We’re excited to announce Ori Model Registry, the central hub for storing, versioning, and deploying your AI models. No more scattered files in multiple storage repositories and version confusion, with Model Registry you gain a single source of truth that keeps your models organized, up to date, and production-ready. Built-in global caching automatically places each model on the right hardware in the regions you specify, so it’s ready instantly where your users need it.
Centralized model management and deployment
Key capabilities of the Ori Model Registry include:
- Unified model storage & versioning: Every model version is tracked with an ID and version tag, making it simple to organize and keep track of them and manage stages such as development, staging, or production.
- Bring your models to Ori effortlessly: Leverage our simple CLI to upload your models with a single command or add it to your CI/CD scripts for easy automation.
- Global model distribution: Ensure smooth deployments by setting your preferred GPU hardware and a region to store your registered models. For example, you can specify a model as needing an NVIDIA H200 GPU and add it to a registry that is stored in London. Ori will cache models locally and route them so they load instantly when your users need them.
- Instant deployment to endpoints: Ori Model Registry isn’t just a passive storage; it’s deeply connected to Ori’s deployment tools. You can take any model version and deploy it directly to an Ori Inference Endpoint in one click.
Focus on innovation, not infrastructure
By handling the heavy lifting of model and infrastructure management, Ori frees you up to focus on building innovative AI experiences for your customers:
- Streamlined Model Management: Ori Model Registry acts as the single source of truth, tracking every version from development through production. Model Registry makes tracing model lineage and reproducing experiments effortless, while also helping you ensure that you’re deploying the right model at the right location.
- A central hub for your model deployment: Models trained or fine-tuned on Ori land in the Registry, ready for deployment to Endpoints, which means you don’t have to worry about provisioning infrastructure or worry about demand-based scaling.
- Deliver lightning-fast AI experiences : Organize your model registries by location so Ori automatically caches your models in these regions, enabling you to provide low-latency experiences to your users.
- Effortless and easy to use: Designed for simplicity, Model Registry is easy to set up and maintain for your entire team, and needs no DevOps expertise. Additionally, it is tightly integrated with the Ori platform, making your ML workflows truly end-to-end.
Find out more about Ori Model Registry in our technical documentation.
Build limitless AI on Ori
Ready to supercharge your AI/ML workflows with centralized model organization and deployment? Take your AI projects from idea to impact, with Ori’s end-to-end AI cloud platform.
