The Axonis federated AI platform

Axonis Case Studies

Every deployment on this page started the same way: an organization with data it could not move, and an AI initiative that had stalled because of it.

‍

The pattern repeats across industries. A health system holds imaging and claims data across a dozen facilities, each under its own governance agreement. A bank holds transaction data in three jurisdictions that will not permit it to leave. A defense program runs sensors at the tactical edge on links that drop for hours at a time. In each case the data science is solvable. The data movement is not.

‍

The studies below document what changed when the model went to the data instead. They are written for the architect who has to implement this, so each one states the constraint that blocked the project, the architecture that was deployed, what integrated with what, and what was measured afterward.

‍

What each study covers

• The governance, regulatory or physical constraint that ruled out a centralized approach
• Deployment topology: how many nodes, where they sat, and what network conditions they operated under
• Integration points with the existing stack, including Snowflake, Databricks, MinIO, Apache Iceberg, Jupyter and the model frameworks already in use
• Measured outcome: time to first production model, infrastructure cost against the centralized alternative, and model accuracy on live production data rather than a sanitized extract
• What the governance and audit trail looked like when a regulator or an internal reviewer asked

‍

How to read the numbers

Axonis is infrastructure, so these are infrastructure results. Across deployments we see up to 12x faster time-to-AI-value than centralizing first, roughly a quarter of the cost of building and maintaining a central data estate for AI, and around 20 percent better model accuracy from training on live production data instead of the subset that was cleared for export.

‍

Those figures move with the environment. A deployment across four sites on reliable links behaves differently to one across forty on intermittent ones. Each study states its own conditions so you can judge which is closest to yours.

‍

If your constraint is not represented here

The architecture does not care much about the industry. It cares about where the data sits, who governs it, and what the network between the nodes looks like. If you are working through a constraint that is not covered below, the fastest path is a conversation with an engineer rather than a longer document.

‍

Talk to an engineer