The startup said its Series D round, announced Wednesday (April 29), will allow it to further integrate its product to new clients and expand to new regions.
“Finance runs on judgment, relationships, and insight,” Gabe Stengel, co-founder and CEO, wrote in the announcement. “Over the last few decades, it’s also become an industry where some of the best people spend their time assembling decks and rebuilding models instead of talking to clients. AI changes that. It democratizes access to high finance, gives bankers their time back to do higher-leverage work, and helps our partners transform into the institutions they want to be.”
In an interview with Bloomberg News, Stengel described the origins of the company, with him and fellow Princeton University computer science graduate John Willett, a former JPMorgan Chase banker, teaming to create an AI tool designed to take some of the gruntwork out of dealmaking.
“A lot of the analytical work is done by a 21-year-old in tools from 40 years ago at 2 a.m.,” Stengel told Bloomberg, describing a thought that haunted him early in his career: “Why do I have to use Excel? Why do I have to present it in PowerPoint?”
The report, citing sources familiar with the matter, said Rogo’s client base includes Lazard—Stengel’s former employer—JP Morgan, Bank of America, Wells Fargo and Singapore sovereign wealth fund GIC.
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While the Rogo platform lets banks lessen their workloads, the Bloomberg report added that some industry players worry it might cut down on the number of junior bankers.
In related news, PYMNTS wrote earlier this week about the way agentic AI has begun moving “from conference-room promise to operating-room reality in financial services,” with banks, insurers and asset managers all testing software agents on the type of manual work that can hinder decisions.
That report cited recent articles from Snowflake, KPMG and The Economist centered around the same theme: the first major gains are likely to come from tasking agents with tightly-controlled duties such as gathering data, checking documents, monitoring signals, routing approvals and preparing recommendations.
“The larger shift is not simply faster automation,” PYMNTS wrote. “It is a new model for financial work, one in which firms use stronger data foundations, clearer governance and human oversight to turn fragmented processes into more continuous workflows.”
