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Our Investment in Relyance AI: Bringing Real-Time Visibility to the Chaos of Data Compliance

September 15, 2021

Data privacy, governance, and security infrastructure are currently red hot priorities for obvious reasons. There has been a firestorm sparked by efforts across the globe to legislate consumer privacy, as well as increasingly sophisticated data attacks and public, embarrassing leaks. The European Union implemented GDPR in 2018, creating a zeitgeist around privacy awareness and requirements. At the same time, these demands brought to light the struggle organizations face in trying to implement tools that understand their data, protect it, and assess ongoing risk. In response to these pressures, organizations have increasingly built out dedicated departments and cobbled together systems focused on data privacy and compliance.

Not surprisingly, a new wave of software companies has also emerged to meet this opportunity. The data privacy management software market has seen soaring growth amid continued expansion of regulatory regimes worldwide. And tailwinds continue as several states have passed or are in the process of passing data privacy regulations such as California’s CCPA which passed in 2020. Organizations and data protection professionals need to be able to easily comply with these rules, but the challenge of keeping up with all these policies is daunting for both companies and their software vendors. The majority of businesses don’t have the resources in place to ensure full compliance with data privacy regulations and the majority of software solutions tackle the problem in a fragmented way while lacking automation and modern data discovery techniques.

In fact, the market remains dominated by manual processes that are necessary to navigate a tangled web of state, federal, and international regulatory environments, as well as ever complex data environments. A mass of different checklists and spreadsheets create time-consuming busy work and organizational friction, as well as a huge load on engineering to help identify data sources and workflows. Ultimately organizations remain at high risk of non-compliance and costly consequences. Compliance is complicated, and the need to access data and understand data risk, in real time, and in a simplified way is of paramount importance.

That’s why we’re excited to announce our Series A investment in Relyance AI. They’ve built a first-of-its-kind platform that allows businesses to view and control the use of personal data. By combining extensive legal knowledge with deep technical expertise, Relyance AI has broken the long cycle of inefficiency, inaccuracy and friction that comes with compliance. At its core Relyance AI has taken a DevOps-like approach to the problem (think AppDynamics or Datadog) and their technology automatically maps all data sources, data paths, and data sinks. This gives a holistic “bottoms up” view of data assets and data movement that is completely distinctive in the market. Existing market offerings focus on building applications on top of incomplete and/or inaccurate data. Relyance AI, on the other hand, builds applications that can automatically monitor all data movement, in real time, with a level of coverage, depth, and accuracy that is impossible with existing solutions.

Leila Golchehreh, Co-CEO of Relyance
Abhi Sharma, Co-CEO of Relyance

Relyance AI is taking a fundamentally different and deeply technical approach to solving data protection pain points with an exceptional founding team, well-suited for the challenge. Co-founder and Co-CEO Leila Golchehreh is a lawyer and entrepreneur who spent 12 years living the pain of manual privacy and compliance workflows as Data Protection Officer and Sr. Counsel for Workday, Adaptive Insights, and other tech companies in private practice. Her experience and data protection expertise is well-matched with Co-founder and Co-CEO Abhi Sharma’s impressive background as an engineer, machine-learning expert, and entrepreneur. Abhi is an incredible technologist, who grew up in a small town in India and later earned his masters in CS from Carnegie Mellon. He started his first company at CMU, and joined AppDynamics (where I was an investor) as a platform engineer. There he met the founder and CEO, Jyoti Bansal. I’ve known Jyoti for over a decade, and have partnered with him on two companies, AppDynamics and Harness. When he told me that Abhi was one of his best engineers ever, I jumped. Jyoti and Abhi stayed in touch and Jyoti led the Relyance AI seed round. Now, we’re co-leading the Series A with Jyoti and Unusual Ventures.

That’s one aspect of the investment that is particularly exciting for us. We have deep respect for Jyoti’s product and company building skills and enjoy partnering with him. While he focuses 90% of his time on company building, in this rare case, he is joining Relyance AI’s board, and that is a strong signal of the promise we all see in the company.

At Menlo, we didn’t just come across Relyance AI. We’ve been investigating the data privacy and compliance space for some time now (see Steve Sloane’s blog and graphic below), but until now hadn’t seen a breakthrough, technology led approach with a killer team that understood both the market need and unique approach. We’re thrilled to be partnering with Leila, Abhi, and the Relyance AI team in their mission to bring transparency to personal data processing to the world.