Artificial intelligence startup DualEntry has bagged $90 million in Series A funding, catapulting its valuation to $415 million in just one year since launch.
With backers like Lightspeed Venture Partners, Khosla Ventures, and GV (Google Ventures), the New York-based firm is setting its sights squarely on disrupting the ERP market long dominated by Oracle NetSuite and Sage.
Their hook? An AI-native platform that promises “NextDay Migration”—transferring years of financial data in less than 24 hours, a process that usually drags on for months.
What’s striking is how much appetite there is for AI-powered finance.
It’s not just startups cashing in—giants like the European Central Bank are leaning on AI to secure the digital euro from fraud, showing regulators and central banks are just as eager to integrate machine learning into their core systems.
That’s a strong signal: the future of money isn’t just digital, it’s algorithmic.
And while DualEntry’s pitch sounds like a lifeline for mid-market firms drowning in outdated systems, some caution is creeping in.
Just this week, Morgan Stanley warned that the AI investment boom may be overextending itself, with hyperscalers burning through cash faster than expected.
It raises the question: are we seeing sustainable transformation, or another frothy bubble?
Still, private investors don’t seem spooked. In fact, capital continues to pour in—Riverwood Capital just funneled another $180 million into AppZen, a firm automating back-office finance tasks like expense audits.
Taken together, the momentum shows a clear pattern: investors believe AI in finance is no passing trend, but the foundation of the next decade’s infrastructure.
From my point of view, it’s easy to see why. Anyone who’s lived through the pain of legacy ERP migrations knows how soul-crushingly slow and expensive they can be.
If DualEntry can really deliver on a “flip the switch in a day” promise, then it’s not just another flashy AI startup—it’s a potential category changer.
The real test, of course, will come when larger enterprises start trusting them with billions in financial data.
Until then, it feels like we’re watching the first act of a story that could upend one of the least sexy—but most vital—corners of corporate tech.