Pave Finance, a New York-based AI trading and portfolio management platform for financial advisors, closed an oversubscribed $15 million Series A round at a $100 million valuation. The raise, announced September 14, signals growing demand for technology that automates the operational heavy lifting of personalized portfolio construction at a time when advisory firms are straining to scale bespoke client services.
What the platform does
Pave tracks more than 50,000 publicly traded securities and integrates with custodians including Schwab, Fidelity, and BNY Pershing for client onboarding. The platform gives advisors both discretionary and non-discretionary options, generating revenue through a combination of licensing, trading, and investment advisory fees. The core pitch is time savings - reducing the manual burden and cost of building, managing, and trading individualized portfolios.
The company was founded in 2021 by Pascal Cevaer-Corey, a former McKinsey consultant who wanted to create an investment offering with the same quality available to people with "significant sums of money," but at an accessible price point. He was joined by Peter Corey, a former hedge fund manager, and Stephen Evans, a quantitative portfolio manager. The firm now represents $130 billion in assets across more than 300,000 accounts.
Leadership and funding path
CEO Christopher Ainsworth took the role in December 2022 after serving as a managing director in Deutsche Bank's private wealth division. "As advisory businesses grow, firms must now find efficient ways to manage a larger volume of clients who are simultaneously demanding greater personalization in their portfolios," Ainsworth said in a statement.
The Series A follows a $14 million seed round in 2025. Investors in the latest round include advisory firms, former executive officers and board members of financial services companies, and company insiders. The capital will expand Pave's market-facing and engineering teams.
Why this matters for finance professionals
For advisors and wealth managers, the operational math is straightforward: more clients demanding tailored portfolios creates a scalability bottleneck that manual processes cannot solve. Platforms like Pave compress the time between client intake and a live, personalized portfolio by automating construction and trading across tens of thousands of securities. The $130 billion in assets already on the platform suggests that firms are actively paying for this kind of AI for Finance capability - not as a future experiment, but as current infrastructure. For AI for Finance Managers, the takeaway is that automation is moving beyond robo-advisory for retail and into the advisor-served channel, where personalization at scale is becoming a competitive requirement rather than a differentiator.
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