| Vendor / publisher | DoD Chief Digital and Artificial Intelligence Office | NIST Information Technology Laboratory |
| Type | Government-published · Government-published resource | Government-published · Government-published resource |
| Official site | https://cdao.pages.jatic.net/public/ | https://ai-challenges.nist.gov/aria |
| Industries (cited page) | Defense & national security | Cross-industry |
| Frameworks named on cited source | DoD Responsible AI, DoD Directive 3000.09 | NIST AI RMF |
| Open source (OSI license on official repo) | Not an OSI-licensed official repo on this listing | Not an OSI-licensed official repo on this listing |
| Summary (from listing) | CDAO program (funded FY23–FY29) of Python AI T&E libraries, the RAVEN MLOps platform and the maite types/protocols. Focused on CV classification and object detection for UAV, satellite and autonomous-driving missions. Public packages on GitHub, Conda and PyPI. Not a certification. | NIST ITL evaluation (Assessing Risks and Impacts of AI): sector- and task-agnostic model testing, red-teaming and field testing. LLM pilot. Schedule Kickoff May 2024 through Summer 2025 Pilot Summary Report Out. That report is still listed as coming soon. |
| Last verified | 2026-10-14 | 2026-10-14 |
| Cited coverage (counts only) | Maps to 1 DoD AI guidance requirement — see which with Pro Maps to 1 DoD Directive 3000.09 requirement — see which with Pro | Maps to 1 NIST AI RMF function or subcategory — see which with Pro |
| Analyst assessments (counts only) | Analyst assessment: 1 NIST AI RMF function or subcategory — see which with Pro Analyst assessment: 1 DoD AI guidance requirement — see which with Pro Analyst assessment: 1 DoD Directive 3000.09 requirement — see which with Pro | Analyst assessment: 2 NIST AI RMF functions or subcategories — see which with Pro |