HHS · no agency ID · record R0599

Structuring and Validating Completeness of Case Data Information

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: Presumed high-impact, determined notSource: b) Presumed high-impact, but determined not high impact
Impact justification: The use of AI is narrowly focused on extracting key data points from scanned notices. The outputs do not serve as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the 6 cases outlined in M-25-21, page 19.
Start date: 2024-12 (month precision)Source: Dec-24
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Government Benefits Processing
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

How can referrals from the Department of Homeland Security (DHS) be more quickly reviewed for critical pieces of information about their parents and the reason for separation? Since November 2024, when a minor is separated from their parent or legal guardian, the U.S. Customs and Border Protection (CBP) within DHS is required to send certain pieces of information about the parent/legal guardian in accordance with the Ms L vs ICE settlement. CBP send this information in a block of free text and sometimes do not include the required information. Historically, ACF's Office of Refugee Resettlement (ORR)’s tracking of required information has been done manually and inconsistently.

Expected benefits

More easily searchable and accurate data on family separations Quicker validation of CBP compliance in essential data sharing for separated families, enabling faster follow-up as needed to receive any missing data points

System outputs

Structured data asset of the critical data points needed about a separation case. AI is used to conduct initial parsing of the data provided by CBP and highlight whether or not the required fields from the Ms L vs. ICE settlement are included and can therefore be updated into the child's profile in ORR's data system. ORR's Intakes Team does final review and in cases where data appears to be missing, the ORR Intakes Team reaches back out to CBP for that information.

Technology

AI classification: Agentic AISource: Agentic AI: AI systems that perform tasks or make decisions autonomously with minimal human intervention.
System name(s): ACF Horizon
Custom-developed code: Yes
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
Vendors (standardized): Palantir

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

Data and privacy

Involves PII: Yes
Privacy Impact Assessment: www.hhs.gov ↗
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: No training or fine-tuning; we are using secure commercially available LLMs.
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