Using AI for Providing Insights and Recommendations on Activity Data - Databricks

Using AI for Providing Insights and Recommendations on Activity Data

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In the customer age, being able to extract relevant communications information in real-time and cross reference it with context is key. Learn how Salesforce Inbox is using data science and engineering to enable salespeople to monitor their emails in real-time and surface insights and recommendations.
Salesforce is developing Einstein, an artificial intelligence capability built into the core of the Salesforce Platform. Einstein helps power the world’s smartest CRM to deliver advanced AI capabilities to sales, services, and marketing teams – allowing them to discover new insights, predict likely outcomes to power smarter decision making, recommend next steps, and automate workflows so users can focus on building meaningful relationships with every customer.

Find out how Salesforce Einstein Inbox combines activity data, such as emails, with contextual and CRM data to provide real-time insights and recommended actions. Learn about use cases, architecture, and how a variety of technologies including data engineering, data science, graph processing, NLP, machine learning and deep learning are combined together to support the application.

This session will include an interactive demo where you’ll get to see the associated code using notebooks running Spark.

Session hashtag: #SFds6

About Alexis Roos

Alexis is director of data science and machine learning at salesforce where he is leading a team of data scientists and engineers delivering Intelligent services for Einstein platform. Alexis has over 20 years of engineering and management experience with the last 6 years focused on large scale (10s of TBs of data and billion records) data science & engineering including data preparation, entity resolution, distributed graph processing, machine learning, NLP and deep learning. Alexis started coding as a teen, became an avid 68000 programmer and pursued a MS in CS & Cognitive Sciences when AI was about expert systems.

About Sammy Nammari

Sammy Nammari is a Senior Machine Learning Engineer at Salesforce. He works on machine learning for text data at scale, and in the past he's worked on Spark infrastructure and data pipelines in Spark. Sammy has a BS in Electrical Engineering from the University of Illinois at Urbana-Champaign, and an MS in Electrical Engineering from Stanford.