Get to know the basics of Faraday, and what you can use it to do.

Welcome to Faraday! Let's get started by sharing some basic information about what Faraday is and what you can use it to do.

Faraday predicts customer behavior

Faraday provides AI infrastructure for predicting customer behaviors, like:

To name a few. You can use these prediction objectives to drive powerful customer experiences use cases, like:

Faraday makes predictions about people

Everything Faraday predicts involves a person. You use Faraday to predict that person's behavior. At scale, this means making many predictions — one (or more) for everybody in a group, like your customers.

This also means that Faraday is not a general-purpose AI platform. If you're looking to power a self-driving car, we can't help with that.

Focusing on predicting the behavior of individuals means that doing so with Faraday is very easy — everything you need is built in. The skids are greased.

For instance:

  • Built-in consumer data, with over 1,500 responsibly-sourced details on nearly every adult. This means more accurate predictions faster, without the hassle of licensing or scraping data.

  • Built-in Responsible AI, including bias mitigation and prediction explainability. This means you can build predictive customer experiences without jeopardizing your customers.

Faraday is a DAG

Faraday is a Directed Acyclic Graph (DAG). You can think of it like a pipeline, flowing from your data, through the Faraday predictive machinery, then out into your application, where you use predictions to improve customer experiences.

And that's what we'll tackle next.