We hear a lot about deep learning algorithms and their applications on very large data sets. This interview delves into a company and its customer base that works in that area.
Sramana Mitra: Let’s start by introducing our audience to yourself as well as to the company.
Jack Porter: I’m the CEO of Razorthink. We provide a specific segment of artificial intelligence called machine super intelligence, which is the intersection of advanced deep learning and high-performance computing. Our customers are some of the largest customers in the world. We sit on top of their big data stack and we track patterns.
With these patterns, we make predictions for them. Our predictions could be churn for a customer or an opportunity to upsell a new product to a customer. We do focus on the financial services industry. A lot of our customers are banks and credit card companies. We also have customers from telecommunications sector. Most of our customers are customers who not only have a demographic piece of information but also a very rich transaction feed.
We’ll be inside their check register, saying, “This person is likely to leave the bank because he’s stopped doing this kind of behavior.” It’s a very powerful technology now. A lot of companies are jumping on that. Almost all of our direct contacts are CIOs of these companies and this problem is on their hit list. It’s to focus on artificial intelligence and get a business edge out of it.
Sramana Mitra: Is this a venture-funded company?
Jack Porter: We’ve done our seed investment. It was a large one. We raised $4 million. We’ll be doing another round in September.
Sramana Mitra: You raised $4 million from angels or from VCs?
Jack Porter: Angels.
Sramana Mitra: You’ve already said that you primarily focus on the financial services industry. Can you pick two or three customers and step us through use cases of where you are adding value and how you’re adding value?
Jack Porter: One of our customers is one of the largest banks in the world. It’s a company in India. It’s a little bit different in India where a lot of the banks provide other products as well. A specific product that banks provide is life insurance. We sit inside the transaction feed of the customers and we’re watching for life events. Based on these life events, we’d predict if these customers would be interested in acquiring a life insurance policy.
We start seeing checks going to mortgage brokers and things to that effect showing us that they’re likely to be buying a house or likely to have a baby. We’ll be looking for those events and say, “These are great opportunities. I’ll talk to this customer if he wants to have life insurance.”