Sramana Mitra: Let me ask you a few different questions that come to mind as I am listening to you. First, you said that a large New York bank came to you, what does that mean? How did they know about you? How did that happen? A large New York bank doesn’t just come to a random company.
Francisco Webber: That is a good question. They had a team that was supposed to be their spearhead in AI technologies. They had a bunch of experts who were scanning the market. At that time, we were a tiny company far away in Austria. The only way for us to reach out was for me to buy a plane ticket one after the other to do meet-ups and small-scale conference presentations.
At that time, we had no product. I simply explained how the system worked. It has such an intuitive simplicity that even businesspeople could use it. They told me after the presentation that it was completely logical that it works.
Sramana Mitra: So somebody from the bank’s team of AI researchers heard you speak at a conference.
Francisco Webber: Exactly. They were looking for the technology.
Sramana Mitra: Did similar things happen with your other customers in which there were groups of people looking for this kind of technology coming to you or did you do something else to get these customers?
Francisco Webber: We had also grown our small marketing activity. Gradually, we got the attention of people working in large companies going to those events on AI and big data. I presented at all possible events. We also wrote articles in the newspaper and so on.
For that, we got individual people from large companies who were precisely seeking. Most of them were early adopters. They had been seeking AI technology by themselves already. Mostly, they seek it because they have specific high pressures in certain areas. The first thing that they did was to try out all the big providers. The problem there was that some of those big providers like Google provide a rather base technology. You would still need someone who knows how to implement and analyze the use case.
What most of those companies did was slow and large projects, but I think it was just crucial for them to learn how this is done. Nobody exactly knew how this worked. Being a small, agile tech team was convenient. We could win a number of those use cases by just being the only ones able to solve them. All of the others gave up because, for example, you would have to enter 20,000 names and descriptions in an ontology. We don’t need to do that kind of work. We do it automatically.
Sramana Mitra: Besides the use cases that you have productized, are you also opening up your platform to other developers to build use cases on top of your technology?
Francisco Webber: Absolutely. I would say that it’s the whole idea behind all of this. Our current strategy in building and on the other hand bridging heads into certain markets is one aspect. This is especially true for a controversial technology like ours. We are definitely not using standard ways of doing things. It becomes more important to prove that we have some traction as a company. People are paying money to get this so that is one proof.
Fundamentally, our product is completely agnostic in terms of a certain business area. As long as the business value is formulated in a text, it should be applicable. That is our second way of proving our company. Of course, we built our stuff in a way that we ended up having a platform.
We do already have a platform. A platform to be used by a community of developers needs more than just the technical, it also needs an engine around it to make sure that people can have easy access. In the near future, we plan to open it up because we will never be able to cater to all use cases that would be a match out there.
This segment is part 4 in the series : Thought Leaders in Artificial Intelligence: Francisco Webber, CEO of Cortical.io
1 2 3 4 5 6 7