Rowspace Secures $50M Funding for AI Financial Data Platform

There is a quiet advantage sitting inside every top-tier investment firm. Years of memos. Models. Monday morning debates. Buried PowerPoints that once moved nine figures with a single slide. Most of it trapped in folders and half-remembered instincts. Rowspace just raised $50M to turn that buried edge into something that compounds.

San Francisco based Rowspace was founded in 2024 by Michael Manapat and Yibo Ling, two MIT grads who have lived on both sides of the capital stack. Michael Manapat, now Co-founder and CEO, built machine learning systems at Stripe and Notion. Yibo Ling, Co-founder and COO, led finance teams at Uber and Binance. One sharpened the code. The other carried the P&L. They met in graduate school, then ran headfirst into the same problem in the real world: critical decisions stitched together from scattered data and institutional memory that lived mostly in someone’s head.

So they built a finance-native intelligence layer. Not another shiny chatbot summarizing PDFs. Rowspace integrates structured and unstructured data across a firm, from accounting systems to old presentations, and performs deep reasoning in advance. The goal is simple and brutal: when capital is on the line, the answer should not depend on who remembers the spreadsheet from 2017.

Sequoia Capital led the $50M round, with participation from Emergence Capital, Stripe, Conviction, and other firms and angels who know what durable infrastructure looks like. When Alfred Lin talks about vertical AI that actually understands the domain, this is what he means. About 10 top-tier firms are already on the platform, signing 7-figure annual contracts. That is not experimentation money. That is conviction.

The deeper play is not automation for the sake of efficiency. It is encoding judgment. Institutional investors win because they see patterns others miss. But patterns decay when they are not systematized. Rowspace processes data in its own cloud systems, focusing on secure compilation and synthesis of proprietary information so firms can query years of insight like it is a living asset.

Congratulations to Michael Manapat and Yibo Ling for building something that respects how finance actually works. This is what happens when operators stop complaining about messy data and start turning it into leverage. In a market obsessed with surface-level AI tricks, Rowspace is betting that real edge lives in the details, and the firms who understand that are already leaning in, quietly, writing checks that suggest they see what is coming next.