As software development accelerates, it's becoming increasingly challenging for legal, security, and IT teams to coordinate their efforts to track personal data flows. Manual workflows that rely on filling out forms and attending meetings can leave IT staff in the dark, which puts user and customer trust at risk.

That's where Relyance AI comes in. Our machine learning technology builds a dynamic, real-time data inventory and map that monitors how personal data moves through your code, applications, infrastructure, and third-party vendors.

On this episode of the Darius Gant Show, Abhi Sharma, Co-Founder & Co-CEO of Relyance AI, shares his background and experience building and marketing compilers, large-scale data processing architectures, machine learning systems, and observability tools. Abhi explains how he applied metamodeling and machine learning to tackle the problems at the intersection of different privacy and security domains, leading to the creation of Relyance AI.

Listen to the podcast on Spotify and Apple podcasts.

Show Notes:

02:26 Applications and entrepreneurship background

05:25 Different applications of machine learning on previous startups

07:11 How Relyance founded a solution to a privacy problem

09:23 Exploring the challenges of privacy and data governance

11:25 Addressing the challenges of data privacy compliance

15:35 Regulatory penalties faced by tech companies

17:53 Discussion on the growing importance of data privacy regulation

21:01 Privacy regulatory enforcement and Relyance solution to assist customers

24:34 Challenges of building a privacy program

29:32 Benefits of machine learning for data protection compliance

32:46 Leveraging public data and machine learning to provide timely value

36:01 Relyance AI foundational modes and defensibility strategies

41:04 Attracting top talent in AI/ML and hiring for data science and machine learning projects

46:57 How to get in contact with the Relyance team

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