Privately own, train and monetize your AI assets
Orchestrate fine-tuning with an intuitive drag-and-drop canvas. Connect encrypted datasets, pick trusted guardian nodes, and launch privacy-preserving training jobs
Features
Privately fine tune models
Fine-tune and evaluate models without exposing raw data or private weights. Data remains encrypted and access is policy-controlled.
Modular drag and drop interface
Build training pipelines visually: add base models, attach datasets and drop in compute nodes — no config gymnastics.
Verifiable training results
Immutable traces and reproducible test sets let stakeholders validate improvements before rewards are distributed.
Decentralised training powered by DiLoCo
Run confidential compute on distributed guardian nodes with selective access.
How it works
Select a Base Model
Evaluate external AI models securely on your data - with both data and models kept private
Attach Datasets
Link one or more personal datasets without exposure - you stay private
Pick a Training Node
Select guardian node and then launch training-fully private.