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. Are you the vendor? Factual corrections are free.
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
- 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.