HHS · no agency ID · record R0796

SAM.gov RFI Comment Analysis POC

Department of Health and Human Services · HHS/CMS/OIT

Overview

Development stage: PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2025-08 (month precision)Source: Aug-25
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Information Technology
Operational functions: Procurement and acquisition Derived by keyword rules; see methodology

Problem the AI is intended to solve

The SAM.gov RFI Comment Analysis POC solves the problem that CMS procurement staff currently must manually review and score vendor responses to Requests for Information (RFI) posted on SAM.gov, which is time-intensive, especially when there are many questions and many vendors responding.

Expected benefits

The RFI Comment Analysis POC will enable CMS teams to systematically evaluate vendor responses using AI-powered analysis, improving the efficiency of assessments.

System outputs

The AI system outputs vendor scoring and ranking reports

Technology

AI classification: Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.
System name(s): CEDAR
Custom-developed code: Yes
Public source code: Not reported

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

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: Not reported
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: Not reported
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