Secure and deploy ML
in one click, on-prem
The On-Prem Kubernetes AI Integrity Platform
Jozu provides the missing production ops layer for AI - secure packaging, policy control, security scanning, and deployment integrity. Deploy models 7x faster while maintaining tamper-proof security, full audit trails, and policy compliance for production bound AI.
Secure and deploy production
AI/ML with confidence
Unlike AI-specific platforms that focus on experimentation, Jozu is purpose-built for production security and compliance. Jozu is the missing control point between development and production with the same security rigor applied to application code.
7x
Faster Model Deployments
41%
Faster AI Delivery
87%
Less Audit Prep Time
150K+
KitOps Downloads
WHY JOZU
The On-Prem
Advantage
Enterprises pick Jozu because it installs behind their firewall, ensuring that no data leaves their environment; or is visible to Jozu–All while remaining vendor neutral and avoiding unnecessary lock-ins.
Fully Private or
Air-Gapped
Jozu is installed completely behind your firewall, and uses your existing registries, RBAC, and authentication systems. Data never leaves your environment, and it works in air-gapped environments.
Built on Open Standards
Jozu packages your AI projects using the CNCF KitOps project. KitOps is the reference implementation of the CNCF's ModelPack specification, a vendor-neutral industry standard trusted in production across global enterprises and governments.
Enterprise Security
& Compliance
Jozu features automated security scanning with policy enforcement. It uses tamper-proof packaging with SHA-based attestation, and enables complete audit trails for EU AI Act, ISO 42001, and NIST AI RMF compliance.
Works with Your Tools
Jozu bridges the gap between your data scientists and DevOps teams. Our PyKitOps SDK, CI/CD integrations, and familiar workflows make adoption seamless and quick regardless of which team is using it.
KEY CAPABILITIES
Built for Enterprises.
Enterprises run on Kubernetes. From packaging to deployment, Jozu gives enterprises everything they need to run AI securely, quickly, with complete control, and at the scale they require. Immutable artifacts, automated security scans, lightning-fast deployments, and full audit trails ensure your models are not just high-performing, but fully compliant and accountable—whether you’re running locally, in a private cloud environment, or on-prem.
Immutable Model
Packaging
Package models, datasets, code, and configuration together in signed artifacts. Store in your enterprise container registry. Deploy locally or to any serving platform.
Kubernetes Native
Close the gap between experimental success and production reality. Jozu fits perfectly beside KubeFlow's orchestration and KServe's serving capabilities, privising the missing governance layer your projects require
7x Faster
Deployments
In-cluster deployment caching eliminates redundant builds and expensive deployment-time network transfers. Tested with Llama 3.2 8B: 44.9 seconds vs standard deployment of 342.3 seconds.
Complete Audit Trails
Track full lineage for each model or dataset. View change history or download audit reports anytime. Everything aligns to your authentication and authorization definitions.
Integrates with the tools your
team already love.
Jozu integrates with the tools your DevOps team already knows and trusts.
-
Kubernetes Distributions
Jozu works with all distributions:- Amazon EKS
- Azure AKS
- Google GKE
- Red Hat OpenShift
- VMware Tanzu
- Rancher RKE
- And many more...
-
Container Registries
Jozu works with all distributions:- JFrog Artifactory
- Sonatype Nexus
- Harbor
- Amazon ECR
- GitLab Registry
- Docker Hub
- Any OCI 1.1 registry
-
CI/CD & MLOps Tools
Jozu works with all distributions:- Jenkins
- GitLab CI
- GitHub Actions
- MLflow
- Kubeflow
- Databricks
- And 50+ more...
Trusted by Government and
Global Enterprises
Jozu's technology is used by the US government, European government, and global enterprises in every vertical.
We're building a vendor-agnostic MLOps platform and KitOps ModelKits align perfectly with that vision. They work wherever our containers do - on-prem or in the cloud - giving us the freedom to store and deploy ML artifacts without being tied to a specific infrastructure.
3-week proof of value
Interested in trying Jozu? Jozu on-prem is available through a guided Proof of Value
to demonstrate impact in your environment.
- WEEK 1
Installation & Baseline
1-hour installation with your DevOps team, including a baseline measurement of current deployment times and security gaps. No disruption to existing workflows.
- WEEK 2
Evaluation
Real-world testing with your models and infrastructure, including performance measurements comparing Jozu to current processes. Integration validation with your tools.
- WEEK 3
Results Review
Quantified impact assessment showing improvements, including ROI analysis based on your deployment patterns. Implementation roadmap discussion.
An open initiative to unite AI/ML and DevOps teams
The AI/ML space is evolving daily, requiring ongoing innovation from the tools that support its development. At Jozu, we believe that the best solutions come from gathering diverse perspectives to engage in open collaboration. An outcome that open source is uniquely designed to foster.
To support this effort, we are contributing to open source KitOps, which includes Kit CLI and ModelKit files, so ML and DevOps teams can work in a more collaborative way. We’re committed to working alongside the community to make continued investments into KitOps and building a roadmap that meets the needs of individual and enterprise development teams.
KitOps simplifies AI project complexity by packaging your projects dependencies in a single versioned and tamperproof, ModelKit.
