H2O AI Feature Store

The Only Intelligent Feature Store

H2O.ai and AT&T co-created the H2O AI Feature Store to store, update, and share the features data scientists, developers, and engineers need to build AI models. Organizations spend large amounts of time exploring and transforming raw data to create predictive features. Unfortunately, these highly valuable and often costly features are typically only available to the data scientists that created them. H2O AI Feature Store makes it easy for organizations to organize, govern, share and operationalize these valuable features. With H2O AI Feature Store, organizations can increase their pace of innovation and deliver impactful AI outcomes faster.

How-it-Works

  1. Data Science and engineering teams engineer features using their tools of choice.
  2. Popular feature engineering pipelines, such as Snowflake, Databricks, H2O Sparkling Water, Apache Spark, and more have pre-built integrations with the H2O AI Feature Store. Additionally, any engineering pipeline can write features and associated metadata to the H2O AI Feature Store via the REST API.
  1. When features are written to the H2O AI Feature Store, data scientists can specify over 40 metadata attributes, tags, and the set of features that need to be available for real-time applications. H2O AI Feature Store uses built-in AI to automatically recommend new features, identify bias, and create feature insights.
  2. Data Scientists can explore and search the feature store to find features to use in their models. Helping them build more accurate and robust models faster. The online Feature Store is powered by Redis to enable sub-millisecond reads for inference. The offline Feature Store supports use cases for batch model training, analytical applications without realtime requirements and exploratory data analysis.