Contentsquare is a global SaaS technology startup that empowers brands to build better digital experiences for all. We've been experiencing tremendous growth within the past few years as our team has grown from 300 to 750 employees, and have recently raised a $190M Series D funding in 2020. In addition, we have 7 main offices across the world (Paris, NYC, London, Tel Aviv, Munich, Tokyo, Singapore) with 700 clients globally including many accounts from the global Fortune 100. We can tell you that this growth is not going to stop here, we still are looking for great talent like you to join our family! Not to brag but… we have been recognized by Gartner as one of the four most innovative ecommerce technologies in the world, and featured in Wired Magazine as one of Europe's hottest startups.

Paris-based analytics platform ContentSquare said Monday that it's raised a $60 million Series C just one year after announcing its $42 million Series B. The fresh round, led by French private equity firm Eurazeo, brings the company's total funding to $120 million since 2016. This raise, like the last, is going toward research and development focused on AI and predictive analytics. ContentSquare is different from services like Google Analytics or Adobe Analytics which show site and app activity, but not why visitors do what they do. The "why" is ContentSquare's differentiator, said company CEO and founder Jonathan Cherki. "They might tell you that you're losing people and where you're losing them from," said Cherki.

Is your company's technology up to speed or out of date? What technologies are other businesses using that you should be considering? Each week, we'll do a quick survey of a small businesses to see what technology they're using because we're all interested in keeping up with the Jones's, right? So how do you compare? Founded in 2012, ContentSquare is an experience optimization platform for online and mobile businesses designed to help increase conversions.

In this article, we will discuss how to go from the research phase to the production phase for ML projects and what are the different options to do so. If you try to have your training and server code in the same repository you would probably end up with a big mess that is hard to maintain. Training models and serving real-time prediction are extremely different tasks and hence should be handled by separate components. Last but not least, there is a proverb that says "Don't s**t where you eat", so there's that too. Thus, a better approach would be to separate the training from the server.

Artificial intelligence is reshaping the way businesses are approaching their future. Learn how AI is taking on human-level functions for customer service, fraud prevention and more. As the "next big thing" emerges, it isn't unusual for buzz to outpace understanding at first. Artificial intelligence continues to cement itself in the technological lexicon, but defining what exactly it is and how it can be used can be hard to pin down. Answers vary depending on who you ask.