Paul Sinaï with Sébastien Couasnon at Tech&Co

Paul Sinaï with Sébastien Couasnon at Tech&Co

Paul Sinaï on BFM Business, presents the ForePaaS Platform, the end-to-end collaborative multi-cloud platform revolutionizing corporate data projects

 

How Paul Sinaï and ForePaaS help organizations design and industrialize Machine Learning

 

Paul Sinaï addresses some of the solution’s specific features that large organizations can use to design and industrialize their machine learning and analytical solutions in record-breaking time:

  • Automated deployment of an infrastructure capable of raising the speed and agility bar on data projects and securing a fast return on investment.
  • The capacity to aggregate data from a wide range of sources (ERP, CRM, Mail, Internet of things, other corporate information systems, social media and more) and thereby create new services generating revenue streams and improving overall corporate performance.
  • The possibility for companies to control and manage their data using a multi-cloud platform allowing them to keep a handle on their hosting infrastructure choices.
  • The ability to control data-driven intelligence (algorithms, artificial intelligence, machine learning, analytics) by allowing complete flexibility over the choice of solutions and applications.

 

ForePaaS is gaining traction with large global corporations

 

The ForePaaS Machine Learning Platform,  according to Paul Sinaï, has already gained traction in a wide range of industries, such as energy, transport and retail, and is used by such key account customers as Total, Saint-Gobain and Pathé Gaumont.

 

By late 2017, ForePaaS raised USD 10 million. We subsequently broke into the US market. ForePaaS employs more than 40 people and is determined to double its headcount by recruiting data engineers, data scientists, marketing and sales to demonstrate the simplicity of its solution to organizations worldwide.

 

Watch the video with Paul Sinaï

 

Notice the French 3-day stubble look!

 

 

For more articles on cloud infrastructure, data, analytics, machine learning, and data science, follow Paul on Towards Data Science.

 

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