Rowspace launches with $50M to turn institutional knowledge into compounding edge for finance

Sequoia leads Seed and Series A funding to help firms operationalize proprietary data for AI

SAN FRANCISCO, Feb. 25, 2026 /PRNewswire/ -- Rowspace, the AI platform that accelerates financial services firms' decision making based on their proprietary data, launched today with $50 million in funding across a Series A co-led by Sequoia and Emergence Capital and a seed round led by Sequoia. Stripe, Conviction, Basis Set, Twine, and angels from across finance participated in both rounds.

The best investors have spent decades building something invaluable: institutional judgment. The partner who's seen five hundred deals knows which patterns matter. The credit analyst who's survived three cycles knows what to watch for. But that knowledge is trapped across messy repositories of memos and models, email exchanges, and myriad legacy systems.

Rowspace puts this data to work. It connects structured and unstructured data across a firm's entire history—document repositories, investment and accounting systems, data infrastructure, and more—then applies a finance-native lens that reflects how that firm reconciles information, interprets discrepancies, and makes decisions. Rowspace scales and accelerates the application of the firm's judgment to its most data-intensive work—and delivers it wherever teams already operate, whether through Rowspace's own interface, within tools like Excel and Teams, or directly into a firm's existing data infrastructure.

"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," says Michael Manapat, Co-founder and CEO of Rowspace. "We're building specialized intelligence that turns a firm's data into scalable judgment with the rigor finance demands."

Firms managing hundreds of billions to almost a trillion dollars in assets are already using Rowspace for portfolio monitoring, complex analysis across decades of deal data, and credit portfolio optimization. These institutions chose Rowspace because generic AI tools couldn't deliver the specificity and uncompromising accuracy their decisions require.

"I've lived this problem," says Yibo Ling, Co-founder and COO of Rowspace. "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."

The company plans to scale quickly this year across its San Francisco and New York offices, with a focus on engineering and research talent drawn to hard problems with major economic implications.

"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," says Alfred Lin, who led the investment for Sequoia. "They've seen the problem from both sides, pairing technical depth with firsthand understanding of what customers actually need. That combination is rare."

Many of Rowspace's backers have been connected to the founders for years before they decided to start the company.

"We back founders who bring lived experience to big, enterprise goals—basically the definition of the Rowspace team," says Jake Saper, General Partner at Emergence Capital. "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."

With Rowspace, a PE firm evaluating a new deal can draw on decades of institutional knowledge to inform its assessment of the risks and opportunities for that deal. A growth investor making portfolio allocation decisions can act on what's true today, not numbers that will take weeks to reconcile. A credit investor can find new opportunities that match its macro view while making sure compliance tests at both the loan and portfolio level are satisfied. Every decision is informed by the full depth of what these firms know.

"Imagine a firm that never forgets," says Manapat. "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."

Rowspace deploys directly into customer environments, so data never leaves their control. Stringent security around a firm's most important asset—its data—has been a design principle from the start. This is the foundation that allows the most exacting firms in the world to fully lean into the AI era and compound their advantage over time.

About Rowspace
Rowspace helps financial firms make faster, sharper decisions by turning their proprietary data into compounding edge. The platform connects structured and unstructured data across a firm's entire history, models how that firm operates and thinks, and delivers that intelligence wherever teams work. Rowspace deploys directly into customer environments for complete data security. The company is based in San Francisco and led by former Notion CTO Michael Manapat and two-time CFO Yibo Ling. Learn more at rowspace.ai.

SOURCE Rowspace