Federated Learning to Power Free Enterprise

The shift to a privacy-first world is irreversible. Delivering personalized experiences without compromising consumer privacy requires a new approach to first-party data and predictive AI.

federated learning

share models and insights without sharing data

Members of the Fantix federation collaborate without ever sharing user-level data. You only share anonymous, aggregated abstractions of your datasets.
Lawyers and engineers love this.

WTF is Data Abstraction?

Learn

Get Insights in Hours, Not Months. For Free!

Gain insights about your users from the collective knowledge of the federation. You won't find a faster way to get aggregated demographic, psychographic, and market intelligence about your users.

Model

Turnkey Models

Access any of the consumer predictive models we have already trained (find them here), or train your own on our federated data to personalize user experience and maximize LTV.

Monetize

Add a Revenue Stream

You can monetize if you choose to make your abstractions available for other members to train their models on. The sweet deal is that nobody -- not even Fantix -- will ever see any user-level data, but you will still earn for contributing to the collective knowledge of the federation.

A No-Code Solution That Every Team Will Love

Product

Gain insights into target markets, customers, competitors, and industry trends. Or join our private Beta to test our personalization API.

Marketing

Acquire custom audiences to use across marketing channels. Leverage audience and customer insights to increase LTV.

Data & Analytics

Find out where else, when and how much your customers spend. All without complex pipelines and data engineering wizardry.

Legal & Corporate

Your user data never leaves your premises. We don't need it. We don't want it. One more time: no user-level data ever leaves your server.

Let's Collab!

May We Wow You with a Demo?

Fantix powers data-driven but data-less collaborations that protect consumer privacy and business confidentiality.