Inpher CEO Jordan Brandt interviewed on C-Suite Radio with Jeffrey Hayzlett

Jeffrey Hayzlett: (1:38) Why did you start [Inpher]?

Jordan Brandt: Autodesk [my previous company] was moving to cloud – as have most companies now – in offering their software, and there are a lot of challenges around data privacy, data security, and even data residency… While I was doing grad school at Harvard, I met my current co-founder (my genius mathematician!) Dr. Dimitar Jetchev, and he had been working on some interesting technology to improve data security while enabling all of the analytics and AI that we want to do now. So, we put our heads together and said “Hey, this is the next big thing,”… and the future was data privacy and security as it relates to artificial intelligence.

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JH: (3:05) You think there’s too much information floating out there right now?

JB: I think there’s too much unsecured information out there right now. I think the information flow is absolutely critical and necessary, but we just need to make sure that it’s done in a private, compliant way.

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JH: (5:51) If companies have [their data], why is it so easy for these other guys to go and [breach] it?

JB: That’s what we’re trying to make it harder to do – for the bad guys to get the data and for the companies to be able to use all of those data assets for the initiatives that they have… while protecting it against adversaries, which all those attacks are increasing. Specifically, now in the COVID crisis, transaction fraud and digital fraud [are] on the rise dramatically, so that need is more critical now than ever.

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JH: (6:21) Are data and privacy a priority for enterprises?

JB: We’re fortunate in the current scenario that it is mission-critical, not a “nice-to-have.” They need to meet the compliance requirements that are imposed upon them, and… a lot of the data they actually have an individual enterprise is not sufficient to anticipate what’s to come, and that’s because a lot of new patterns of behavior are emerging… Fraud is on the rise, and the patterns that [signal fraudulent behavior have] not necessarily been experienced before… If we put our experiences together, we gain greater knowledge – and that’s really what we’re enabling… That’s still very much a critical need for these enterprises, and that doesn’t go away given current market conditions.

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JH: (10:38) With a remote workforce, how safe is our data right now? What challenges should we be doing to address that?

JB: That’s a particularly salient question right now, obviously that enterprises are accustomed to people coming in, [and] logging into secure networks. Now, suddenly, that attack surface has increased exponentially, so ensuring security of the data wherever it sits has become a big priority… Rather than focusing on the resilience of the network, focus on the resilience of the data itself.

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JH: (11:13) How many companies do you think have a real data strategy or a real privacy strategy?

JB: For us, we’ve served large enterprises in regulated industries that have a very high bar for security and privacy, and are pretty advanced in their use of analytics and AI, like financial services and healthcare, as you can imagine. We see that continuing and not going away, regardless of what the market trends may be.

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JH: (12:07) I would say the top enterprises all have [data privacy strategies] in place at some level, don’t they?

JB: They do – absolutely. There are tiers of sophistication and adoption. They way that we differentiate that market if you think about data analytics and AI are those who are using it in production versus those who are researching it. So, most or all of the Fortune 500 companies are researching it, and a majority of them now are actually implementing that practice. The smaller businesses are typically relying on third-party providers to do the analytics on their behalf.

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JH: (17:02) Do you think we were prepared to deal with the massive changes for business world experience with COVID? How fast were you able to adapt?

JB: The world wasn’t prepared and in our view of the world, we saw more criticality on what it is that we do and offer, and we also saw inbound interest from a more diverse set of customers than we had been serving before. You can imagine the surge of interest from life sciences, biotech, pharma… there are only certain pools of data right now about COVID infection rates, about the symptoms. You need to be able to share the data coming from all those healthcare providers around the world, not just domestically or within a state, but globally to get better insight on that – and that’s really driving the need for this, because again, those sovereign data policy issues come in. I can’t send you the data from Korea. I can’t send you the data from Singapore. I can’t send you the data from the EU.  Because it has very personal information in there, but we want to be able to use that for the benefit of all humanity. We want to build these models that can help us predict these outcomes, and so that need has become more pressing than ever.

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JH: (18:20) You say privacy and security are foundational to the future of computing. What’s the future look like from your perspective?

JB: If you look at how we’ve used the increase in computational power… and the inverse curve that shows the amount of computing that we have in the world today…  The question is what do we use that computational power for. We use it for bigger, better, faster, more. We use it to process more data with higher precision at faster rates. Our thesis and my prediction is that we’re going to increasingly allocate a privacy budget for that computation. So I don’t want to just do bigger, better, faster, more, but I also want to do all of that privately and compliantly and guarantee data security. We anticipate more and more enterprises, and individuals, will allocate some of that computational budget that they have to guarantee the privacy of their data.

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JH: (19:27) What’s the next step for AI and privacy-enhancing technologies, and where are we headed with all of this tech?

JB: Right now, we’re serving these industries like financial services and healthcare, and what we’re seeing is more cross-industry data sharing. And when I say data sharing, I don’t mean the actual data, but the insights from the data… Think of the ability you could get if you had your financial data, your health data, your transaction data, and all of this, but you probably don’t want all of that in the hands of one entity… But the benefit you can get as a consumer is enormous. So, we anticipate that we’ll see more and more of this cross-industry data collaboration for insights. You can think of credit modeling. The bank only has a certain set of information, but if you combine that with the teleco data and other data, you can probably derive better decision systems.