Contact and place of performance
Monika Masei
Beltsville, MD
USA
1. Purpose The Food Safety and Inspection Service (FSIS) is seeking information on AI-powered predictive analytics solutions to enhance its ability to prioritize inspections, allocate resources, and oversee food safety operations using inspection data, large language models (LLMs), and external risk indicators. This RFI aims to gather insights from industry experts and technology providers to understand the current s...
View more4. Scope of Interest
Respondents should address as many of the following areas as possible. You may include additional information beyond what is requested if it is material to the RFI.
FSIS is not asking for the development of AI software from scratch. The ideal solution will take a vendor's existing commercial software platform, preferably on the Azure Government Cloud, and have data path, enhancements and customization that can be done to the existing software platform.
Risk Scoring & Analytics:
- Describe capabilities for generating dynamic risk scores using structured and unstructured data.
- Explain integration of external data sources (e.g., weather, illness trends, recall history).
- Provide details on transparency features (e.g., explainable AI, confidence indicators).
Advanced Analytical Features:
- Sentiment/contextual analysis on inspection narratives and complaints.
- Pattern detection for recurring issues across establishments.
- Predictive resource planning and scenario simulation.
User Interfaces & Tools:
- Role-specific dashboards (supervisory, analytical, operational).
- Conversational AI assistants for natural language queries.
- Mobile and field applications for inspectors.
Governance & Security:
- Audit logs, user permissions, and feedback loops.
- Data security measures (encryption, access control, compliance).
Cost Estimates:
- Provide a detailed breakdown of costs (development, deployment, maintenance).
- Discuss ROI and cost-saving benefits.
Implementation Timeline:
- Outline proposed timeline for deployment, including milestones for assessment, testing, and full implementation.
Training & Support:
- Describe training programs for FSIS personnel.
- Include ongoing support and technical assistance.
Scalability & Integration:
- Explain scalability for varying volumes of data and establishments.
- Discuss integration with FSIS systems and Azure Government Cloud (preferred environment).
5. Requested Information
Respondents are encouraged to provide:
- Detailed information on proposed predictive analytics solutions.
- Case studies and past performance.
- Cost models or pricing structures.
- Government FTE time estimates for support and feedback.
- Recommendations for Key Performance Indicators.
- Potential implementation barriers.
6. Submission Instructions
Responses should be submitted electronically in PDF format to:
[email protected] and [email protected]
Due Date: March 14, 2026
Email Subject: RFI Number FSIS-FY26-0003 – PHIS Predictive Analytics
Include:
- Company name and point of contact.
- Executive summary (1 page max).
- Detailed responses (10 pages max).
- Optional: White papers, case studies, product brochures.
- Relevant experience.
7. Disclaimer
This RFI is for planning purposes only and does not constitute a solicitation or obligation. No compensation will be provided for responses.
The United States Department of Agriculture (USDA) Food Safety and Inspection Service (FSIS) issued this sources sought notice to identify AI-powered predictive analytics solutions aimed at enhancing food safety operations. The agency intends to modernize its current reliance on numeric risk scores and manual analysis by implementing advanced technologies that prioritize inspections, allocate resources, and integrate large language models with external risk indicators. Primary objectives include establishing AI-driven risk scoring, predictive resource planning through scenario simulation, and the development of role-specific dashboards or conversational AI tools. FSIS prefers existing commercial software platforms capable of customization and enhancement within the Azure Government Cloud environment.
This market research effort, identified under solicitation number FSIS-FY26-0003, focuses on capabilities including sentiment analysis of inspection narratives, pattern detection for recurring safety issues, and the integration of external data such as weather and illness trends. The requirement is classified under NAICS 541511 for Custom Computer Programming Services and PSC DA10 for IT and Telecom - Business Application/Application Development Software as a Service. While the agency is seeking detailed cost estimates, implementation timelines, and training programs, there is no set-aside designated for this requirement at this stage.
Responses to this notice are due by March 14, 2026. Submissions must be sent electronically to the primary point of contact, Monika Masei, and should include an executive summary and a detailed response addressing risk scoring, governance, and scalability. The solicitation documentation includes two attachments: a Request for Information PDF and a Statement of Objectives for PHIS AI. All performance is slated to take place in Beltsville, Maryland.
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Scoped analysis and attachments—go beyond the summary when you need detail from the solicitation package.