AI Assurance DirectorySafety engineering
Neural Network Dependability Kit (NNDK)
Evidence strength: Emerging How this is scored
Open-source fortiss toolbox for engineering neural networks in safety-critical domains: dependability metrics, test-case generation, formal verification and runtime neuron-activation-pattern monitoring. Jupyter examples on GTSRB, MNIST, KITTI. Used in driving, medical imaging and space navigation.
Certification evidence
Analyst assessment: 2 NIST AI RMF functions or subcategories — see which with Pro
Certification relevance. Searched vendor and publisher pages; no cited clause, function or article.
No cited mapping or literature quote yet. Analyst assessments, if any, stay on Pro.
Listing detail and source evidence (Pro)
Included on Pro, Team and Enterprise. Public summaries, tags and official links on this page stay free.
Analyst assessments (Pro)
Included on Pro, Team and Enterprise. Public summaries, tags and official links on this page stay free.
Procurement evidence pack (Pro) — print cited mappings and analyst notes. The print view is not on this page.
- Vendor / publisher
- fortiss
- Type
- Open source
- Open source
- Open source · AGPL-3.0 on the official repository https://github.com/dependable-ai/nn-dependability-kit. Badge is used only when that repo shows an OSI-approved license.
- Official site
- https://www.fortiss.org/en/research/results/software/nndk
- Industries
- Frameworks named on cited source
- None tagged. The cited pages do not name a framework we cover.
- Last verified
Listing is not an endorsement, certification or recommendation. Capabilities, availability and framework support can change. Confirm with the vendor and the relevant authority. See the disclaimer.