Thought Leaders in Artificial Intelligence: Peter Brodsky, CEO of Hyperscience (Part 3)

Sramana Mitra: Let’s double-click down one level and take one more example. When, automatically, your technology is able to verify a person’s income, how is it able to do that? What data source is it going after to be able to do that? 

Peter Brodsky: We are probably getting too deep into customer specific details and the answer to that question really varies. We offer what is meant to be a generic platform. There is a reason why the company is horizontal.

Hyperscience has generic business blocks that can be used to compose any kind of business process you want similar to how you can compose any kind of user interface you want using a standard library of UI agents.

How you, as a company, put those business blocks together and how you configure what data you feed is largely a customer-specific question. By no means are we focused on mortgages and insurance. Like I said, it’s a very horizontal platform. 

Sramana Mitra: I’m going to extrapolate the answer to my question. In the case of the example where we were trying to understand your technology, your customer would tell you the kinds of documents they need for verification. It could be a verification of income and whatever that set of documents is. You would set up your technology to verify against those documents and when there is ambiguity, you would introduce a human review process. 

Peter Brodsky: That’s the right way to think about it. The company is already ingesting documents. They are doing it all manually. We come along and it’s a drop in automated replacement for manual processes that automates somewhere around 95% of the work. Everyone keeps on doing what they used to, but it’s much less. 

Sramana Mitra: How many customers do you have?

Peter Brodsky: We don’t really disclose that but I’ll say that we serve many in the Fortune 500, Global 2000, as well as major world governments. 

Sramana Mitra: Give me a ballpark number. Are we talking about thousands of customers or hundreds? 

Peter Brodsky: Dozens of customers. 

Sramana Mitra: From what you have seen so far, how many people’s jobs are getting automated through this process?

Peter Brodsky: It’s about 95%. It’s pretty much one-to-one mapping. If you automate 95% of the work, then you need 95% less work that’s done by people. 

Sramana Mitra: I’m not looking for percentages. I’m looking for absolute numbers. 

Peter Brodsky: That varies from customer to customer but I think the more interesting tidbit here is, what we don’t see is companies downsizing. What they do is they take that same set of people and they reassign them to the next highest order bit of business that hasn’t been automated.

It runs counter to the common narrative that automation impacts jobs. I think it does, but not how people always worry that it will. 

Sramana Mitra: If there is a workflow process that has a thousand people and you automate 95% of that, I have a very hard time believing that there would be enough work for those people to be reassigned. 

Peter Brodsky: No, they are just reassigned to the next order of business. 

Sramana Mitra: Do you have a use case or an example of where a thousand people’s jobs were protected even though your technology came in and automated 95% of the function?

Peter Brodsky: Yes, pretty much every single one of our customers. There’s only one exception and the exception was that they paused hiring. We’ve never seen a single one of our customers let anyone go after they brought in Hyperscience.

Every single time we see that those people get reassigned to work on the next highest order of business. This isn’t surprising because companies are always trying to do more. We are in a downturn, and we are going to see what happens, but I don’t think that Hyperscience is going to have a negative effect on our customer’s employees.

It certainly hasn’t been the case today. We’ve been operating for about two and a half years now and we just haven’t seen it. 

Sramana Mitra: That’s interesting. I would be interested in seeing more data on this going along, because I’ve looked at use cases where this kind of technology has been introduced and thousands of jobs get replaced.

Mortgage lending is a good one. We looked at PrecisionLender. They got acquired by Q2 Holdings recently. That was definitely a massive automation-led job reduction. 

This segment is part 3 in the series : Thought Leaders in Artificial Intelligence: Peter Brodsky, CEO of Hyperscience
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