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With Jozu, your AI development lifecycle is faster and more secure than ever before. Find a model on Hugging Face, package it as a ModelKit, push it to Jozu Hub, automatically scan it for licensing issues of security vulnerabilities, add an inference microservice, push to prod.

From HuggingFace playground to production, AI deployment needs more than ‘docker run’. With Jozu Hub + KitOps: ✅ Pull & package Meta’s SAM ✅ Run locally with Kit CLI ✅ Deploy to Kubernetes, clean & signed ✅ Pass the EU AI Act smell test

🚨 New User Study: A national lab is transforming how it manages AI/ML at scale with Jozu Hub. • Secure, standardized “golden paths” • Immutable, signed ModelKits • Seamless Dev → Ops handoff • Built-in compliance and audit trails A blueprint for enterprise-grade MLOps

82% of enterprises are doing AI. Almost half of AI projects never see production. The gap? Security, compliance, and trust. You can’t automate what you can’t prove safe.

Interested in learning more about KitOps? Have questions? Need a bit of help? Join us today at 1:30 PM EST for the KitOps weekly office hours: discord.gg/feqR7uce?event…

If your AI supply chain has no clear audit trail, every deployment is a trust fall. Immutability + attestations = trust you can prove, not just hope for. Secure MLOps starts here

1st step Done Jozu ! ✅

You can generate partial SBOMs for your AI apps with tools like Syft They scan container images for dependencies. But Syft won’t track: – datasets – model lineage – fine-tuning configs For that, you need model-aware SBOMs like KitOps.

See how fast you can bring Hugging Face’s latest SmolLM3 model into your workflow with our Hugging Face Import: • Copy the HF URL • Import the model • Pull locally • Unpack All in under 1 minute. Watch how it works

Secure AI Platform Engineering 🏗️ Model deployment isn’t just “run.py”. We provide: ✅ Immutable model packaging ✅ On-prem or private registry support ✅ Auto-generated inference microservices It's GitOps + DevSecOps for AI infra.

I just brought Hugging Face’s latest SmolLM3 model into our workflow using Jozu’s Hugging Face Import! It took me less than a minute. Here’s a quick video of how it works 👇

Check this out!

Deploying machine learning models from Jupyter notebooks to production is a complex & fragmented process. KitOps is solving these issues by standardizing model packaging & deployment. Watch the Ep: youtu.be/BM9PcoK2Ik8

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