI
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Provider burnout due to medical documentation burden, which can put Veteran care at risk if unaddressed.
Purpose and benefits: Increased efficiency.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: VBA Mail Management Services (MMS) - Modification
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: We are shifting data capture from back-office processing to the point of first contact. The system validates VA forms in front of the user interactively as it is being submitted, allowing the submitter to verify and correct errors immediately (reduces churn). This will help with claims modernization.
Purpose and benefits: To prevent claims processing inefficiencies in data quality at intake.
Topic area: Benefits Processing
Development stage: Pre-deployment
US federal AI use case: PowerScribe One
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: It enhances existing radiology dictation and report creation software by providing AI findings and narrative text that help automate and augment reporting. Machine learning and advanced language understanding technologies derive meaning from the data to drive workflows, meaning less work for the radiologist and more consumable, meaningful reports to inform care decisions.
Purpose and benefits: It increases the radiologists' efficiency, automates report writing, and enhances patient care decisions.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Integration of Provar Manager with VA GPT
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: Streamline the creation of test cases. This approach saves time, reduces manual effort, and ensures that testing is both efficient and aligned with project's goals.
Purpose and benefits: Seamless testing of Customer Relationship Management (CRM) applications developed in Salesforce that support Department of Veteran Affairs services. Reducing time to deliver and ensuring accurate match of the requirements vs deliverables.
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: BillieGPT POC
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: It will exist to assist School employees (School certifying officials) in general use, policy, and procedures for handling Veterans cases from the school's perspective. Gives info directly to school officials rather than having them call in to the VA call centers for assistance.
Purpose and benefits: Better outcomes for student veterans, increased efficiency
Topic area: Benefits Processing
Development stage: Pre-deployment
US federal AI use case: Community Care Clinical Documents
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Thousands of Veterans receive care in the community in both unscheduled urgent/acute care settings and scheduled care settings. Following these encounters, VA must receive clinical documentation describing the encounter and address follow-up care needs. The current process for this is manual, inefficient, and not always effective at timely documentation retrieval. This results in delayed care for Veterans and duplication of services.
Purpose and benefits: Solving this problem will improve care quality for Veterans, decrease administrative burden on clinicians, automate manual processes, and improve workforce efficiency, resulting in decreased burnout and overtime expenditures.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: ECC Automated Knowledge Management
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: Currently, teams manually review and update Knowledge Articles, often without clear prioritization. This leads to rework, inefficiencies, and missed opportunities to align knowledge with real-time service changes. An AI-driven approach will streamline this process and ensure knowledge is kept current and relevant.
Purpose and benefits: This initiative is expected to improve efficiency by 20% in the Minimum Viable Product (MVP), and grow as the agent creates and modifies knowledge.
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: Summarization of Clinical Data
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: Give a provider a summarized status of the patient and what has happened to the patient since they last saw the Veteran.
Purpose and benefits: Decreased provider burden and increased time the provider can dedicate to the Veteran during the encounter through increased efficiency.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: GE Omni Legend
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The Omni Legend positron emission tomography (PET)/computed tomography scan (CT) system is intended for CT attenuation corrected, anatomically localized PET imaging of the distribution of positron-emitting radiopharmaceuticals. It is intended to develop an image of the whole body, head, heart, brain, lung, breast, bone, gastrointestinal and lymphatic systems, and other organs. The system is also intended for stand-alone, diagnostic CT imaging.
Purpose and benefits: Accelerates imaging workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Medsafely
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Reduce the length of time it takes to perform medications reconciliation.
Purpose and benefits: - Save cost and time - with just 3 pharmacists using the product, net savings are $5,388.00.
- Increase accuracy, safety, and employee satisfaction.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Knowtex Ambient Scribe
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: This solution intends to reduce clinician burnout and improve documentation quality.
Purpose and benefits: Reduced clinician burnout, increased efficiency, improved documentation quality
Topic area: Health and Medical
Development stage: Pilot
Risk category: High-impact
US federal AI use case: Secure Access Service Edge (SASE)
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The AI is intended to identify, prevent, and mitigate risks from unauthorized data access, exfiltration, and misuse of sensitive information, including PHI/PII in cloud applications and network traffic. It addresses gaps in visibility, compliance enforcement, and threat detection across a hybrid work environment.
Purpose and benefits: - Improved data security by automatically detecting and alerting/blocking risky or non-compliant data transfers in real time. 
- Operational efficiency by automating policy enforcement and reducing manual review workload.
- Enhance compliance with federal mandates by monitoring PHI/PII across all access points, thereby maintaining trust with Veterans and the public through stronger protection of sensitive information.
Topic area: Cybersecurity
Development stage: Pilot
Risk category: High-impact
US federal AI use case: AI + Digital Process Automation (DPA) Business Process Flow Improvement Solution for Contract Closeout Modernization – Pilot Project
Agency: Department of Veterans Affairs - OALC: Office of Acquisitions Logistics, and Construction
Problem addressed: The AI and Digital Process Automation (DPA) solution pilot for the VA's Strategic Acquisition Center aims to modernize the manual and labor-intensive federal acquisition contract closeout process by automating repetitive tasks, enhancing accuracy, ensuring regulatory compliance, and improving oversight. By integrating AI-driven financial reviews and real-time data analytics, the solution aims to reduce errors, shorten closeout timeframes, and optimize resource allocation, ultimately creating a more efficient, accurate, and compliant process in line with Federal Acquisition Regulation (FAR), VA Acquisition Regulation (VAAR), and VA Financial Policy.
Purpose and benefits: The AI and Digital Process Automation (DPA) solution for the VA’s Strategic Acquisition Center will enhance efficiency by automating repetitive tasks, thereby reducing contract closeout times and minimizing errors. This will ensure regulatory compliance with FAR and VAAR, provide cost savings through optimized resource allocation, and improve oversight and transparency. The streamlined process will reduce administrative backlogs and ensure better use of public funds, ultimately supporting the VA's mission by enabling more efficient service delivery and financial management, benefiting both veterans and taxpayers.
Topic area: Procurement and Finance Mgmt
Development stage: Pre-deployment
US federal AI use case: AI Incident Management
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The proposed AI system, referred to as the AI Incident Management (AIM), is designed to aid in faster problem determination and remediation during High Priority (HPI) and Critical Priority (CPI)  Incidents impacting the performance or availability of critical systems.
Purpose and benefits: By leveraging historical data, real-time performance monitoring, and advanced machine learning models, the system will identify potential causes and suggest remediation actions in real time, significantly reducing downtime and improving system reliability and resiliency.
Topic area: IT
Development stage: Pilot
US federal AI use case: Custom GPT for Network Operations and Automation (Wide Area Network)
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: This solution will be able to:

1.	Information Retrieval: Query our router database and backup configurations to answer questions about network topology, device status, and configuration details
2.	Configuration Generation: Assist in building network device configurations based on our standards and requirements
3.	Troubleshooting Support: Help diagnose network outages by analyzing device data and providing guided troubleshooting steps
4.	Read-Only Device Access: Eventually integrate with our network infrastructure to gather real-time information from devices in a secure, read-only manner

It will solve the problem of reducing the time required to resolve network issues, human errors in configuration, availability of network support.
Purpose and benefits: Benefits:
•	Reduced mean time to resolution for network issues
•	Standardized configuration generation reducing human error
•	Enhanced knowledge sharing across the WAN team
•	24/7 availability for network operations support
•	Improved training resource for new team members
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: Predict Septic Shock in ICU Patients
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Reduce ICU mortality and morbidity related to septic shock and respiratory failure. Provide nurses and physicians with the opportunity to intervene earlier in the course of these high mortality, high morbidity conditions.
Purpose and benefits: Improved patient outcomes through reductions in mortality and morbidity. Costs savings related to lower length of stay associated with these conditions.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Romexis Dental Imaging Software
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Automates process and speeds up dental x-ray reads.
Purpose and benefits: Improves workflow, enhances dental implant planning, and automates tasks
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact