Rowspace, an AI platform designed to help financial services firms operationalize proprietary data, launched today with $50 million in funding across a seed round and Series A. The Series A was co-led by Sequoia and Emergence Capital, with the seed round led by Sequoia. Additional participants across both rounds include Stripe, Conviction, Basis Set, Twine, and several finance-industry angels.
Rowspace aims to address a longstanding challenge in financial services: institutional judgment is often buried across fragmented systems, including investment memos, financial models, email threads, accounting platforms, and legacy data infrastructure. While seasoned investors and operators build pattern recognition over decades, much of that expertise remains siloed and difficult to scale.
The company’s platform connects both structured and unstructured data across a firm’s historical records, spanning document repositories, investment and accounting systems, and broader data infrastructure. It then applies what it describes as a “finance-native lens,” modeling how a firm reconciles information, interprets discrepancies, and ultimately makes decisions. The system integrates into existing workflows, whether through Rowspace’s own interface, tools such as Excel and Teams, or directly into a firm’s data stack.
Firms managing hundreds of billions to nearly a trillion dollars in assets are already using Rowspace for portfolio monitoring, complex historical deal analysis, and credit portfolio optimization. According to the company, these institutions turned to Rowspace after finding that general-purpose AI tools lacked the specificity and accuracy required for high-stakes financial decisions.
Rowspace deploys directly into customer environments so that data remains under client control, a design choice intended to meet stringent security requirements common among large financial institutions.
The company is based in San Francisco, with additional operations in New York, and plans to scale its engineering and research teams this year.
KEY QUOTES
“Finance is full of high-stakes decisions. There used to be a tradeoff between moving quickly and making fully informed, nuanced decisions using all the possible data at a firm’s disposal. Our AI platform eliminates that tradeoff. We’re building specialized intelligence that turns a firm’s data into scalable judgment with the rigor finance demands.”
Michael Manapat, Co-founder And CEO, Rowspace
“I’ve lived this problem. As a former CFO who’s managed a major investment portfolio, I’ve made decisions by synthesizing data across fragmented systems. Most tech tools aren’t comprehensive or nuanced enough for finance. And most finance tools need to raise their technical ceiling. We intend to do both.”
Yibo Ling, Co-founder And COO, Rowspace
“Michael built the machine learning systems at Stripe that process billions of transactions and helped drive Notion’s expansion into AI. Yibo has been a finance leader and investor who’s wrestled with the exact challenges Rowspace is solving. They’ve seen the problem from both sides, pairing technical depth with firsthand understanding of what customers actually need. That combination is rare.”
Alfred Lin, Partner, Sequoia
“We back founders who bring lived experience to big, enterprise goals—basically the definition of the Rowspace team. They’re doing the previously impossible work of connecting proprietary data, and reconciling and reasoning over it with real rigor. Without this foundation, it doesn’t matter what other AI tools you’re using.”
Jake Saper, General Partner, Emergence Capital
“Imagine a firm that never forgets. Where an experienced investor’s workflows—touching many different tools in specific ways—can be codified and multiplied. When that’s possible, a first-year analyst can tap into decades of institutional knowledge, and judgment scales with a firm instead of being diluted. That’s what we’re building.”
Michael Manapat, Co-founder And CEO, Rowspace
