Jozu
On-prem/SaaS DevSecOps platform to package, secure, and deploy AI models and agents with audit trails, policy controls, and Kubernetes workflows.
🛡️ AgentReady threat assessment
MAESTRO 7-layer threat model + OWASP AIVSS risk score for Jozu, derived from its capabilities.
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology — every score is re-derived by the same automated method as an agent's public evidence changes.
Overview
Jozu is an enterprise AI DevSecOps platform for securely packaging, scanning, and deploying AI/ML models and agent-driven apps. Delivered as SaaS or fully on-prem, it provides a model/agent registry, policy enforcement, SBOM/provenance, and tamper-proof ModelKits based on open standards (KitOps/OCI). Jozu integrates with Kubernetes stacks and CI/CD tools to speed compliant, auditable releases—supporting air-gapped environments and EU AI Act/NIST alignment.
Key features and capabilities
- MLOps
- DevSecOps
- model registry
- policy enforcement
- SBOM
- provenance
- OCI artifacts
- Kubernetes
- on-prem
- air-gapped
Use cases
- Creating a secure registry for models and agent applications with versioning and lineage.
- Automating SBOM/provenance attestations and policy checks before deployment.
- Deploying hardened inference containers to Kubernetes in private or air-gapped environments.
- Integrating ML workflows with GitHub Actions, GitLab CI, Kubeflow, MLflow, and KServe.
- Preparing compliance/audit reports for EU AI Act, ISO 42001, and NIST AI RMF.