April 02 to 04 2018, Santa Clara, USA.

Speaker "Alexis Roos" Details

Name :
alexis roos
Company :
Title :
Topic :

Using AI to provide insights and recommendations from activity data

Abstract :

In the customer age, being able to extract relevant communications information in real-time and cross reference it with context is key. This presentation will explain how Salesforce is using data science and engineering to monitor Salespeople activities in real-time and surface insights and recommendations across products. Salesforce is developing Einstein which is an artificial intelligence (AI) 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 – helping them 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. In this presentation, Alexis and Joe will explain how Salesforce Einstein Activity Platform processes activity data (such as emails) in real-time using streaming and machine learning in addition to contextual knowledge from users and CRM data to provide real time insights and recommended actions. Alexis and Joe will go over use cases, high level architecture and how a variety of technologies (data engineering, data science, NLP, machine learning and deep learning) are combined together to support Salesforce applications.

Profile :
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 twenty years of engineering and management experience including 13 years at Sun Microsystems/Oracle, three startups and two systems integrators. Over the years, Alexis has worked on dozens of successful software products from inception, definition, design to implementation. For the last six years, Alexis has focused focusing on large scale (10s of TBs of data and billion records) data science and engineering using technologies including data engineering, entity resolution, distributed graph processing, machine learning, natural language processing and deep learning. Alexis started learning programming as a teenager, became an avid 68000 programmer and then pursued a Master's Degree in CS with a focus on Cognitive Sciences when AI was about expert systems and has done countless online trainings and learning over the years. Alexis' speaking experience include dozens of conferences (including Spark summit SF and East, Scala by the Bay, Hadoop Summit, Oreilly Web 2.0, Java One, etc), meet-ups and panels in addition to trainings and two University courses on Big data. Alexis is also currently a mentor at thecamp (https://thecamp.fr/)

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