Trust your AI
supply chain.

Every model, agent, MCP, and skill in your stack — verified before it runs, governed while it runs, provable after the fact.

THE THREAT

The models, agents, MCPs, and skills your teams are shipping are unsigned, unscanned, and unaccountable.

Enabling AI across your enterprise opens the largest unverified surface in your stack. The next breach won't come from your code. It'll come from an artifact your team trusted by default.

Learn more about Jozu's perspective on security:

  • Backdoored models in production

    Weights pulled from public hubs land directly in serving infrastructure. Static scanners can't see what's hidden in the parameters.

  • Compromised agents and MCPs

    Tool-poisoning, shadow tools, prompt injection through dependencies. Every install is an unknown actor with execution rights.

  • No chain of custody

    No signatures. No attestations. No way to prove which model produced which output, or which version of an agent took which action.

  • Runtime damage, no audit answer

    When something goes wrong — exfiltration, unauthorized action, a regulator's question — there is nothing tamper-evident to fall back on.

THE PLATFORM

Jozu is the supply chain
security layer for AI.

From the artifact your team pulls in, to the action it takes in production. One chain of custody, end to end — across models, agents, MCPs, and skills.

Verify

Jozu Hub

Centralized, signed, scanned, attested. The registry that decides whether a model, agent, or MCP is allowed into your environment at all. Deployed on your infrastructure.

Explore Jozu Hub
Govern

Jozu Agent Guard

Runtime policy enforcement on every agent action — including the local tool calls and stdio operations gateways can't see. Deploys to servers, desktops, edge, IoT, and air-gapped networks.

Explore Agent Guard

CAPABILITIES

Verify, govern, and prove every AI artifact in your enterprise.

Private AI registry

Centralized, signed, scanned. Only trusted artifacts reach production.

Runtime policy enforcement

Admission control plus per-action governance. Including local tool calls and stdio operations that gateways can't see.

Tamper-evident audit

Cryptographically chained logs across artifact, policy, and action. Defensible end to end.

Run anywhere

Self-hosted, on-prem, edge, air-gapped. Same guarantees in every environment.


ENTERPRISE-GRADE

Zero-trust standards,
extended to AI.

The same discipline you already apply to firmware, containers, and software dependencies — finally, for models, agents, MCPs, and skills.

1

Every artifact verified

Cosign signatures, OCI attestations, five integrated vulnerability scanners. Provenance enforced before execution.

2

Every action governed

Policy enforcement at admission and runtime. Human-in-the-loop via MCP elicitation where it matters.

3

Every event provable

Cryptographically chained, tamper-evident audit. Covers the artifact, the agent, the action, the operator.

4

Run anywhere

Self-hosted, on-prem, edge, air-gapped. No cloud dependency. No central controller required.

ARCHITECTURE

Jozu Hub signs and serves the artifacts. Jozu Agent Guard enforces them at runtime — on-prem, at the edge, or fully air-gapped.

JOZU HUB
Registry Server
AI/ML Project Registry
Security Scanning
Policy Administration
Audit Repository
Pulls
Policies (SHA verified)
Pulls Agents, MCPs & Models (SHA verified)
JOZU AGENT GUARD
Secure Runtime
Server, Desktop,
Edge, Air-Gapped
Guardrails
  • Prompt Filtering
  • I/O Filter
Policy Engine
  • Policy Enforcement
  • Tool Access Control
  • Audit Logging
Trusted Workloads
  • Agents
  • MCP Servers
  • Models

Agent Guard operates without compromise in disconnected environments.

Security teams ship AI
on Jozu.

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.
Tomasz Bochenski
External, Lead Machine Learning Platform Engineer, MLOps
DSV
COMPARISON

How Jozu compares.

Side-by-side breakdowns vs the registries, MLOps tools, and runtime guardrails you're probably evaluating.

FAQS
+ How is Jozu different from an AI gateway?

Gateways inspect what crosses the network. Jozu starts at the artifact — verifying every model, agent, MCP, and skill before execution — and enforces policy on every action, including the local tool calls and stdio operations a gateway never sees.

+ Does this slow down my engineers?

No. Approved artifacts are available immediately from the registry. Verification, signing, and scanning happen at admission — not at every request. Local enforcement runs alongside the agent, not in the request path.

+ Does Jozu work air-gapped?

Yes. Both Jozu Hub and Agent Guard are designed for self-hosted, on-prem, edge, and fully air-gapped deployments. No cloud dependency. No central controller required.

+ Where does Jozu fit with KubeFlow, KServe, and KitOps?

Jozu Hub hardens KubeFlow pipelines and KServe deployments with automated scanning, tamper-proof storage, and governance. It uses KitOps ModelKits as the artifact format, so your existing infrastructure stays in place — you don't have to replace your tools.

+ What does an Agent Guard deployment look like?

Agent Guard runs alongside the agent — on a server, a developer laptop, an edge node, or an air-gapped workstation. It enforces admission and runtime policy locally, with no central controller dependency, and ships cryptographically chained logs to Jozu Hub for audit.

+ How do you handle unverified artifacts already in production?

Most teams start by importing existing models, agents, MCPs, and skills into Jozu Hub for inventory and scanning, then route new deployments through Agent Guard. Existing workflows keep running while the unverified backlog gets cleared.

Request your free Jozu trial

Interested in testing Jozu in your private environment? Download the Helm Chart, and start your 2-week trial.

  • STEP 1

    Install

    Jozu Hub can be installed in your environment in just 1-hour, with no disruptions to existing workflows. We suggest taking a baseline measurement of current deployment times and security gaps, to benchmark against.

  • STEP 2

    Evaluate

    Once installed, you can run real-world tests with your models and infrastructure for up to 2-weeks. This will allow you to measure Jozu's performance against your existing tools and processes.

  • STEP 3

    Review

    At the end of your 2-week trial our team will work with you to review your results, and help you quantify improvements and ROI. This includes an implementation and roadmap discussion.