Request for Information (RFI) - Artificial Intelligence for Image Adjudication
Overview
Buyer
Place of Performance
NAICS
PSC
Set Aside
Original Source
Timeline
Qualification Details
Fit reasons
- NAICS alignment with historical contract wins in similar service areas.
- Scope strongly matches core technical capabilities and delivery model.
Risks
- Past performance thresholds may require one additional teaming partner.
- Potential clarification needed on staffing minimums before bid/no-bid.
Next steps
Validate eligibility requirements, assign capture owner, and schedule partner outreach to confirm teaming strategy before submission planning.
Quick Summary
The U.S. Customs and Border Protection (CBP), under the Department of Homeland Security, has issued a Request for Information (RFI) for Artificial Intelligence (AI) and Machine Learning (ML) solutions to enhance Non-Intrusive Inspection (NII) image adjudication. This RFI aims to improve the efficiency and effectiveness of processing high volumes of X-ray images from large-scale scanning systems for privately owned vehicles (POVs) and cargo. Responses are due by May 30, 2026.
Purpose & Scope
This RFI is for market research and planning purposes only, not a commitment to procure. CBP seeks information on how to best develop and implement modular AI/ML models that can operate on large-scale NII imagery and metadata (with an emphasis on WCO UFF). Solutions should be adaptable to CBP operational needs and integrate as drop-in components within existing CBP architectures, avoiding new proprietary data platforms.
Information Requested
CBP is interested in vendor capabilities regarding:
- Algorithm Products: Developed or developing solutions for anomaly detection, manifest/commodity verification, conveyance modification, and contraband detection, including performance metrics.
- Development Approach: Models/architectures used, limitations, and generalization capabilities.
- Technical Capabilities: Image segmentation, supported image formats (including UFF), technical dependencies, system requirements, and potential incompatibilities.
- Deployment & Scaling: Typical architecture, training, deployment, and scaling strategies.
- Field Experience: Operational settings, performance results (detection and false alarm rates).
- Training & Verification: Methods and requirements for training, verification, and deployment, including data handling.
- Integration: Algorithm system integration approach, APIs, and integration with CBP viewers.
- Model Evolution: How AI/ML models evolve through continuous training and performance monitoring.
- Specific Applications: AI/ML for contraband/condition detection and supported LS-NII modalities (POVs, cargo, sea containers, rail cargo).
- Risk & Cost Management: Strategies to minimize technical risk and life cycle costs.
- Standardization & Interoperability: Industry's role in standardizing technology and maximizing interoperability.
- Teaming: Subcontracting/teaming arrangements, including small/disadvantaged businesses, and collaborative activities for open architecture solutions.
Submission Details
- Questions Due: May 15, 2026, by 12:00 PM EST.
- Responses Due: May 30, 2026, by 12:00 PM EST.
- Submission Method: Electronic submissions via email. Files larger than 10 MB must be broken down.
- Page Limit: Fifteen (15) pages, excluding specific front/back matter.
Contract & Timeline
- Type: Sources Sought / Request for Information (RFI)
- Set-Aside: None specified
- Response Due: May 30, 2026
- Published: May 4, 2026
Additional Notes
This RFI is for Government Market Research only and does not constitute a commitment to procure. All costs associated with responding are at the respondent's expense. Information provided is subject to change and is not binding on the Government.