Microsoft, IBM, Google – they’re all building AI engines. Cognitive Scale has carved out a layer above them – a Middleware of sorts – that enables them to flexibly power applications in different categories. This is a very interesting positioning, and a story well worth reading for AI aficionados.
Sramana Mitra: Let’s start by introducing our audience to yourself as well as to Cognitive Scale.
Akshay Sabhikhi: I’m the CEO of Cognitive Scale. We are a four-year-old company that was born in AI. We’re based out of Austin, Texas and have about 150 people. We are focused on making AI practical, real, and scalable for enterprises. This company started in healthcare. It’s a tough industry and an industry desperate for the ability to look at the vast amounts of data and to be able to make a difference to how you engage patients. That was the beginning of the company.
Since then, we’ve evolved this company to focus on several other industries including financial services and commerce with a focus on telco, media, and entertainment. While doing that and helping deliver AI-focused capabilities to large organizations, we have developed a very robust platform called CORTEX. AI is not so much about artificial intelligence as it is about augmented intelligence.
In other words, our belief has been that it’s not about replacing humans. It’s the power of bringing AI to humans so the combination of man and machine can really solve problems. That’s the founding theme of this company. There are lots of applications and use cases that we can walk through here.
Sramana Mitra: Before we go into the use cases, can you click one level down and synthesize what genre of problems do you solve with this augmented intelligence as you call it?
Akshay Sabhikhi: Let me start by saying that a big difference in the way we go about doing AI is today when you look at a lot of AI systems, people are talking about chatbots. It’s about how to bring data to a system and then how do I let you ask a question. When you ask a question, hopefully the machine is smart enough to respond to you.
Our premise has been, you don’t know what question is going to be asked. I use that as a way to describe what the company does. We have flipped the order to say that there are many individuals and organizations that could benefit from insights that are delivered to them based on what they need to know rather than a specific question that they have. If you already have a question, it’s already too late.
Our view has been, “How do you deliver a system of insights that can flip the order where the system is smart enough to say, ‘I know you and I understand the situation.’?” We have solved AI in enterprises around two clusters of problems. The first one is what we call engage. It’s about driving an insane level of engagement with the end consumer or an employee within the organization. How do I understand you?