Today, a startup that has built an AI-based platform that can detect and take action on that data is coming out of stealth with funding to tackle the issue head-on.
Nightfall — which integrates with and then automatically scans structured and unstructured data that appears in apps like Slack, GitHub, AWS and hundreds more for sensitive information, which it then acts to secure — is launching publicly today with $20.3 million in funding.
Madan studied computer science and specifically worked on machine learning research at Stanford, focusing on HR and recruitment data, and has one exit already under his belt (a networking and advice platform called Chalky) while also working as an investor at Venrock and analyst at Pejman Mar Ventures, while Sathe was the lead engineer who had built and scaled Uber Eats.
Cloud-based collaboration platforms have been the making of distributed teams, which can use them to communicate with each other and work together, sharing data from different apps to get things done even when they are not in the same physical space.
“Business-critical data exists across different systems like Slack, Github, AWS and other apps, and that means sensitive and financial information can proliferate broadly across an organization’s systems,” Madan said.