Artificial Intelligence Test, Evaluation, Verification, and Validation (TEVV) Capability Request for Information (RFI)
Closed Special Notice Posted
- Agency
-
Defense Intelligence Agency
Department of Defense
- Responses due
- Set-aside
- No set-aside
Opportunity facts
- Place of performance
- Washington, District of Columbia, United States
- Points of contact
Notice details come from SAM.gov. Updated .
About this opportunity
The Defense Intelligence Agency (DIA) issued a Request for Information (RFI) on January 12, 2026, seeking industry input on Artificial Intelligence Test, Evaluation, Verification, and Validation (TEVV) capabilities. This Special Notice is classified as a planning tool rather than a formal solicitation and does not constitute a binding contract or offer. The RFI was originally due on February 6, 2026, but has been extended to February 19, 2026, due to a government shutdown and weather delays in the National Capital Region. The DIA recognizes that the development, deployment, and operation of AI and AI-enabled capabilities within the Intelligence Community and Department of War requires rigorous, comprehensive, and continuous TEVV activities to ensure trustworthiness, reliability, cybersecurity, safety, accuracy, and ethical compliance. Responses should be submitted using the provided Questions and Answers Template via email to ST_Proposal_INBOX@dodiis.mil for unclassified materials, with secure transmission required for responses containing Controlled Unclassified Information or classified information.
The primary objective of this RFI is to develop standardized, scalable, and measurable TEVV metrics and frameworks that can assess the technical performance of AI systems while effectively communicating their trustworthiness and operational readiness to users, senior leaders, and policy makers. DIA seeks comprehensive industry expertise across eight topic areas, including organizational experience, intelligence mission understanding, TEVV frameworks and methodologies, performance metrics, automation and continuous monitoring approaches, collaboration mechanisms, advanced testing capabilities such as red-teaming, and implementation lessons learned. There are no specific eligibility restrictions stated in the Special Notice; however, respondents should have relevant experience with AI testing methodologies, government contracting, and familiarity with Defense Intelligence Enterprise operations across multiple security domains including NIPRNET, SIPRNET, and JWICS. The initiative aims to accelerate the adoption and acceptance of transformative AI technologies throughout the Defense Intelligence Enterprise by establishing an enterprise-wide AI TEVV capability that can support diverse intelligence applications while accommodating specialized mission-specific validation requirements and maintaining consistency across the enterprise.
Notice text
2 versions
Update #2 · Latest ·
*** Due to Government shutdown and NCR snow delays, DIA is extending the RFI response date to 19 February 2026***
Introduction
The Defense Intelligence Agency (DIA) recognizes that the development, deployment, and operation of artificial intelligence (AI) and AI-enabled capabilities (AIEC) within the Intelligence Community (IC) and Department of War (DoW) depends fundamentally upon rigorous, comprehensive, and continuous test, evaluation, verification, and validation (TEVV) activities. As AIEC become increasingly central to intelligence operations and national security decision-making, establishing trust through demonstrated reliability, cybersecurity, safety, accuracy, robustness, and adherence to ethical and legal standards is paramount. Effective TEVV of AIEC serves as the cornerstone for building confidence among operational users, mission owners, senior leadership, and policy makers that AI systems perform as intended, produce trustworthy outputs, mitigate unintended risks, and align with established legal and regulatory frameworks. DIA seeks to implement a mature AI TEVV capability to accelerate the adoption and acceptance of transformative AI technologies throughout the Defense Intelligence Enterprise (DIE).
Background and Motivation
DIA is exploring methods to develop standardized, scalable, and measurable TEVV metrics, as well as improve upon existing TEVV frameworks to assess technical performance of AIEC. These metrics must also effectively communicate the trustworthiness and operational readiness of AIEC to users, senior leaders, decision makers, and policy makers who must authorize their deployment into high-consequence environments.
DIA's responsibility extends beyond internal enterprise systems to include oversight authorities across multiple DIE domains under various DIE Manager (DIEM) authorities. While DIA seeks an enterprise solution for this Agency, certain mission areas may require specialized or extended TEVV approaches. DIA recognizes the critical importance of partnering with ongoing AI TEVV initiatives across DoW components, IC elements, and other federal agencies to leverage existing investments, reduce duplication of effort, promote interoperability, and align to broader community-wide standards and best practices that are rapidly evolving.
General Requirements
Therefore, DIA seeks concepts that provide both enterprise-level standardization and the flexibility to accommodate mission-specific validation requirements, while minimizing duplicative or conflicting processes. DIA believes that effective AI TEVV must address a spectrum of system types supporting analysis, collection, operations, targeting, and business management, amongst others. Each category may require tailored TEVV approaches while maintaining consistency with overarching standards and enterprise governance. Furthermore, AIEC supporting DIA may span from development/training environments through operational deployment across multiple security domains (NIPRNET, SIPRNET, JWICS, etc..) and classification levels. Solutions must account for testing and validation requirements across this continuum, including appropriate isolation, data management, and security considerations for each domain. Lastly, DIA is particularly interested in TEVV capabilities that incorporate automation to enable continuous testing and evaluation throughout the AIEC’s lifecycle, from development through deployment and operational monitoring.
Conclusion
Any proposed capability must align with applicable policies and directives including relevant Intelligence Community Directives (ICDs), Department of Defense (DoD) Manuals (DoDMs), and DoD Instructions (DoDIs), while incorporating both traditional DoW Developmental Test & Evaluation (DT&E) and Operational Test & Evaluation (OT&E) best practices and recently-published AI-specific guidance, frameworks, and testing manuals that address the distinctive challenges of evaluating non-deterministic, data-dependent systems.
Through this RFI, DIA seeks to discover industry best practices, innovative approaches, mature methodologies, and state-of-the-art tooling to bolster its AI TEVV capabilities and address the unique requirements of intelligence mission systems. DIA invites industry partners to share their expertise, lessons learned, technical solutions, and recommended strategies that will enable the Agency to establish a robust, scalable, and sustainable AI TEVV capability appropriate for the intelligence enterprise.
Update #1 ·
Introduction
The Defense Intelligence Agency (DIA) recognizes that the development, deployment, and operation of artificial intelligence (AI) and AI-enabled capabilities (AIEC) within the Intelligence Community (IC) and Department of War (DoW) depends fundamentally upon rigorous, comprehensive, and continuous test, evaluation, verification, and validation (TEVV) activities. As AIEC become increasingly central to intelligence operations and national security decision-making, establishing trust through demonstrated reliability, cybersecurity, safety, accuracy, robustness, and adherence to ethical and legal standards is paramount. Effective TEVV of AIEC serves as the cornerstone for building confidence among operational users, mission owners, senior leadership, and policy makers that AI systems perform as intended, produce trustworthy outputs, mitigate unintended risks, and align with established legal and regulatory frameworks. DIA seeks to implement a mature AI TEVV capability to accelerate the adoption and acceptance of transformative AI technologies throughout the Defense Intelligence Enterprise (DIE).
Background and Motivation
DIA is exploring methods to develop standardized, scalable, and measurable TEVV metrics, as well as improve upon existing TEVV frameworks to assess technical performance of AIEC. These metrics must also effectively communicate the trustworthiness and operational readiness of AIEC to users, senior leaders, decision makers, and policy makers who must authorize their deployment into high-consequence environments.
DIA's responsibility extends beyond internal enterprise systems to include oversight authorities across multiple DIE domains under various DIE Manager (DIEM) authorities. While DIA seeks an enterprise solution for this Agency, certain mission areas may require specialized or extended TEVV approaches. DIA recognizes the critical importance of partnering with ongoing AI TEVV initiatives across DoW components, IC elements, and other federal agencies to leverage existing investments, reduce duplication of effort, promote interoperability, and align to broader community-wide standards and best practices that are rapidly evolving.
General Requirements
Therefore, DIA seeks concepts that provide both enterprise-level standardization and the flexibility to accommodate mission-specific validation requirements, while minimizing duplicative or conflicting processes. DIA believes that effective AI TEVV must address a spectrum of system types supporting analysis, collection, operations, targeting, and business management, amongst others. Each category may require tailored TEVV approaches while maintaining consistency with overarching standards and enterprise governance. Furthermore, AIEC supporting DIA may span from development/training environments through operational deployment across multiple security domains (NIPRNET, SIPRNET, JWICS, etc..) and classification levels. Solutions must account for testing and validation requirements across this continuum, including appropriate isolation, data management, and security considerations for each domain. Lastly, DIA is particularly interested in TEVV capabilities that incorporate automation to enable continuous testing and evaluation throughout the AIEC’s lifecycle, from development through deployment and operational monitoring.
Conclusion
Any proposed capability must align with applicable policies and directives including relevant Intelligence Community Directives (ICDs), Department of Defense (DoD) Manuals (DoDMs), and DoD Instructions (DoDIs), while incorporating both traditional DoW Developmental Test & Evaluation (DT&E) and Operational Test & Evaluation (OT&E) best practices and recently-published AI-specific guidance, frameworks, and testing manuals that address the distinctive challenges of evaluating non-deterministic, data-dependent systems.
Through this RFI, DIA seeks to discover industry best practices, innovative approaches, mature methodologies, and state-of-the-art tooling to bolster its AI TEVV capabilities and address the unique requirements of intelligence mission systems. DIA invites industry partners to share their expertise, lessons learned, technical solutions, and recommended strategies that will enable the Agency to establish a robust, scalable, and sustainable AI TEVV capability appropriate for the intelligence enterprise.
Files
| File | Type | Posted |
|---|---|---|
| RFI TEVV QA Response.pdf | ||
| AI_TEVV_Capability_RFI_Updated_2-4-26.pdf | ||
| AI_TEVV_Capability_RFI.pdf | ||
| Questions_and_Answers_Template_RFI.xlsx | XLSX spreadsheet |
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