H2O.ai announced a significant breakthrough in reducing the cost of inferencing through its integration with the Snowflake Data Cloud. The company's latest innovations, H2O.ai eScorer and its Snowflake Integration, enable organizations to deploy machine learning models directly into Snowflake as a user-defined function (UDF). This allows for real-time and batch scoring and eliminates the need for data movement and additional processing steps, resulting in a 30x reduction in scoring elapsed time.

The traditional way of handling scoring involves extracting data from Snowflake into a batch job, scoring the data, and then uploading the data back into Snowflake, a process that typically requires additional resources and infrastructure. H2O.ai e Scorer eliminates the need for this traditional batch workflow by allowing organizations to score data directly within their managed Snowflake environment. This not only reduces the elapsed scoring time but also simplifies the workflow and increases security, as the data does not need to be extracted and reloaded.

H2O.ai eScorer is easy to use and deploy, and it supports a wide range of machine learning models. It also provides a cost-effective way to score data, as it uses Snowflake credits for scoring. H2O.ai is a leading provider of AI and machine learning platforms that enable organizations to make better decisions and improve their business outcomes.