Sramana Mitra: Where are you now?
Divyabh Mishra: Right now, we are close to $6 million. This year could have been a lot more, but everyone has had a hit this year – at least in the first half of the year. Nobody was sure where things were going. Things are picking up though. It has been a trend in the right direction.>>>
Sramana Mitra: You said that you partially sold the company at a $100 million valuation. What is the structure of the company?
Divyabh Mishra: That’s about 43% of the company. That is another interesting piece of the company. Macnica is a public Japanese company. They are distributors of semiconductor parts and are trying to diversify.>>>
Sramana Mitra: You are based in London, right?
Charlie Delingpole: I’ve been in the same room where I started it all. I’ve been in my garage for the past 14 years, but yes, I am in London. We have clients in 80 countries. We have a team in New York, Transylvania, and Singapore.
Sramana Mitra: Are you saying that you work from home?>>>
Sramana Mitra: What is your business model regarding these data scientists who are building these algorithms for you?
Divyabh Mishra: Let’s say the community did not exist and I had subcontracted the work to someone else. They get paid for the work they do. The data scientists are getting paid for building the models. Once we pay them, that model becomes ours. We then deploy and maintain those algorithms and we charge the client for access to those models.>>>
Sramana Mitra: It seems like there is one class of accounts or data objects that is rejected out immediately based on heuristics that you have. There is also another body of behavior monitoring and actions based on behavior monitoring. Are these the only two categories or is there any other kind of intervention?
Charlie Delingpole: That is more within money laundering risk. The key part of finance is the pricing of risk. Just because there is a risk of default or a risk of a claim, it doesn’t mean that you have to abandon that fully. A key part of finance is understanding the risks.>>>
Divyabh Mishra: We do about 10 million API calls per day for one of our customers. For many others, it’s not that huge, but it is still pretty large. We also work with a lot of distributors. We have a lot of B2B clients like electrical or industrial distributors. They have a huge catalog.
For anyone that has a huge catalog and cannot structure this content by hand, there is no other alternative. It’s expensive to do it manually. Our approach of 80% to 85% automation and the rest manual is driving the growth. Those are our current use cases.>>>
Super interesting crowdsourced data model conversation!
25,000 data scientists participating in building algorithms for specific use cases.
David Talby: We have two customers and two different specialties who do that on top of what we do. Quite a few companies have been building on top of our library to sell to different markets.
We don’t intend to compete with our own customers. We intend to stick to that pass layer and focus on data science. There is a lot more work to be done on multi-model learning and understanding images. There is a lot more that we can do in the space.>>>