Exclusive: AI financial platform Rowspace secures $50 million led by Sequoia to help investment firms tackle messy data

Michael Manapat and Yibo Ling first met during their graduate studies at MIT, then pursued distinct career trajectories. Manapat held senior technical roles at [redacted] and Notion, while Ling led finance teams at Uber and Binance. Yet both encountered a shared challenge: how to compile fragmented data to inform critical decisions about capital allocation, workflows, and more.

When OpenAI launched ChatGPT in November 2022, Ling tested its ability to perform basic due diligence tasks. He quickly discovered the new AI tool was hindered by a familiar issue: data. “There was clearly a lot of promise, but it just wasn’t working. You need the right information in the right context,” he told . 

This realization prompted Manapat and Ling to collaborate on building Rowspace, an AI platform that lets financial institutions like private equity firms and hedge funds turn their years of proprietary data into alpha. The company is publicly launching today with $50 million in funding across a previously unannounced seed round led by Sequoia and a Series A co-led by Sequoia and Emergence Capital, with participation from Basis Set Ventures, Stripe, Conviction, and other firms and angel investors. 

Amid widespread concern and market uncertainty about whether large language models and foundation models will make software obsolete, Sequoia partner and co-steward Alfred Lin told that Rowspace is a prime example of the kind of application that will thrive in the new AI-powered world. 

“People are talking about how the marginal line of code is very cheap to produce,” Lin said. “What we’re looking for now in almost every company is product velocity, and how quickly that velocity generates moats like network effects and daily product usage.” 

Finding alpha

Manapat described Rowspace as the intelligence layer sitting atop a firm’s data. The platform integrates all of an institution’s structured and unstructured data—whether in documents, accounting systems, or old PowerPoints—and conducts proactive reasoning. “We focus on ensuring we understand all underlying data to drive actual decision-making,” he said. 

Rowspace’s data approach sounds similar to that of popular new consumer tools like Claude Cowork, which can query computer files and create presentations or research memos. But Manapat noted key differences: for one, it doesn’t take ownership of a firm’s data, instead processing it within the customer’s own cloud systems. 

On a deeper level, Manapat said foundation models like Anthropic excel at last-mile tasks—such as formatting a pitchbook in PowerPoint or building a cash flow model—usually done via real-time search.  

“That’s not our focus,” Manapat said. As he explained, there’s no way to ensure an agent reviewed all available information or took time to reason before reaching a conclusion (a process that’s time-consuming and costly). Instead, Rowspace handles deeper data analysis, like spotting tiny details in years of a company’s financial records. This gives the platform a permanent edge over general-purpose tools like Anthropic. 

“Foundation models won’t be able to cater to every need across all industries,” Lin said. “That work will fall to players like Rowspace, which focus on specific verticals.” 

Manapat admitted pure software or user interfaces will be hard to defend, especially as foundation models advance rapidly. But he said that’s why Rowspace focuses on compiling and synthesizing a firm’s data securely, with a financially literate team. Its engineers come from tech-first companies like Notion and Stripe, as well as private equity and credit sectors. “There’s no one-size-fits-all solution in financial services, since each firm’s alpha comes from its unique approach,” Manapat said. “We’re trying to help firms learn from their own data, knowledge, and methods—and amplify those strengths.”

While Rowspace declined to share its valuation or early customers, Manapat said they include longstanding, well-known private equity and credit firms, plus crossover firms operating in both public and private markets. He added Rowspace works with about 10 top firms with seven-figure annual contract values. 

“Customers use this tool to make money—that’s where it matters most,” Lin said. “If our tool consistently helps people use AI to make better decisions, they’ll earn more and outperform others.”