Rogo, a New York-based agentic AI platform built for financial services, closed a $160 million Series D on April 29, 2026. The round brings total funding above $300 million, according to PYMNTS. The company said the capital will fund integration with new clients and geographic expansion.

Rogo’s client base includes Lazard, JPMorgan, Bank of America, Wells Fargo, and Singapore sovereign wealth fund GIC, according to Bloomberg, which cited sources familiar with the matter.

From Princeton to Wall Street’s AI Stack

Co-founders Gabe Stengel and John Willett met at Princeton’s computer science program. Stengel, a former Lazard banker, and Willett, who came from JPMorgan, built Rogo to automate the analytical grind that dominates junior banking hours: assembling pitch decks, rebuilding financial models, pulling research, and formatting output.

“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. “Why do I have to use Excel? Why do I have to present it in PowerPoint?”

In Rogo’s Series D announcement, Stengel framed the opportunity more broadly. “Finance runs on judgment, relationships, and insight. 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,” he wrote.

The Junior Banker Question

Bloomberg reported that some industry players worry Rogo’s platform could reduce the number of junior bankers needed. The tension is familiar across professional services: agents that automate analytical workflows eliminate the entry-level tasks that have historically trained the next generation of senior talent. Banks adopting Rogo will need to answer whether they’re compressing grunt work or compressing headcount.

Funding Concentration in Vertical Finance AI

Rogo’s $160 million is the largest single round for a vertical agentic AI platform targeting financial services. On the same day, Hightouch raised $150 million for agentic marketing and General Analysis closed $10 million for agentic AI security testing. The pattern across all three: investors are funding vertical agent platforms that embed into specific enterprise workflows rather than horizontal agent infrastructure. In finance specifically, the opportunity is acute because the workflows are high-value, structured, and compliance-bound, which makes autonomous execution both more valuable and more auditable than in less regulated verticals.