QuantumLight Closes $500M Fund II for Systematic VC

QuantumLight has closed a $500M second fund, doubling the size of its $250M debut vehicle roughly 15 months after Fund I reached its hard cap. Sifted reported the close on August 17, 2026, and CEO Ilya Kondrashov said the new vehicle was oversubscribed and exceeded an undisclosed target.

The fund gives QuantumLight substantially more capital to test a provocative investment thesis: venture sourcing can become systematic without turning founders into rows on a spreadsheet. The firm uses Aleph, its proprietary data platform, to screen the venture-backed company universe before human meetings, diligence, and final investment decisions.

The close is evidence that limited partners are willing to enlarge that experiment before Fund I can provide a mature venture track record. It does not yet prove that an algorithmic sourcing advantage becomes superior ownership, support, exits, or realized returns, which is precisely what makes Fund II consequential.

What QuantumLight Closed

QuantumLight’s second fund closed at $500M, also reported as €432M. EU-Startups corroborated that the vehicle surpassed its target and was oversubscribed, but QuantumLight has not disclosed the target amount, named limited partners, anchor commitments, legal vehicle details, check sizes, reserve policy, or deployment period.

The new fund follows QuantumLight’s official $250M Fund I close on May 20, 2025. That first vehicle closed at its hard cap after beginning to invest in 2023, giving QuantumLight $750M in disclosed commitments across two funds without implying that the management company itself raised that amount as corporate financing.

Fund I’s backers were described by QuantumLight as a global group of technology founders and institutions, though the firm did not name them. The absence of a public Fund II LP roster means the safest conclusion is narrow: investors committed twice as much capital to the second vehicle, and the identities and precise reasons behind those commitments remain private.

How Aleph Fits the Investment Process

QuantumLight was founded by Nik Storonsky, the founder and CEO of Revolut, and is led by CEO Ilya Kondrashov. The firm describes itself as systematic venture capital and growth equity, built by founders, investors, quant traders, AI scientists, and engineers rather than around a traditional bench of brand-name general partners.

Aleph is the center of that pitch. QuantumLight says the system analyzes more than 10B data points across 700,000 venture-backed companies, looking for quantitative signals that can surface potential outliers before a conventional network or inbound pipeline does.

The public process is not fully automated. QuantumLight’s own site describes a sequence that includes identifying companies, meeting the team, iterating the model, conducting confirmatory due diligence, and making an investment decision, which makes Aleph a sourcing and screening system embedded in a human investment process rather than a machine that wires money without judgment.

QuantumLight also claims its model produced 2x higher performance than a top-quartile venture benchmark, defined on the site as average MoM for 2014-2019 vintages. That is a company-reported methodology claim, not an independently audited Fund I return, and the distinction matters because model backtests and realized venture performance answer different questions.

Why Doubling the Fund Matters

Venture firms sell two capabilities as one product. They must find promising companies before everyone else, then win access, price risk, earn ownership, help through operating pressure, make follow-on decisions, and eventually return capital to limited partners.

Data can improve the first job without guaranteeing the second. Aleph may identify a company that traditional networks miss, but the resulting investment still depends on founder trust, competitive deal dynamics, entry price, portfolio construction, reserves, governance, and the slow violence of market timing.

Fund II therefore expands both QuantumLight’s opportunity and its burden. The official portfolio already spans AI, fintech, enterprise software, health technology, cybersecurity, energy, and infrastructure, including companies such as Together AI, Function Health, Factory, Robin AI, Ben, Fuse Energy, Lovable, and ElevenLabs.

With $500M, QuantumLight can apply its system across more capital and potentially larger positions. It also has more room to demonstrate whether systematic sourcing creates a repeatable edge, or simply produces a more efficient way to arrive at the same competitive cap tables.

What Fund II Still Has to Prove

Fund I is too young for the conventional venture scorecard. Realized exits, write-offs, ownership dilution, follow-on discipline, distributions, and full-cycle fund returns take years to emerge, so a second close in 2026 arrives before the first vehicle can settle the central performance question.

That timing does not invalidate the thesis. It clarifies what limited partners are buying today: confidence in Storonsky and Kondrashov, access to a differentiated sourcing system, a portfolio-support model informed by Revolut’s operating playbooks, and the possibility that private-market discovery can become more measurable.

The missing details also constrain the analysis. Without disclosed LPs, target size, stage allocation, check ranges, reserves, or a Fund II portfolio-construction plan, readers cannot yet tell whether the larger vehicle changes QuantumLight’s mandate or simply increases the scale of the same strategy.

The firm’s regulatory footing is clearer. Quantum Light Management Ltd states that it is an appointed representative of FCA-authorized Langham Hall Fund Management LLP, placing the management company inside a defined UK regulatory structure while leaving the fund vehicle’s legal architecture undisclosed.

The Venture Market Is Watching the Wrong Contest

The easy story is software versus venture capitalists. The harder and more useful story is whether software changes where human judgment earns its keep, moving advantage away from who already knows the founder and toward who can recognize evidence earlier, test it faster, and still build the relationship required to win the deal.

If QuantumLight succeeds, traditional firms will need more than networks and memorable partner instincts to explain their edge. If it falls short, the lesson will not be that data is useless; it will be that ranking opportunity and producing venture returns remain distinct crafts with different failure modes.

QuantumLight’s $500M second fund makes that contest large enough to matter. The experiment has doubled before the first result matured, and the next evidence must come from portfolio outcomes rather than the elegance of the model.