Nilesh and I started working on what became Layer 9 in the summer of 2019. It was a quintessentially Silicon Valley moment. Over a quick lunch at Asian Box in Mountain View we decided to jump into an entrepreneurial adventure together.
But before I tell you that story, I should tell you how we first met.
1% connection
It was the spring of 2016. I had just helped MetaMind, the startup I had joined as one of the first ten employees, get to a successful exit. We sold our company to Salesforce and the team has continued to do amazing work as part of Salesforce Research and Einstein.
As I was mulling what would come next, I stopped by the offices of Troo.ly. Nilesh had started the company with a former colleague of mine and they were working on a super interesting problem, quantifying trust and reputation. I loved the human and technical elements of the company and it was a really fun afternoon of learning, brainstorming, and meeting the team. I ultimately decided to go in a different direction but I had been so impressed with Nilesh’s quiet, thoughtful style that I decided to keep in touch.
1% inspiration
After a couple of years of running a startup accelerator, I found myself repeatedly drawn to the idea of what trust and trustworthiness meant in the digital age. Meanwhile, Nilesh and his co-founders had driven to a successful exit of their own, selling Troo.ly to Airbnb. We reconnected to discuss ideas around trust for individuals and the enterprise.
Nilesh had experienced the pain of establishing enterprise trust firsthand by this point. At Airbnb, he had driven significant microservices transformation work. He had also been on the receiving end of GDPR compliance requirements. The process of proving that services handled sensitive data appropriately was almost purely manual and proved to be very costly. He believed that much of the work could and should be automated.
When we discussed this problem, I could sense that we were both very energized. Establishing the trustworthiness of services seemed absolutely crucial in the modern enterprise. The unspoken bargain between companies and their users seemed to be increasingly strained. Everywhere you turned, there were more and more examples of data misuse, breach, and more. The onslaught of regulation in response seemed justifiable but the actual corrective action felt clunky and half-hearted at best.
98% perspiration
As we talked to people at other companies who had recently been through their own privacy compliance journeys we heard the same themes repeated over and over. How difficult it had been to figure out what services they had in the first place. How slow, manual, and painful the data lineage and data mapping process had been. The services fees that they had incurred to get consultants on board to help them meet deadlines. The engineering productivity hit that they were reluctant to even think about. The painful knowledge that they had only gotten to a static view of an incredibly dynamic system. The frustrating thought that they would have to do it all over again very soon. It was clear that the problem was real and widespread. But what could we really do about it?
As we looked at monitoring technology that had become increasingly robust, we realized that developing a way to observe the flow of data in motion was the only credible way to understanding lineage of data, understanding the distribution of sensitive information across different data stores, as well as knowing what data was being shared with third-party apps and vendors. We researched what was available for achieving this and saw a clear gap in the market.
The plunge
And so, with clear conviction that real customers want to prove the trustworthiness of their systems, and a strong belief that the technology solution was ambitious but within reach, Layer 9 was born. In retrospect, as many entrepreneurs will tell you, that was the easy part. We are now on to the very exciting and challenging part of building the product to deliver on our vision of creating the first Privacy Engineering company that delivers real time Application Data Monitoring.
We look forward to telling you more in the coming weeks and months. We’d love it if you would join us on our journey. If you’re interested in learning more, please drop us a note via layer9.ai or follow us on twitter @layer9ai.
