Fine-tune for custom needs
Whether it is healthcare, financial services or any other domain, your users can use custom datasets for their domain or leverage their own organizational data with ease.
End to End Fine Tuning
Granular control, built-inTrack training and validation loss to pick the best model version, while controlling fine-tuning with batch size, epochs, learning rate, and LoRa hyperparameters.
Integrated workflowsFine-tuned models are automatically stored and versioned in Ori Model Registry, and ready for deployment via Inference Endpoints.
Anyone can fine-tune in minutes
Ori’s AI Fabric now brings the same one-click convenience you enjoy on the public cloud to your private cloud and on-prem instances.
Fastest path to production
Parameter-efficient fine-tuning and easy-to-use tools significantly accelerate the ML lifecycle. ML teams can iterate quickly and deliver new model versions to production faster than ever before.
Predictable economics
Ori Cloud pricing is token‑based and grouped by model size tier. The hyper-efficiency of LoRA training makes your fine-tuning cost-effective.
Purpose-built for private and enterprise clouds
Ori Fine-Tuning Studio makes large-scale model customization economically viable. It provides the secure, multi-tenant architecture enterprises need to adapt models for every business unit, and the efficiency cloud providers require to serve thousands of customers.
