Ion Hauer is a principal at APEX Ventures, a European early-stage fund investing in deep tech across advanced computing, robotics, space, energy and medical.
What led you to venture capital and APEX Ventures?
I started as a quantum physicist. I did my PhD at Heidelberg University and focused on how the world functions through fundamental research. I quickly realized I didn’t want to stay in academia, so I switched to management consulting with Oliver Wyman, where I learned about finance, strategy and how to act in a boardroom.
After three years, I wanted to be more accountable for outcomes rather than just giving advice, so I joined the BSH Startup Kitchen, a venture client unit within the Bosch Group. We evaluated thousands of startups and ran 30 to 40 proof-of-concept projects annually, with about 40 percent leading to continued business relationships. That’s where I really got into startups and began angel investing.
I became COO at one of my angel investments, GlassDollar, helping them grow revenue, structure operations and raise funding. By late 2022, I wanted to return to deeper technologies like lasers, semiconductors and space. I started raising my own deep tech fund and along the way met APEX, who were doing exactly what I envisioned. They’d been at it for eight years with a bigger fund than I could dream of raising alone. So two and a half years ago, I joined forces with them.
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What is APEX Ventures’ investment thesis?
We invest at an early stage, typically up to 2 million euros in companies at technology readiness level 3 or above. These companies are quite early, often in pre-product or pre-revenue. We focus on advanced computing, robotics, space, energy and medical technologies. We’re a team of scientists and engineers with deep technical DNA, which gives us an edge in evaluating defensible IP.
What differentiates us starts in the screening call. Founders regularly tell us no other investor has asked such deep technical questions or engaged with their white papers. We do all due diligence in-house without outsourcing. We challenge founders to think beyond technology to market perspectives, go-to-market strategies and unit economics.
We actively help founders build networks early, connecting them with industry leaders during due diligence. We’re happy to lead rounds when needed and always aim to build strong syndicates with complementary investors. We know our fund size is limited and we’ll need bigger growth investors later, so we actively help with fundraising for current and follow-on rounds.
What advice do you have for technical founders entering the commercial world?
Start networking six to 12 months before spinning out and fundraising. Identify the industry leaders who really move the needle in your domain. Use LinkedIn to find them through mutual connections. There’s no excuse not to do this early.
You don’t need to start with the CEO of NVIDIA. Find people below that level who have more capacity and openness to talk. Most people are surprisingly willing to share their work and perspectives. You don’t need to bring value to them immediately. Just ask questions.
Use these conversations to test your ideas. Say “I’ve been working on this in your domain. What do you think? Does it solve an interesting problem?” Since you’re not asking for money or commitments, they can give honest feedback. When you later talk to investors and they ask about certain industry figures, you’ll already have those relationships and insights.
Why has quantum computing become a focus for investment?
Several factors have converged. First, the technological advancements of recent years have been tremendous. While Richard Feynman conceived quantum computing in 1982, having physical qubits you can manipulate and couple together in arrays is fairly new. Research groups have done crucial work over the past 15 years that’s now ready for commercialization.
Second, there’s massive public attention and funding. Every nation has a quantum strategy with billions in funding globally. This government support makes commercialization more viable.
Most importantly for VCs, the timeline is much shorter than, say, fusion. While fusion is perpetually 30 years away, quantum in my opinion is three to six years from doing something useful. Quantum has a smoother trajectory where you can show incremental value early. You might be only slightly better than classical computing initially, but as problems grow, the advantage diverges exponentially. This allows for earlier exits through secondaries or acquisitions, which we’re already seeing with deals like IonQ acquiring Oxford Ionics.
Lay out the quantum technology landscape?
There are three main buckets: quantum computing, quantum communication and quantum sensing. Within quantum computing, you can break it down into a stack. Some companies build full-stack quantum computers end-to-end. Others focus on specific layers like algorithms, control systems for stabilization, or electronic design automation for qubit architecture.
We’ve invested in Planqc, a Munich-based full-stack quantum computing company using neutral atoms, which is one of the most promising modalities. We made that big bet because, like in classical semiconductors, it’s often better to own as much of the value chain as possible rather than being just a component provider.
We also invested in Kiutra, which builds cryogenic refrigeration systems for cooling quantum chips. They’re solving the critical problem of cooling without expensive helium-3. It’s a “picks and shovels” infrastructure play supporting others building quantum systems.
Where will we see quantum advantage first?
I believe it will be in simulating actual quantum systems like quantum chemistry or drug discovery involving protein folding and chemical structures. That’s what quantum computing is naturally suited for. The challenge with drug discovery is the 10-year feedback cycle before reaching the market.
Material science offers faster feedback loops. You can simulate new materials for batteries or coatings, synthesize them in the lab and quickly determine if they work. The simulation-to-validation cycle is much shorter.
Other use cases like financial modeling or logistics optimization are possible but harder. You have to encode classical problems into quantum architectures, which is less natural than simulating molecules whose energy levels map directly onto quantum systems.
How do you define deep tech?
Deep tech requires a scientific or engineering breakthrough, typically evidenced by defensible intellectual property. This doesn’t always mean patents, though they help. Deep tech is easier to identify in hardware than software.
The key is uniqueness of insight. In deep tech, maybe five to 10 teams globally can execute on the idea. In regular tech, thousands could do it, and success depends more on go-to-market execution, marketing and pricing.
It’s not binary. We often debate the degree of “deepness” of a technology. Sometimes it’s obvious, sometimes borderline. But it always comes back to the defensibility and uniqueness of the insight that very few others possess globally.