The Concentric Story

Risk is on my mind right now. That will surprise exactly no one: running a startup is an exercise in risk management on topics from the trivial to the strategic. And the problem Concentric’s tackling – protecting an Enterprise’s unstructured data – is about managing our customer’s risk. So, risk is definitely on my mind.

Today Concentric emerged from stealth and took the next step to change how enterprises secure and protect the millions of business-critical documents they create, share, move, modify and manage every day. It’s a big day for us – and I’d like to reflect on how we got here, what we have to offer, and where we’re going. As I thought about it, I realized our story is a story of risk.

When most people think about startups, and risk, they think about the idea: the product concept, the unmet market need, the better mousetrap. But the real risk, even from the beginning, is the people you work with. When Shankar, Madhu and I sat down to figure out what we wanted to do next, some of that risk was already out of the equation for me.  Shankar and Madhu are a formidable team. Together we had years of experience, shared similar values and there was a level of trust that meant we knew we could count on each other through thick and thin.

We were looking for a problem to solve that had the following attributes 1) a widespread problem big enough to be a company, not just a product feature 2)  a tough problem that couldn’t be solved by just anyone; and 3) a valuable problem with customers ready and waiting. In other words, we were ready to embrace technical risk but we wanted to minimize market risk.

There was something we didn’t want to gamble on: the character of our company. We spent as much time talking about our core values as we did researching and validating our product ideas.  We codified our core tenets and values into a document, not because we thought that alone could set the culture for the company, but because we believed it would crystallize our thinking and serve as a reference guide as we built out the team. Sure, there’s still risk ahead of us as we build our company – but at least we have a map of what we want every Concentrian to practice. You can read them here.

Then, we set out to minimize market risk by meeting at least 30 security professionals with a focus on people we didn’t know (just to make sure we got unvarnished feedback). We were struck by how many of them had the same big security gap: business critical data (much of it highly sensitive and exceptionally valuable) was scattered across their organization in millions of files and documents – and they had virtually no visibility or control of it. On top of that, this data was exploding in volume. One CISO told us they had added more data in their environment in the last year than in the prior five years combined and it was everywhere: on-premises, in cloud storage services and in cloud applications. Providing security for this unstructured data checked all the boxes for us: it’s a problem that’s widespread, tough to solve, and valuable.

For unstructured data, answering questions like “Do I have something of value?” “What risks do I face?” and “Is my organization adequately protected?” is incredibly hard. Risk is a function of sensitivity, which requires an understanding of the document’s import and meaning. Our interviews revealed that traditional approaches – like using static policies to characterize and control your data or relying on end users to do that task for you – simply aren’t working. The data is too complex: you can’t write enough rules to identify all of it and users (as dedicated and conscientious as they may be) need more training and motivation than you can possibly give. The security professionals we talked to identified a real need for a solution that analyzes this complex content, derives meaning from it, and assesses it for risk – autonomously and without a lot of human input – so they can secure it wherever it lives. They made it clear to us: if you don’t know what you have, you can’t monitor or protect it. Concentric was born out of those conversations.

Deep learning has been transformative for many applications. It’s made search more accessible to the visually impaired, for example, by analyzing images and generating textual descriptions. It’s heavily used in self-driving cars. It can even learn the “style” of an artist and generate music or compositions in that style. In all these examples, deep learning understands the context and meaning behind the inputs it receives and uses that meaning to solve very complex problems. At Concentric, the power of meaning is the power we bring to bear. We apply deep learning to the world of unstructured data, and we solve the security, compliance and privacy challenges for our clients.

That’s our mission. Concentric’s Semantic Intelligence™ solution uses deep learning to understand your unstructured data’s meaning and assess its risk, so you can fight off data loss and meet security, compliance and privacy mandates.

Have this problem? Please contact us. We would love to engage, listen and explore ways to be helpful. www.concentric.ai or [email protected].