How It Works
Access Performant Models
Browse available models with transparent performance metrics and select the ones you need.
Bring Your Own Model
If you have proprietary models, you can use Hokusai to create incentives for data suppliers to provide access to datasets that will improve your performance.
Collaborate for Better Performance
Hokusai allows AI developers with similar use cases to collaborate and combine their data to create more performant models.
How Does It Work?
Hokusai creates tokens for each model. Tokens are created for performance improvements. Hokusai uses DeltaOne as a unit of measurement for performance improvement. For example, improving a model's AUROC from 0.81 to 0.84 would represent 3 DeltaOne units.
Hokusai creates a bonding curve for each model. The amount each data supplier earns for a DeltaOne improvement depends on the amount of USDC available. Create strong incentives for better performance.
This creates strong incentives for data suppliers to contribute high-quality data and for model developers to improve performance.
🔄 Contribute Your Data. Get a Model. Keep the Benefits.
If your company has a valuable dataset — but no in-house AI team — Hokusai offers a powerful, zero-cost path to deploy AI.
Here's How It Works:
You Contribute Your Data
Securely and privately share your dataset with the Hokusai protocol. Your team — or Hokusai's data scientists — can use our SDK to test, validate, and format your data for model training.
We Train and Deploy a Custom Model
Our network of data scientists will train a high-performance model using your data, evaluate improvements, and deploy the model into production — at no cost to you.
You Get Ongoing Access to Predictions
Your model will be continuously available within the Hokusai platform. You can use it for your business needs and benefit from continued improvements — without infrastructure or hosting costs.
Optional: Monetize Your Model
If your model performs well on shared benchmarks, others can use it too. You'll receive Hokusai tokens tied to your model's performance contribution.