Machine learning can transform how businesses operate, and Salesforce is of the view that barriers to adoption can only be lowered through an open exchange of ideas and code. This is the reason why the company has decided to open source TransmogrifAI — an end-to-end automated machine learning library for structured data, that is used in production today to help power its Einstein AI platform.

In a blog post, Shubha Nabar, Senior Director – Data Science, Salesforce Einstein, said, “TransmogrifAI has been transformational for us, enabling our data scientists to deploy thousands of models in production with minimal hand tuning and reducing the average turn-around time for training a performant model from weeks to just a couple of hours.”

When building machine learning capabilities for consumer products, data scientists usually focus on a handful of well understood use cases and datasets. In contrast, the diversity of the data and use cases at enterprise companies makes machine learning for enterprise products a whole other challenge.

Nabar said that at Salesforce, customers are looking to predict a host of outcomes — from customer churn, sales forecasts and lead conversions to email marketing click throughs, website purchases, offer acceptances, equipment failures, late payments, and much more. It is critical for enterprise customers that their data is not shared with other competitors.

“This means that we have to build customer-specific machine learning models for any given use case. Even if we could build global models, it makes absolutely no sense to do so because every customer’s data is unique, with different schemas, different shapes, and different biases introduced by different business processes. In order to make machine learning truly work for our customers, we have to build and deploy thousands of personalized machine learning models trained on each individual customer’s data for every single use case,” she explained.

Salesforce achieves this through automation. TransmogrifAI, as Nabar puts it, enables data science teams to transform customer data into meaningful, actionable predictions.

By sharing this project with the open source community, Salesforce plans to bring together diverse perspectives to continue to push the technology forward and make it accessible to everyone.