The catalyst for this initiative was a persistent operational challenge: critical institutional knowledge was fragmented across disparate systems, including the firm’s relationship management platform and internal chat tools. This fragmentation created significant data quality issues and a systemic vulnerability. The risk of knowledge loss became particularly acute with the announcement of an upcoming team member’s departure, which underscored how vital insights could vanish if not centrally managed.

While human relationships remain the heartbeat of venture capital, the industry relies heavily on vast datasets. Critical information from pitch decks and legal documents to meeting notes and market trends is often siloed across multiple systems. At Glilot Capital, we aimed to unify this fragmented data into a single, actionable intelligence engine. This vision came to life as GlilotOS.

GlilotOS: Our Digital Infrastructure

GlilotOS is a proprietary platform designed to integrate all operational workflows and data points into a centralized intelligence hub. This infrastructure allows our team to seamlessly navigate market trends, deal flow, and portfolio performance through one interface. By consolidating these streams, GlilotOS provides the essential framework for our investment professionals to serve as high-level strategic partners.

Functioning as our firm’s digital core, GlilotOS utilizes specialized AI agents to unlock the full potential of our institutional memory.

Eliot: Purpose-Built Intelligence

More than a simple AI integration, Eliot is a specialized intelligence layer constructed on top of GlilotOS specifically for the venture capital sector. While the Glilot Capital team actively leverages leading AI platforms such as ChatGPT, Gemini, Perplexity, and Claude across various workflows, our primary focus for agent development and deployment is Eliot. We view these external AI platforms as powerful productivity tools, while Eliot serves as our proprietary AI operating layer, purpose-built around the unique needs of venture capital investing and portfolio management. Eliot functions as a proprietary “super-agent,” connecting to all company data sources from our relationship management system and File Sharing systems and internal tools to internal chat platforms to provide a holistic view of our operations. Currently in its beta phase, Eliot focuses on read-only queries to ensure maximum stability and accuracy before we introduce future generative capabilities, such as automated email drafting.

The power of this integration is already being felt in daily operations. In one recent instance, Eliot was able to instantly cross-reference a list of eleven portfolio companies to identify which had recently appointed a CFO or VP of Finance, a task that would have otherwise required extensive manual searching. Deeply integrated into our architecture, it enables real-time reasoning and synthesis for complex tasks, providing outputs tailored to the rigorous standards of the VC landscape.

Transforming Operations

Eliot has revolutionized our workflow by eliminating manual searches across platforms. Tasks that previously required hours of preparation are now completed instantly:

• Strategic Meeting Prep: By aggregating institutional data on companies and founders, Eliot identifies crucial topics and past touchpoints for upcoming discussions.
• Dynamic Diligence: The agent correlates external market signals with internal research to provide a comprehensive analysis of new investment opportunities.
• Active Portfolio Oversight: Eliot tracks operational changes within portfolio companies, flagging issues that need immediate intervention.
• Enhanced LP Engagement: It streamlines investor relations by managing updates and providing instant access to historical communication.
• Conversational Memory: Years of internal memos and insights are transformed into a searchable, interactive knowledge base.

Looking Ahead

As specialists in AI and cybersecurity investments, we believe it is essential to lead by example. Glilot Capital is the first VC firm to deploy a fully integrated AI agent across all operations. Eliot is now a fundamental part of our culture, defining the next generation of AI-native venture capital.

Cybersecurity venture capital built around real market signals

Glilot Capital is an AI-first VC firm founded in Israel in 2011 as the world’s first VC dedicated to cybersecurity. Today, we invest in cybersecurity, AI and enterprise software at seed and early growth through Glilot Seed and Glilot+. The firm manages approximately $1.3 billion and has completed 27 exits.

Our cybersecurity strategy starts with a simple principle: strong technology becomes a company only when real buyers are ready to adopt it. We combine focused investing with direct access to CISOs and senior enterprise leaders, structured product-market fit work through Mach5, and ongoing support from our Value Creation team.

Why cybersecurity requires a specialized investment approach

Cybersecurity markets are shaped by both technology adoption and active adversaries. New infrastructure, cloud architectures and AI systems create new ways to build, but they also create new attack surfaces. This keeps security priorities closely tied to operational risk and makes practitioner insight essential to investment decisions.

Gartner forecast worldwide end-user spending on information security of $213 billion in 2025 and $240 billion in 2026, representing 12.5% growth. Security software was expected to account for approximately $105.9 billion in 2025, ahead of security services at $83.8 billion. Gartner linked continued growth to rising threats and the expanding use of AI by employees and attackers. [4]

The threat data points in the same direction. Verizon’s 2026 Data Breach Investigations Report found that 31% of breaches began with software vulnerabilities, 48% involved ransomware, and 15 attack techniques were being augmented by generative AI. For investors, the implication is clear: cybersecurity is not a single, static category. It is a constantly evolving market made up of distinct subcategories, buyers and technology layers. Investment decisions must therefore begin with the problem, the team and real buyer signals rather than a fixed market map.

Israel’s role in global cybersecurity

Israeli cybersecurity companies raised $4.1 billion in 2025, according to Start-Up Nation Central. Cybersecurity ranked behind business software in total funding, but its median deal size reached $20 million, twice the median for business software.

The sector’s depth extends beyond a single year. Start-Up Nation Central reported that Israeli cybersecurity funding in 2024 was equal to 40% of the total raised by the U.S. cybersecurity market. The number of Israeli cybersecurity companies grew from 272 in 2014 to 505 in 2024, 60% of them remained at an early stage, and seven of the world’s ten largest cybersecurity companies maintained R&D centres in Israel.

That concentration of founders, technical expertise, buyers and global acquirers gives Israel an unusually strong cybersecurity ecosystem. It also creates a competitive seed market in which access to capital is only one part of what founders need from an investor.

Where Glilot Capital invests

Glilot Capital invests from the first institutional round through early growth. Glilot Seed leads seed investments. Glilot+ invests in companies after Series A that have established early traction and are ready to scale. In September 2025, Glilot Capital announced $500 million across new Seed and Glilot+ funds. Reuters reported that approximately half of each fund was reserved for follow-on investments. [1][2][3]

Cybersecurity, AI and enterprise software increasingly overlap. AI systems create new identity, governance and data-security requirements. Security products must integrate into cloud and developer workflows. Enterprise infrastructure becomes more valuable when it can be deployed with trust. We therefore evaluate companies across these intersections instead of treating them as separate markets.

What gets our attention

We look for founders who understand a problem from the inside and can turn that insight into a category-defining company. Five signals consistently matter in our investment process:

• A founding team with first-hand technical, operational or industry knowledge of the problem.
• A problem large and urgent enough to support a category, with a buyer who has both responsibility and budget.
• Technical depth that remains valuable as models, platforms and competitors evolve.
• Evidence that enterprise buyers will change an existing process or priority to adopt the product.
• The ambition and adaptability to build a durable global company.

Our due diligence combines technical and market analysis with direct practitioner feedback. Glilot Capital’s network of CISOs and enterprise leaders helps us test whether a problem is urgent, how buying decisions are made, and what would need to be true for adoption. That input brings real market signals into the investment process and makes the evidence more concrete.

From investment to product market fit

The first institutional round starts the work. Early cybersecurity companies must refine the product, identify the right buyer, navigate enterprise procurement and convert interest into repeatable adoption. Many strong technologies stall because these pieces do not align at the same time.

Mach5 is Glilot Capital’s structured product-market fit program. It brings portfolio founders into direct conversations with senior operators and prospective customers from our advisory network. The goal is to generate real feedback on the problem, product, positioning and buying process early enough to act on it.

Our Value Creation team continues to work across go-to-market strategy, customer access, executive hiring and the next stages of growth. The model is designed to create a faster loop between assumptions and market signals, helping founders make decisions with more clarity.

A track record built in cybersecurity

Glilot has completed 27 exits since 2011, including all eight investments from its first fund. Selected publicly reported cybersecurity exits include:

These outcomes reflect several paths to value creation, from products acquired by major platforms to companies that helped define new security categories. The current portfolio continues that focus across identity, cloud, application security, data security and AI-native security.

Building for category leadership

Cybersecurity has an active global acquirer market. In 2025, Israeli technology M&A reached $74.3 billion across 150 transactions, led by Alphabet’s $32 billion acquisition of Wiz and Palo Alto Networks’ approximately $25 billion acquisition of CyberArk.

At the same time, founders need to build around customer value rather than a presumed exit path. Category leadership begins with a significant problem, a differentiated product and a repeatable reason for enterprises to adopt it. Pricing, hiring and go-to-market choices should support that ambition from the first year.

Working with a specialist cybersecurity investor

A specialist investor should contribute more than pattern recognition. It should understand which security problems have real urgency, how CISOs evaluate new products, where integrations create friction, and what evidence can move a company from an initial pilot to broad enterprise adoption.

Glilot brings that context into both investment decisions and the work that follows. The combination of sector focus, partner involvement, the CISO advisory network, Mach5 and the Value Creation team is built to turn strong ideas into real market traction, and real traction into category leadership.

Frequently asked questions

What stages does Glilot Capital invest in

Glilot invests from seed through early growth. Glilot Seed leads first institutional rounds, while Glilot+ invests after Series A & B in companies with early traction.

Which sectors does Glilot Capital focus on

Cybersecurity, AI and enterprise software, with particular interest in the infrastructure and control layers where these markets converge.

How does Glilot Capital support product market fit

Mach5 connects portfolio founders with CISOs, senior operators and prospective buyers for structured feedback on the problem, product and buying process. The Value Creation team supports go-to-market execution, customer access, hiring and growth.

How can founders contact Glilot Capital

Founders building ambitious companies in cybersecurity, AI or enterprise software can contact Glilot Capital through glilotcapital.com/contact-us. Bring the problem, the insight and the evidence. Let’s make it real.

Sources

[1] Reuters, “Israel’s Glilot Capital raises $500 million for new AI and cybersecurity investments”, 17 September 2025 –  https://finance.yahoo.com/news/israels-glilot-capital-raises-500-130445268.html

[2] Globes, “Glilot Capital raises $500m for VC funds”, 17 September 2025 –  https://en.globes.co.il/en/article-glilot-capital-raises-500m-for-vc-funds-1001522087

[3] Calcalist / CTech, Meir Orbach, “Glilot Capital raises $500 million, topping $1 billion in assets”, 17 September 2025 –  https://www.calcalistech.com/ctechnews/article/sj500f7dsle

[4] Gartner, “Gartner Forecasts Worldwide End-User Spending on Information Security to Total $213 Billion in 2025”, 29 July 2025 –  https://www.gartner.com/en/newsroom/press-releases/2025-07-29-gartner-forecasts-worldwide-end-user-spending-on-information-security-to-total-213-billion-us-dollars-in-2025

[5] Verizon, 2026 Data Breach Investigations Report –  https://www.verizon.com/business/resources/reports/dbir/

[6] Start-Up Nation Central, Israeli Tech Annual Report 2025, 22 December 2025 –  https://startupnationcentral.org/hub/news/pr-israeli-tech-annual-report-2025/

[7] Calcalist / CTech, “Israeli startups raised $15.6 billion in 2025 as AI drove bigger, more concentrated bets”, 22 December 2025 –  https://www.calcalistech.com/ctechnews/article/b1o113p8mbx

[8] Start-Up Nation Central, “Israel’s Cybersecurity Sector Surges, Secures 40% of U.S. Funding Total”, 13 July 2025 (updated 5 November 2025) –  https://startupnationcentral.org/hub/news/israels-cybersecurity-sector-surges/

[9] Reuters, as [1] –  Alphabet–Wiz ($32B, March 2025) and Palo Alto Networks–CyberArk (~$25B, July 2025).

[10] TechCrunch, “Microsoft Buys Israeli Hybrid Cloud Security Startup Aorato In $200M Deal”, 13 November 2014 –  https://techcrunch.com/2014/11/13/microsoft-buys-israeli-hybrid-cloud-security-startup-aorato-in-200m-deal/

[11] SecurityWeek, “Rapid7 Acquires Threat Intelligence Firm IntSights for $335 Million”, 20 July 2021 –  https://www.securityweek.com/rapid7-acquires-threat-intelligence-firm-intsights-335-million/

[12] Palo Alto Networks, “Palo Alto Networks Completes Acquisition of Cider Security”, 20 December 2022 –  https://www.paloaltonetworks.com/company/press/2022/palo-alto-networks-completes-acquisition-of-cider-security

[13] Globes, “Tenable confirms acquisition of Israeli cloud security co Ermetic”, 7 September 2023 –  https://en.globes.co.il/en/article-tenable-confirms-acquisition-of-israeli-cloud-security-co-ermetic-1001457403

[14] Globes, “BeyondTrust buys Israeli access security co Entitle”, April 2024 –  https://en.globes.co.il/en/article-beyondtrust-buys-israeli-access-security-co-entitle-for-200m-1001476744

[15] Calcalist / CTech, “Akamai acquires Israeli AI browser security startup LayerX for $205 million in cash”, 14 May 2026 –  https://www.calcalistech.com/ctechnews/article/byinuqxkme

[16] Calcalist / CTech, “Cribl acquires Israeli cyber startup CardinalOps for around $100 million”, 14 July 2026 –  https://www.calcalistech.com/ctechnews/article/rk71zhxeml

[17] Glilot Capital, About –  https://glilotcapital.com/about/

AI is driving an extraordinary rise in opportunities right now. Our deal flow has never been richer. In the last quarter alone, we closed 4 new investments. We are very picky about new investments, so for us, that is a very high number. Given that, I thought I would share more clarity on what we look for in a new investment.

Since we founded Glilot Capital in 2011, one thing has become very clear: the founders are in the center of everything we do, it doesn’t matter how much work we put into helping portfolio companies, we are not the ones to determine if a company will succeed or not, it’s all about the founders. This is why the identity of the founders is the most important part of any investment. We can talk about markets, technologies and returns, but in the end, every successful company we’ve backed was built by people who combined vision, discipline and persistence. Our job as investors is to be great partners to those people, focused, committed and hands‑on, from the first check to the last major decision.

We invest in cybersecurity and enterprise software from seed through growth, but our filter always starts with the entrepreneurs. When I look at a new cyber deal, I do not run through a mechanical checklist. I ask a few simple questions: who are these founders, why are they building this, and do we see a path to build something truly meaningful.

What We Look For

When evaluating a cybersecurity deal, the first thing we look for is a founding team that can build a huge business fast. The best founders we’ve backed lead from the front, stay close to the details, and are ready to do the hard work themselves, not just delegate. They usually bring a deep understanding of the problem space, often from intelligence units, security roles or building products at leading vendors, and they know how to translate that experience into a clear product and business.

We care a lot about persistence. Markets change, funding cycles come and go, and nothing moves in a straight line. Founders who stick it out through challenges, keep their heads, and continue to think creatively are the ones who ultimately build lasting companies. When we see that combination of character, experience and clarity, it matters more than any single feature in the product.

Of course, we also look at the market and technology. We focus on problems that represent large categories, not just nice features, and we pay attention to timing, whether a problem is becoming urgent for customers, not just interesting. On the technology side, we prefer depth over wrappers: architectures, detection methods or data advantages that are difficult to copy and can support real scale. These are the same fundamentals we apply across every cybersecurity deal we evaluate.

But even in these dimensions, we look at them through the lens of the founders. We ask whether this particular team is the right one to build in this specific market with this kind of technology, and whether they can attract the people and customers they will need along the way.

Why We Sometimes Say No

Saying no is as important as saying yes. Over the years, we’ve learned that when something feels fundamentally misaligned, it is better for both sides to pass early. Usually, that misalignment shows up around the founders and the story they are building.

Sometimes we meet teams targeting crowded spaces without a clear, sharp reason for why their company should lead the category. Sometimes the vision and the market size do not match, or the team is incomplete for the kind of company they want to build. For example, strong technology without a true business leader, or the opposite. And sometimes the difficulty is simply that the founder cannot explain the problem and solution in a way that is clear and convincing.

These are not theoretical criteria; they come from many years of working with entrepreneurs through good and bad cycles. When we decide to say no, we try to be direct and transparent, because honest feedback can still be useful for the founder’s next step, whether with us or with another investor.

What Happens When We Say Yes

When we decide to invest, we do not think in portfolio terms; we think in terms of this specific company and this specific partnership. We built Glilot to be a focused, value‑added fund, not a factory that jumps from one trend to another. That means deep involvement: helping with strategy, opening doors through our network of CISOs and executives, supporting hiring and go‑to‑market, and staying close through every major inflection point.

One of the things I am most proud of today is seeing founders come back to work with us on their second or third company. For us, that is the clearest sign that the way we choose deals, and the way we show up after we invest is working. In the end, our investment criteria in cyber deals can be summarized very simply: we look for great founders with real problems to solve, and we commit to being the kind of partner those founders deserve.

If you’re building in cybersecurity or enterprise software and think Glilot Capital could be the right seed partner, we’d love to hear from you, reach out to our team.

Since joining Glilot, the question I hear most often has nothing to do with AI itself – it has to do with time. LPs ask whether exits will happen sooner. GPs debate whether holding periods will compress. Founders wonder whether AI lets companies scale and get acquired years earlier than before.

It’s a fair question. Diligence that once took months can now take weeks, and capital moves faster than it used to. But I’d frame the real question differently: has the speed of investing changed our expectations more than it’s changed the underlying work of building great companies? Sitting between LPs who fund our conviction and GPs who act on it, my answer, after many of these conversations, is yes.

What AI Has Actually Changed

AI has genuinely upgraded venture’s operating model. Founders build with remarkable efficiency; small teams now do what once required entire engineering organizations. Investors synthesize market research in minutes and evaluate competitive landscapes at a scale that would have been impossible a few years ago. Fundraising has shifted too – companies often arrive at first meetings with more polished products and clearer data, though this varies by sector and stage. On the LP side, reporting is faster, and questions that once took a week of pulling data can often get answered in an afternoon.

That’s really good. But it carries a risk. In our enthusiasm for faster ways of working, we can start assuming the outcomes themselves should arrive faster too. AI has compressed many of the activities surrounding venture investing without rewriting the mechanics of building businesses that endure. Confusing operational speed with value creation is one of the more subtle risks facing our industry right now.

What It Hasn’t
Venture has always run on asymmetry – a handful of exceptional investments can define a fund, and finding them has always required technical insight, conviction, and patience. AI strengthens those capabilities, but the qualities that separate extraordinary companies from merely good ones are still resistant to automation.

Enduring companies are built through thousands of decisions about product, hiring, customers, pricing, and execution that compound quietly, long before the market notices. AI changes how quickly founders reach each decision. It doesn’t change how long it takes good decisions to add up to an obviously great company.

Cybersecurity makes this vivid. It’s one of the fastest-moving sectors in tech, yet the process by which great cybersecurity companies become trusted partners to enterprises hasn’t sped up nearly as much. Large organizations still evaluate vendors carefully, and mission-critical infrastructure still depends on confidence that takes time to earn.

The same pattern holds more broadly: many companies now reach product-market fit faster than a decade ago, but becoming genuinely indispensable to customers tends to stay a long game. The companies that define categories rarely do so because they moved fastest in year one – more often it’s because they kept making better decisions than competitors, year after year.

Friction vs. Judgment

This is where the conversation inside venture is starting to shift. We increasingly celebrate speed as if it were the objective itself: how quickly diligence finishes, how fast capital deploys, how soon companies scale. These are useful questions, but not the most important ones.

Venture has generally rewarded firms not for the fastest decisions, but for the right ones. Faster diligence is valuable because it can lead to a better decision, not because it finishes sooner. AI-assisted sourcing matters when it surfaces founders who’d otherwise be missed, not just more of them.

What This Means for Founders, GPs, and LPs

For founders, there’s never been a better time to build – but the same tools are available to everyone, so speed alone is becoming less of a differentiator. The edge is shifting to what AI can’t replicate: customer understanding, technical originality, resilience, and the ability to earn trust over time.

For GPs, the logic is similar internally. AI should free up time for the work that actually compounds returns: understanding founders, evaluating technical differentiation, and helping portfolio companies through inflection points. The best investors have never been distinguished by how fast they gather information, but by how well they interpret it.

For LPs, this argues for a different set of diligence questions. Rather than asking how much AI has sped up a manager’s process, it’s more useful to ask how AI has improved the quality of their decisions, and whether the firm has a repeatable way of identifying exceptional founders. Speed alone can reward the wrong behavior – it’s possible to move fast and still make worse decisions. In my own conversations with LPs, the ones I particularly value don’t ask only about our impressive speed; they also ask about our conviction, and whether we can defend it years later.

The Discipline of “Not Yet”

The best firms should use every tool that makes them genuinely faster: admin, research, internal process, portfolio support. But that efficiency shouldn’t reduce the rigor applied to investment decisions, or rush an exit before a business has reached its potential. Some of the most successful venture-backed companies got there not by pursuing the earliest possible liquidity, but by continuing to build and pivot long after they had the option to stop.

The View from the IR Desk

Working in investor relations puts me between institutional investors and venture managers – one side focused on distributions, the other on building extraordinary companies. Both are right. The job isn’t choosing one perspective over the other; it’s resisting the temptation to assume that because everything moves faster, value creation does too.

My conversations with LPs are rarely just about performance. More often they’re about conviction and repeatability, and about how technology is changing not just the companies we invest in, but how we invest. I’ve come to think that’s what IR is really for – translating the realities of company-building to investors, and bringing the priorities of institutional capital back into the venture ecosystem.

AI will keep reshaping venture capital in ways we can’t fully predict. Some of those changes will make us faster; the best will make us smarter. The firms that define the next decade will likely be the ones that understand the difference – using technology to remove friction, not judgment, while holding onto what has always produced exceptional outcomes: intellectual honesty, disciplined decision-making, and real partnership with LPs and founders alike.