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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