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Introduction: A New Era for Traditional Industries
Artificial Intelligence is no longer just a buzzword—it’s becoming a structural force capable of reshaping the very foundations of long-established industries. In this high-stakes transition, Q Fund, a venture capital firm laser-focused on DeepTech, is betting on AI not just as a tool but as an industrial revolution. In a detailed interview for CTech’s VC AI Survey, Managing Partners Liav Ben Rubi and Dana Taigman Koren shared their insights on the evolving AI landscape, particularly how it is poised to deliver profound transformation across sectors often resistant to change.
With a focus on Seed to Series A investments, Q Fund is targeting the inflection point where proprietary data, expert-driven knowledge, and cutting-edge AI converge. Their thesis is simple: industries running on thin margins and archaic processes are ripe for disruption—and AI could be the key to unlocking massive efficiency and profitability gains.
the Original
Q Fund’s managing partners, Liav Ben Rubi and Dana Taigman Koren, believe that AI’s potential to disrupt traditional sectors is vast. They argue that industries relying on tribal knowledge and subject matter experts often have deep data silos that, when unlocked via AI, can drive transformative results. The fund emphasizes sectors such as automotive, defense, logistics, energy, and broader industrial processes.
Founded in 2022, Q Fund operates at the Seed and Series A level, actively seeking startups that bring innovation to sectors where AI hasn’t fully penetrated. They’ve rated AI’s impact on their own operations at 6 out of 10, showing they’re still exploring its full utility internally through customized tools.
While they haven’t had any exits yet from AI startups, they distinguish evaluating AI companies from traditional hardware-focused investments. Metrics like product usage rate, active user percentage, and customer-level gross margin are more important to them than broad financial numbers like ARR at this stage. Their investment approach looks at potential impact and market timing rather than short-term revenue.
Their analysis of AI risks highlights user churn as a top concern, especially given the experimental nature of many tools. Rather than focusing on AI subdomains, they prioritize how deeply a solution can impact a specific sector. Key transformation drivers include predictive maintenance, automation, intelligent decision-making, and alignment with macro trends like reshoring and skilled labor shortages.
Q Fund also highlights Israeli strengths in compute-heavy AI solutions and micro-applications, pointing toward promising exit potentials. However, they also observe that traditional industry-focused AI startups in Israel are still few and far between, despite growing demand.
What Undercode Say:
The insights shared by Q Fund reveal a critical truth about where the next wave of tech unicorns might emerge: not in flashy apps or social networks, but in dusty, overlooked sectors like manufacturing, shipping, or industrial compliance. What makes this narrative powerful is its realism. While most of the startup world chases consumer engagement or SaaS efficiency, Q Fund is looking to redefine how steel gets made, how factories monitor safety, or how supply chains avoid collapse.
The emphasis on proprietary data is especially prescient. In a time when public datasets are saturating mainstream AI development, the true competitive advantage lies in private, domain-specific knowledge—what Q Fund calls the “strongest moat.” This turns traditional companies into gold mines of latent value, just waiting for AI-savvy startups to extract insights and automate inefficiencies.
Moreover, the fund’s refusal to get hypnotized by traditional metrics like ARR or user growth in early stages shows an investor maturity many lack. Their eyes are clearly fixed on long-term category leadership, not quick returns. This mindset is crucial in DeepTech, where success often arrives slower but hits harder.
Interestingly, Q Fund doesn’t limit itself to AI subfields like NLP or vision. Instead, it looks at AI as a means to an end—focusing on whether it can materially improve procurement, compliance, or logistics. That customer-first lens could be the differentiator that separates sustainable companies from hype-driven collapses.
Also notable is their clear-eyed view on risk. By citing churn and unrealistic deployment expectations, they show they’re not wearing rose-colored glasses. This realism, combined with their recognition of Israeli talent in compute-heavy verticals, gives their strategy both a global and local advantage.
In short, Q Fund is betting on a quiet revolution—AI transforming the very bones of industries the tech world rarely celebrates. If their thesis holds true, they could be backing the foundational companies of the next industrial age.
🔍 Fact Checker Results
✅ Q Fund was indeed founded in 2022 and invests in early-stage DeepTech startups.
✅ Their emphasis on proprietary data as a competitive moat aligns with modern AI deployment strategies.
❌ No confirmed exits from AI startups under Q Fund have been recorded yet.
📊 Prediction
By 2028, Q Fund-backed startups will likely play a critical role in modernizing supply chains, manufacturing, and industrial compliance across Israel and Europe. At least one of their portfolio companies could reach unicorn status by tackling a “boring” but lucrative industry pain point—like predictive factory maintenance or automated procurement—where traditional VC funding has been sparse but demand is high.
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Reported By: calcalistechcom_4cd93b0b0a2483966a9222e3
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