Lee Kappon of Suridata tells us how to discover and protect the organization’s specific sensitive information across all the data repositories.
First of all, how are you and your family doing in these COVID-19 times?
Lee Kappon: We are all doing well after the second shot of the vaccine.
Tell us about you, your career, how you founded Suridata.
Lee Kappon: I’m Lee, currently living in the center of Israel, Tel-Aviv area. I served 3 years as an Operations Officer in the Israeli Air Force. I hold a BA and an MBA from Tel-Aviv University. Ever since I remember myself, I have always identified situations that needed improvement and wanted to make them better. I always loved building things from scratch, and I love the challenge that comes with it. At some point, I realized I had the Entrepreneurial drive.
Before founding Suridata, I led the deployment of NLP-based technological solutions for large corporations. As part of my role, I worked closely with security teams and kept hearing about their struggle to understand where their most valuable and sensitive data resided. In the past, if you think about it, it was very easy – all the data was stored in local servers, so we knew which data we owned and where. Today, with hundreds of SaaS applications, cloud, and working from home – the data is expanding all over. It became a real challenge to know where the valuable and sensitive data resides and knowing it is a fundamental step towards handling the growing threats security teams tackle daily.
So together with my co-founders, Haviv (COO) and Eyal (CTO), who have vast experience in the security world – we started Suridata.
How does Suridata innovate?
Lee Kappon: We bring an innovative AI approach to the data security world – a proprietary Autonomous Learning capability. Autonomous Learning is innovative because it replaces the use of pre-defined patterns. This capability autonomously learns the customer’s data and then understands what is sensitive based on the learning. The learning is based on our NLP engine. NLP stands for Natural Language Processing, which deals with developing technologies and algorithms that can understand human language. NLP deals with written texts and spoken words (conversations, interactions) and understands the meaning, just like a person would have understood it. Implementing this capability in order to provide data visibility is equivalent to thousands of human analysts who read the texts across the entire organization and classify them based on similar content but in machine scale and speed. This results in an accurate and cost-effective solution.
How does the coronavirus pandemic affect your business finances?
Lee Kappon: In the beginning, everyone was in total shock, and it affected the sales cycle and the fundraising. Customers’ budgets were on hold, and all new security plans were frozen. After a while, when it was clear that the new way of life is here to stay, the processes of new technology adoption started to ramp-up again. Our fundraising process started during the pandemic, so all meetings were held through Zoom, and the process was longer than usual. Our team immediately switched to working from home, so we were able to cut expenses.
Did you have to make difficult choices regarding human resources, and what are the lessons learned?
Lee Kappon: When building the core team of a startup company, you actually build a Commando unit. You can’t compromise on the personnel. Each of the core team members has to be independent, and their DNA must fit a rapidly growing environment. One of the most important things is that you have to create a culture of open communication. Lesson learned – acknowledge that recruiting such people is a challenge and accept the fact that you may have to fire people after a short while if you find out that they are not suitable. Otherwise, the price of their bad work would be higher.
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