FINQ, the AI-powered asset management firm led by veteran investor Eldad Tamir, is calling for a seismic shift in how venture capital operates. As traditional VCs struggle to adapt to the exponential rise of artificial intelligence, Tamir is spearheading FINQ’s efforts to replace human bias with algorithmic intelligence.
In a widely shared LinkedIn post that lit up the tech investing world earlier this month, Tamir described the state of venture capital bluntly: “It’s not iteration—it’s reinvention.” His message? The old rules no longer apply, and sticking to them could cost investors their competitive edge.
VC at a Crossroads
Tamir’s position—now gaining mainstream attention—was amplified by a recent Banking Dive piece, which spotlighted the industry’s growing discomfort with AI that acts as more than just a tool. “Investors are happy to fund AI that improves a dashboard,” Tamir noted. “But the second it threatens to replace human judgment, the brakes go on.”
That conservatism, he argues, is creating a dangerous blind spot. With entire startup categories—such as autonomous finance, AI-native biotech, and decentralized governance—emerging outside the bounds of traditional analysis, “founder charisma” and “network adjacency” are no longer valid filters.
FINQ’s Answer: Let the Models Decide
To meet this moment, FINQ is preparing to launch a new suite of AI-powered ETFs designed around machine-led rebalancing and adaptive asset selection—without reliance on sector nostalgia, index mimicry, or legacy fund manager discretion.
This approach echoes moves by firms like QuantumLight, founded by Revolut’s Nik Storonsky, which recently reported that all 17 of its AI-sourced portfolio companies are outperforming top-tier VC benchmarks by 2x—with no pitch meetings, no human gatekeeping, and no traditional sourcing. Tamir and Storonsky are now seen as the figureheads of a new investing paradigm: one where the future belongs to the algorithm.
AI as the New Alpha
Recent PitchBook data shows that 30% of VC firms now use AI to source at least half of their deals—up from just 7% in 2019. But as Tamir notes, “there’s a huge difference between using AI as an accessory and building your entire thesis around it.”
FINQ’s long-term strategy goes even further: to establish an investment infrastructure where models—not managers—drive the next wave of alpha.
With IRRs declining across traditional VC funds and competition for access intensifying, FINQ believes the next top-performing funds will emerge not from elite partnerships or Silicon Valley circles, but from firms that optimize for machine-learning agility.