Leveraging Retrieval Augmented Generation (RAG) AI to Power Outcome-Based Contracting
General Services Administration
Overview
- Development stage
- In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
- High-impact designation
- Not reported
- Impact justification
- Not reported
- Start date
- Not reported
- Withheld from public reporting
- Not reported
Mission
- Topic area
- Procurement and Financial Management
- Operational functions
- Search and knowledge retrieval Derived by keyword rules; see methodology
Problem the AI is intended to solve
The AI is intended to solve the problem of federal acquisition teams struggling to write clear, concise, outcome-based requirements, which often leads to incomplete or undesirable contract outcomes and higher costs. This experimental effort aims to determine if an AI-powered assistant can provide coaching and feedback on drafting such requirements with accuracy and reliability comparable to experienced human facilitators, thereby reducing reliance on limited Subject Matter Expert availability.
Expected benefits
Not reported
System outputs
Not reported
Technology
- AI classification
- Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
- System name(s)
- Not reported
- Custom-developed code
- Not reported
- Public source code
- Not reported
Sourcing
- How it was built
- Not reported
- 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
- Not reported
- Privacy Impact Assessment
- Not reported
- Authorization to Operate
- Not reported
- Demographic features
- Not reported
- 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.
Potential impacts and how they were identified
Not reported