Azeem Azhar

Quantum computing is no longer speculative—it’s becoming an investment priority. (The most comprehensive quantum startup map—V3) In 2023, European quantum startups outpaced North America, raising $781 million (three times the $240 million raised in the US). Globally, quantum startups raised $2.2 billion, a massive jump from $522 million in 2019. This isn’t happening in a vacuum. Governments are fueling the momentum. The UK has committed $4.3 billion to quantum technologies, while Germany has pledged $3.7 billion. At the same time, VC interest is holding steady, even as funding dries up in other tech sectors.   Quantum technology will have a wide-reaching impact, from cybersecurity and financial modeling to drug discovery and materials science. Pharma will likely see the earliest impact (drug development and molecular simulations using quantum).   In 2022, Finnish startup Algorithmiq raised $4 million for quantum-powered drug discovery, while Paris-based Qubit Pharmaceuticals secured $17 million for molecular simulations. Another European company, Terra Quantum AG, based in Switzerland, raised $75 million to scale its quantum-as-a-service model, which has direct applications in pharma and beyond.   Big Tech is also all-in. Google, IBM, Intel Corporation, and NVIDIA are pouring resources into quantum hardware and software. Meanwhile, publicly traded quantum companies have seen their stocks surge, signaling growing institutional confidence.   At APEX Ventures, we invest in revolutionary quantum startups. We are partnered with kiutra, enabling the second quantum revolution with easy-to-use and sustainable cryogenics, and planqc, building quantum computers that store information in individual atoms.   For founders and investors, the question isn’t whether quantum will matter—it’s when. The trajectory is clear: capital is flowing, enterprise adoption is accelerating, and governments are fully committed. If AI dominated the last decade, quantum may own the next.   Huge thanks for the massive support on the last two posts and for your suggestions!   #Venturecapital #AI #Deeptech #Startups Follow us at APEX Ventures and subscribe to our newsletter for exclusive content on groundbreaking Deep Tech startups: 🔗 https://t2m.io/EV2qHQuo

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"OpenAI has signed about $1tn in deals this year for computing power to run its artificial intelligence models...the deals would give OpenAI access to more than 20 gigawatts of computing capacity, roughly equivalent to the power from 20 nuclear reactors, over the next decade." https://lnkd.in/eGirY8hc

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When I proposed that World Fund invest in a quantum computing startup back in late 2021, the link between climate and compute wasn’t obvious. It is now. Today, I am so proud of Jan Goetz and the entire IQM Quantum Computers team as they announce their $320 million Series B – the largest quantum raise ever outside the US. Too often, the narrative is that Europe is “behind.” This achievement proves otherwise. You can build a global leader out of Espoo and Munich in one of the most cutting-edge technology fields. You can become a global thought leader out of Europe, as Jan is doing. My hope is that this news sparks a stronger European narrative - and encourages us to be loud and proud about our successes. Back in 2022 we ended up leading IQM’s €128m Series A with me being on the board for the past three years. To see them now scaling globally, with a roadmap to fault-tolerant, error-corrected systems, is an extremely proud moment for me personally. So excited for what comes next for them! A warm welcome to Ten Eleven Ventures as the lead investor and Alex on the board - this is a major step towards our US expansion and global quantum dominance. A big congrats to our co-investors Tesi, Elo Mutual Pension Insurance, Varma Mutual Pension Insurance, Schwarz Group, Winbond Electronics Corporation, EIC - European Innovation Council, Bayern Kapital, Vsquared Ventures and more. Press coverage in the comments. More information on the link between climate and compute in our report on the subject which profiles IQM, linked here. https://lnkd.in/dYGcKb73 

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"We're not building another application layer on top of existing models. We've developed a completely new foundational architecture that enables us to create specialised AI assistants that outperform current solutions in specific domains like programming and medicine, while using twenty-five times less computational resources," says the CEO of Farang, our latest investment at APEX Ventures 🚀 When Voima Ventures introduced us to Emil Romanus, we were immediately fascinated by him as a person and AI developer. We completely share his perspective, that today's LLMs achieve their "magic" through a brute-force approach and there must be a more natural — more human brain like — way to train AI models. This is exactly what Farang has set out to do and we cannot wait to share the first models with the world 🤖 We are very proud to back Emil and his team on their mission to build the kind of foundational change we believe will separate the next generation of AI leaders from today's incumbents. https://lnkd.in/g792s9An #deeptech #venturecapital #onwardsandupwards

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On-Prem is the New Cloud: Why Enterprises are Reversing Stance in the Age of AI Remember when cloud was the battleground for innovation, agility, and scale? Everyone was tracking the % of on-prem compute moving to the cloud and it was growing every year? Well now there’s a reversal. The reality today? On-prem is the new cloud. Here’s why. AI’s Dark Side: Legal Risk and Data Governance Headaches Enterprises are excited about AI, but also uneasy as vendors like OpenAI face intensifying legal pressure. In a high-stakes lawsuit, a judge ordered OpenAI to preserve all ChatGPT chats (even deleted ones), overriding its 30-day deletion policy. Imagine that: you delete sensitive conversations, but they’re still sucked into legal limbo. The precedent is clear: AI prompts and outputs are discoverable records, demanding integration into enterprise ESI (Electronic Stored Information) policies. For large organizations handling sensitive data, the risk is simple: you can’t afford your AI tools to turn into legal liabilities. Especially when global regulations (GDPR, etc.) and internal governance collide with unpredictably broad discovery orders. Sovereignty, Control, Trust Many enterprises still ban ChatGPT or impose strict rules on usage. Even when allowed, token limits are throttled. Enterprises are cautiously letting AI in (as they should). Enterprises need to have control and trust. SAP is leaning into this with its Sovereign Cloud On-Site, deployable on customer premises with SAP-managed infrastructure. It is built to deliver data, operational, technical, and legal sovereignty in one package. Doubt it will be the last. Scaling Pains Talking to founders, three reasons stand out why cloud isn’t scaling with AI: 1/ The rate at which AWS/GCP lets you provision compute and the compute it wants you to provision both falter as AI and AI driven developers deploy a lot more code more frequently than before. So sometimes it’s not about data governance, but actually about performance and functionality. 2/ Shadow AI is rampant—employees paste sensitive info into models despite restrictions—creating demand for better permissioning tools. 3/ Data leakage remains a live risk, like the August 2025 Grok incident where hundreds of thousands of private chats became publicly accessible and indexed. One thing is for sure - founders selling into the enterprise are scaling faster if they offer the ability to run on-prem. The Future is Hybrid Don’t get me wrong - cloud is not going anywhere. But neither is on prem. A few years agoI thought we were headed for a full cloud shift, but now I think the future is truly hybrid.

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The next frontier of AI isn't just about choosing the right model. It's about building moats through implementation. Across the Emergence Capital portfolio, companies like Bland and Federato are scaling faster by embedding Forward-Deployed Engineers. These engineers bridge the gap between AI and reality, ensuring real results in production. Read more from my colleagues Gordon and Kyle on why FDEs are the key to unlocking AI's full value. https://lnkd.in/gcsRRGX2

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We just completed our quarterly State of Vertical AI analysis. Q2 saw $17.4B invested across 784 vertical deals, including 2 >$5B EV + a few new unicorns. Vertical financings represented >50% of all raises by # but just 36% by $. Demonstrating the early-stage momentum of Vertical AI... But also the continuing $ concentration into late-stage generalist AI players. Momentum: + RE, Education & Hospitality saw the most outsized early-stage activity + Life Sciences & Public Sector were most overweight to mid / late stage Big question of the quarter: While Vertical AI shows capital efficiency early, emerging leaders are still raising SaaS-era amounts of capital (with a few exceptions, like Jane). Will changing post-LLM burn needs reshape the growth-stage landscape going forward? Link to the full Q2 analysis here... And roundup of deal highlights in comments below 👇 https://lnkd.in/g_enwmSn

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