A feature store is a data platform that manages and governs your features for machine learning - both for training and serving. You have access to and can reuse previously engineered features available within the entire organisation, avoiding the need to write a feature engineering pipeline for every model put in production.

The Hopsworks Feature Store is available today on Azure as both a managed platform (www.hopsworks.ai) and a custom Enterprise installation. It manages your features for training and serving models in a cluster under your control inside your organisation’s existing cloud account.

Financial institutions invest huge amounts of resources in both identifying and preventing money laundering and fraud. Most existing systems for identifying money laundering are rules-based that are not capable of detecting ever changing schemes. Consequently, these systems generate too many false-positive alerts, taking time and money to run down.

The Hopsworks.ai is the world's first managed feature store for the cloud that provides an open-source and general purpose feature store to design and operate AI applications at scale with Apache Spark.

The Hopsworks Feature Store is a platform for managing and serving features for machine learning that also integrates Kubeflow and On-Premises Clusters (Hadoop).

The Hopsworks Feature Store is a platform for managing and serving features for machine learning. It integrates seamlessly with popular platforms for Data Science and cloud-based data lakes based on S3.

All hyperscale AI companies (LinkedIn, Facebook, AiBnB, Microsoft, Google, etc) build their machine learning platforms around a Feature Store.