"Clearly there was a lot of promise, but it just wasn't working. You need the right information in the right context. That realization motivated Manapat and Ling to join forces to build Rowspace, an AI platform that allows financial outfits like private equity firms and hedge funds to turn their years of proprietary data into alpha."
"The thing that people are talking about is the marginal line of code is very cheap to produce. What we're looking for now in almost every single company is product velocity, and how fast product velocity generates other things that become moats, which are like network effects and people using your product on a daily basis."
"Manapat described Rowspace as the intelligence layer that sits on top of a firm's data. The platform integrates all of an institution's structured and unstructured data, whether in the form of..."
Michael Manapat and Yibo Ling, who met at MIT, pursued separate careers in technology and finance before identifying a shared problem: fragmented data hindering decision-making. After testing ChatGPT's capabilities for due diligence, Ling recognized that AI tools lacked proper data context. This insight led them to co-found Rowspace, an AI platform designed for financial institutions like private equity firms and hedge funds to convert proprietary data into competitive advantage. The company launched with $50 million in funding from Sequoia, Emergence Capital, Stripe, and Conviction. Sequoia investor Alfred Lin highlighted Rowspace as exemplifying successful AI applications, emphasizing that product velocity and daily user engagement create sustainable competitive advantages in the AI era.
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