Quinn Raises $11M to Bring AI-Powered Wealth Advice to the Masses

Quinn Raises $11M to Bring AI-Powered Wealth Advice to the Masses

Quinn Debuts with $11M to Democratize Financial Advice Using AI

Another stealth startup just stepped into the fintech spotlight—but this one’s not here to automate transactions. It’s here to automate trust.

Quinn, an AI-powered financial planning platform, has launched publicly after raising $11 million in Seed funding. The round was led by Viola Fintech, with participation from existing backers, and it signals a serious bet on the future of embedded, scalable wealth advice—delivered by AI, not armies of human advisors.

What’s Quinn solving? The age-old scalability problem in financial services. Traditional firms operate with a roughly 1:100 advisor-to-client ratio, leaving millions of consumers without personalized guidance. Quinn breaks that bottleneck by embedding financial advice directly into digital banking and wealth platforms, using AI to mimic (and in some ways surpass) the human touch.

Embedded Advice, Real-Time Plans

Rather than replace human advisors outright, Quinn positions itself as an advisor multiplier. Its tech can be white-labeled, co-branded, or embedded natively into existing financial products. Through API integrations, banks and wealth firms can spin up fully compliant, AI-driven financial guidance—without reinventing their entire tech stack.

Here’s what Quinn is offering under the hood:

  • Onboarding in under 12 minutes, with clients completing robust financial assessments quickly
  • Instant financial plans in 30 seconds, personalized and actionable
  • Embedded cross-sell/upsell tools, delivered within the context of a client’s broader financial goals
  • Productivity lifts for human advisors, freeing CFP® professionals to focus on complex or high-touch interactions

It’s fintech-as-infrastructure meets personalized wealth tech, wrapped in a scalable, data-driven engine.

Context Is King

“Financial planning has long been too exclusive, serving the wealthy few,” said Quinn CTO and Co-founder Asaf Amir, a machine learning veteran. “By embedding financial planning into the heart of financial institutions, we’re making advice universally accessible.”

CEO Royi Markowitz adds, “The future of wealth management isn’t about replacing advisors—it’s about amplifying them.”

That’s not just marketing fluff. In practice, Quinn becomes the first responder in a client’s financial journey, surfacing advice contextually—right when a customer checks their portfolio, reviews expenses, or explores new financial products. That positioning makes it a powerful ally for banks and fintechs hungry to deepen engagement and improve product adoption without scaling advisory teams.

Competitive Landscape and Market Signals

Quinn isn’t the first company to chase scalable advice, but few have cracked the embedded use case this cleanly. Comparisons might include Facet, Wealthfront, or even Zoe Financial, all of which automate aspects of the planning process. But Quinn’s edge appears to be in institutional delivery—designed from the ground up to integrate into enterprise systems, not just direct-to-consumer.

The funding comes at a time when financial institutions are under pressure to digitize client engagement without adding headcount. That’s especially true in the mid-market RIA and neobank sectors, where traditional advisors are stretched thin, and consumer expectations around personalization are skyrocketing.

Viola Fintech’s Noam Inbar puts it plainly: “Quinn is a powerful example of contextual fintech in action… delivering personalized, high-impact financial advice exactly when and where it’s needed.”

Bottom Line

Quinn is betting that the next frontier of fintech isn’t about building more apps—it’s about embedding intelligence into the ones we already use. With $11 million in fresh capital and a quietly growing customer base among financial institutions, it’s making a strong case that AI can finally scale the advisory model without sacrificing trust, compliance, or personalization.

If Quinn delivers on its vision, the real question isn’t whether humans or machines give advice—it’s whether consumers care, as long as the advice works.

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