HHS · no agency ID · record R0619

Grant management support: structuring information in applications

Department of Health and Human Services · HHS/ACF

Overview

Development stage: DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2025-07 (month precision)Source: Jul-25
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Other
Operational functions: Document processing and extraction, Summarization Derived by keyword rules; see methodology

Problem the AI is intended to solve

How can ACF staff more efficiently review grant applications that have non-standardized formats? Grant applications for ACF-funded programs can come in different formats, even when a standard set of questions or template is provided. ACF staff evaluating applications look for explanation and details to assess against pre-established evaluation criteria. Going back-and-forth across an application to find the relevant explanation can be time intensive, especially for applications that include multiple documents spanning 50+ pages.

Expected benefits

Increased efficiency of review so that more time can be spent on grant application analysis and evaluation

System outputs

Varies, depending on the program office. Outputs generally involve summarizing information, extracting key information into a specific format, flagging potential gaps or inconsistencies, and providing citations / page numbers to support follow-up review and validation. In all cases, AI is only used to support review of grant applications but does not make any final determinations for awards.

Technology

AI classification: Agentic AISource: Agentic AI: AI systems that perform tasks or make decisions autonomously with minimal human intervention.
System name(s): ACF Upstream, ACF Credal
Custom-developed code: No
Public source code: Not reported

Sourcing

How it was built: Contract and in-houseSource: c) Developed with both contracting and in-house resources
Vendor (as reported): Palantir, Credal
Vendors (standardized): PalantirCredal

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: www.hhs.gov ↗
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: RAG implementation using commercially-available LLMs and user-provided grant applications
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported