How U&I Ventures Is Weaponizing the CISO Network to Secure AI

SAN FRANCISCO – October 29, 2026 — Generative AI is breaking enterprise technology. As organizations race to deploy autonomous agents and large language models, the chief information security officers tasked with protecting these systems are staring down a rapidly expanding attack surface. Traditional security tools are failing, and the gap between innovation and defense is widening. Into this breach steps U&I Ventures, a San Francisco-based seed-stage venture capital firm that today announced the oversubscribed final close of its $32.237 million debut fund.

But the capital itself is arguably the least interesting part of the announcement. Founded by veteran investor Kim Moore, the firm has architected a structural shift in how early-stage bets are made. The fund leans on a formalized network of 1,800 enterprise technology executives to validate product-market fit before a single check is written, effectively crowdsourcing both due diligence and distribution.

The 'Buyer-Led' Venture Flywheel

The traditional venture capital model often relies on a "build it and they will come" philosophy, where multi-stage firms fund visionary founders and hope the enterprise market catches up. This new firm flips the dynamic, employing what can be described as a buyer-led flywheel.

By convening a community of roughly 650 CISOs, 850 CTOs, and over 300 CIOs, the fund embeds the end-user directly into the investment process. The firm's leadership—which includes Head of Operations Joaquin Guzman and Founding Operating Partner Kim Cooper—hosts weekly, closed-door discussions across San Francisco, New York, Tel Aviv, and London. These sessions reveal exactly where enterprise infrastructure is fracturing under the weight of AI adoption, allowing the firm to identify opportunities grounded in real-world needs.

"I spent years asking founders what they needed beyond capital, and the answer was always access to the right people," said Kim Moore, Founder and General Partner. "That is the foundation for U&I. Our network has a seat at the investing table and helps us understand what enterprises need before we invest."

This approach is not entirely without precedent in the cybersecurity realm. Syndicates like Silicon Valley CISO Investments and specialized funds such as Cyberstarts have successfully leveraged domain-expert networks to de-risk investments. Cyberstarts, for instance, has amassed over $1.4 billion in commitments by engaging founders before a product even exists, leading to massive outcomes like cloud security giant Wiz. However, U&I's specific focus on the intersection of AI-native infrastructure and its massive, active operator network gives it a distinct edge in bridging the distribution gap for emerging seed-stage founders.

The results of this strategy are already visible. During the oversubscribed seed round for Pluto Security, an AI workspace security platform, the venture firm connected founder and CEO Shahar Bahat with 68 enterprise CISOs in under 24 hours. The security startup, which emerged from stealth this month, has since raised a total of $42 million across two funding rounds, backed by TLV Partners and Jump Capital. It now boasts multi-million-dollar annual recurring revenue with over 40 enterprise customers, including Fortune 500 organizations.

Securing the Autonomous Enterprise Battlefield

The urgency driving these investments stems from a fundamental shift in how artificial intelligence is deployed. The market is moving beyond simple conversational interfaces toward autonomous AI agents capable of executing complex tasks, accessing sensitive databases, and interacting with third-party APIs.

Industry analysts at Gartner recently named agentic AI a top cybersecurity trend for 2026, warning that the rapid deployment of these agents is outpacing security teams' ability to govern them. The primary risk is no longer just what an AI model says—such as generating toxic content or leaking training data—but what an autonomous agent actually does in a production environment. Gartner has outlined mandatory capabilities for modern AI security platforms, including automated security testing, runtime defense against prompt injections, and the discovery of shadow AI applications used by employees without IT approval.

"As companies deploy more autonomous AI systems, they're facing security challenges that existing tools weren't designed to handle," noted Alex Stamos, Chief Security Officer at Cognition. "The technology leaders responsible for securing these systems know firsthand where the gaps are. By bringing those leaders together with founders early, U&I is helping turn real-world security challenges into solutions enterprises actually need."

To address these vulnerabilities, the debut fund has already backed nine startups, including seven currently operating in stealth. These stealth investments specifically target autonomous vulnerability remediation, agentic digital forensics, identity management, and the testing and evaluation of AI agents in production environments. One portfolio company in stealth recently secured initial pilot deployments at Fortune 20 enterprises purely through the firm's network.

Another publicly announced portfolio company, ZeroDrift, provides real-time visibility and control for AI compliance decisions. The startup recently closed an oversubscribed $10 million seed round, backed by a16z speedrun, to help highly regulated industries monitor, approve, and block AI communications.

"U&I has been by far our most helpful investor," said Kumesh Armoogan, Founder and CEO of ZeroDrift, highlighting the tangible value of a network that can accelerate product adoption in notoriously slow-moving sectors like finance and insurance.

The Micro-Fund Playbook for the Generative AI Era

The launch of a $32.237 million debut vehicle also underscores a broader economic reality in the current tech landscape. While multi-billion-dollar foundation model companies dominate headlines and vacuum up massive amounts of capital, a thriving ecosystem of micro-funds is quietly building the crucial infrastructure required to make those models safe for corporate use.

Moore's journey to solo general partner reflects this shift. As an early employee at Asana and a former investor at Glynn Capital and Innovation Endeavors, she spent over a decade observing the operational challenges faced by technology leaders. Her previous investments in security startups like Fig Security and Mate Security, both of which subsequently raised Series A financing, validated the thesis that early access to buyers is the ultimate competitive moat.

Fund I plans to back 40 to 45 pre-seed and seed-stage companies, with initial checks ranging from $250,000 to more than $800,000. In an era where seed rounds can easily exceed $10 million, these check sizes might seem modest. Yet, the true currency the fund offers is not capital, but velocity.

For a pre-seed founder building an AI security tool, navigating the enterprise procurement labyrinth can take 12 to 18 months. By embedding prospective buyers into the investment process, the firm effectively short-circuits this sales cycle. Startups develop products with early input from potential customers, ensuring that by the time a product reaches general availability, it is already mapped to an existing corporate budget and addresses a verified vulnerability.

As the AI security market marches toward a projected $93.75 billion valuation by 2030, the demand for specialized, purpose-built infrastructure will only intensify. The traditional venture capital playbook of writing a check and stepping back is being replaced by a highly operational, hyper-networked model of company building. By transforming the enterprise buyer into an active participant in the venture ecosystem, this new class of investors is not just predicting the future of enterprise security, but actively engineering it.