SIRCE II

Request for Information (RFI)

This RFI is issued by the U.S. Food and Drug Administration (FDA) for market research purposes to identify qualified vendors capable of supporting the Systems for Inspection & Imports, Recalls Compliance, and Enforcement (SIRCE) II initiative. The FDA is seeking information on industry capabilities, capacity, and innovative approaches for delivering comprehensive IT modernization and support services.

This RFI seeks input on draft SOW Task Areas and Technology Stack. Vendors are asked to provide information and examples related to:

• Implementing modern technology and retiring legacy systems.

• Automated system provisioning, deployments, and routine task automation.

• Minimizing failure rates of mission-critical systems (logging, availability, redundancy).

• Right-sizing system resources for application performance.

• Implementing and managing hybrid cloud environments (internal and external).

• Meeting security standards, risk mitigation, and system patching.

• Onboarding new team members to custom/legacy technologies.

• Maintaining Operations and Maintenance (O&M) procedures.

• Responding to concurrent task orders within 10 business days.

• Staffing up to 100 resources.

• Artificial Intelligence (AI) integration and innovation in software development.

• Program management methodologies, KPIs, and risk management.

• The SIRCE II effort is anticipated to have a five (5) year period of performance.

• The estimated value is up to $400M.

• Task orders are estimated to be 2-4 per year.

• Awardees will have fifteen (15) business days to respond to each task order.

• Awardees will be responsible for staffing efforts within fifteen (15) business days of award.

• This RFI is for market research only and does not constitute a solicitation for proposals.

• No contract will be awarded based on responses to this RFI.

• Interested companies must submit a Capability Statement (limited to five (5) pages).

• Responses are due by March 6, 2026, at 12pm Eastern Time.

• Submit responses via email to Noah.Padilla@fda.hhs.gov.

• The FDA may contact respondents for additional information or demonstrations.

• Not specified in this RFI, but companies should be prepared to register on SAM.gov for any future contract.

• The FDA is particularly interested in vendors with proven experience in large-scale IT modernization, hybrid cloud environments, AI/ML, DevSecOps, and rapid scaling.

• The RFI aims to gather industry feedback on solicitation approach, evaluation criteria, and technical requirements, as well as understand pricing approaches and identify innovation opportunities.

Form / Attachment / Pricing Sheet

This document, "Attachment 2 - Representative Technology Stack," details the technology infrastructure, methodologies, and tools currently in use or proposed for the Systems for Inspection & Imports, Recalls Compliance, and Enforcement (SIRCE) II opportunity. It serves to inform potential bidders about the existing or desired technical environment.

• Infrastructure: Includes on-premise, AWS EC2, Azure, and Google Cloud Platforms, along with specific servers and operating systems like Oracle HTTP Server, Oracle Linux, RedHat Linux, and Windows.
• Software Development Methodology: Outlines Agile development and DevSecOps practices, utilizing tools such as Jenkins, Git/GitLab, Docker, and Kubernetes.
• Artificial Intelligence: Mentions Amazon SageMaker, Bedrock, Azure AI, and Google Vertex AI for AI/ML projects, including support for frontier models and MLOps.
• Emerging Design Patterns/Protocols: Lists RAG, MCP, A2A, and customizable LLMs.
• Data: Specifies Databricks on AWS.
• Application Monitoring: Includes AWS CloudWatch, Grafana, and SolarWinds.
• Databases: Lists MS SQL, Oracle, PostgreSQL, MariaDB, Databricks, AWS S3, and SQLite.
• Automated Testing Tools: Includes Selenium, Katalon Studio, Appium, and JMeter.
• Accessibility & 508 Compliance Testing: Mentions AMP and NVDA.
• Other Technologies: A broad list including Java, J2EE, .NET, Python, AngularJS, REST/JSON, SOAP, and various Oracle technologies.

This attachment is crucial for bidders to understand the technical landscape of the SIRCE II system. It helps in assessing their capability to integrate with, maintain, or enhance the existing technology stack. Bidders should consider how their proposed solutions align with or can be adapted to this representative technology stack when preparing their proposals.

Statement of Work (SOW) / Performance Work Statement (PWS)

This document outlines critical task areas for "Systems Integration and Engineering Services" and "Architecture Support Services" as part of the "Systems for Inspection & Imports, Recalls Compliance, and Enforcement (SIRCE) II" effort. The overarching goal is to enhance FDA's IT capabilities to support its regulatory mission.

Systems Integration and Engineering Services:

• Develop integration and interoperability strategies for evolving systems.
• Phase out legacy systems and phase in new systems.
• Collaborate with other organizations.
• Recommend strategies for business/mission needs, integration, interface, and interoperability challenges.

Architecture Support Services:

• Provide a full range of architecture support services.
• Minimize the cost of developing and maintaining integrated, end-to-end automated systems.
• Support more intuitive workflows and reduce user task completion time.
• Develop software following modern architecture and design principles.
• Identify tools and technologies using full cycle benefit analyses.

Artificial Intelligence (AI) Services:

• Provide comprehensive AI adoption and implementation support.
• Enhance existing systems with AI capabilities and develop standalone AI-driven solutions.
• Support the full spectrum of AI technologies (e.g., machine learning, generative AI).

Representative AI Tasks Include:

• AI Strategy and Planning: Develop adoption roadmaps, conduct readiness assessments, perform feasibility studies, create governance frameworks, and identify use cases.
• AI Solution Development and Integration: Design and implement AI/ML models for various tasks (risk scoring, pattern recognition, NLP, computer vision), build predictive analytics models, develop generative AI solutions, create intelligent automation workflows, implement recommendation systems, and develop AI-powered data analysis tools.

Not specified in this document.

• AI development must ensure ethical practices and compliance with FDA standards.
• AI solutions should improve operational efficiency, decision-making, and regulatory effectiveness.