The Blink Edition No. 14

The European private markets briefing you can't afford to miss. Deals, signals, and moves, decoded every Monday by SeedBlink.

AI has made building a product dramatically cheaper. Which raises an obvious question: if everyone can build, where does the advantage go?

My answer is execution. AI does not build your whole product, it does not run your business, and it does not find your distribution channels. And you cannot leave it alone.

Think of it as an employee. Extremely hardworking, knows a great deal, has an enormous memory. It also lies with complete confidence and is thoroughly unpredictable. Would you keep someone like that? Every leadership book says you let them go the next morning. So why would anyone let it run a business unsupervised?

That does not make the tools less valuable. It means the scarce thing is no longer the ability to produce something, but the ability to run a company around it.

This matters to me in a very specific way. Most of what I have built was built in Romania, where strong technical talent has always been the easiest thing to find. Business strategy, management and commercial execution were harder, and I put myself at the front of that line. Which means AI is commoditising exactly the thing we were best at, and raising the value of the thing we built least.

Ideas were never the hard part. AI has simply made it harder to pretend otherwise.

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If AI has made building cheaper for everyone, one place to look for the consequence is how companies sell.

The 2026 Aleph and Benchmarkit benchmarks, covering 342 B2B SaaS and AI-native companies, offer a useful snapshot. Among the 198 that reported the metric, the median company recovered the cost of acquiring a customer in 16 months across 2025, an improvement on the year before. The spread is another story: the top quartile recovered that cost in six months or less, the bottom quartile in 24 months or more. Deal size explains part of the gap, since smaller contracts pay back faster than enterprise ones, but the report's own reading is that a payback period which looks fine is quietly becoming a competitive disadvantage.

The benchmark does not show that AI caused this. What it shows is consistent with a world in which execution matters more: the median looks healthy, while the distance between companies that sell and operate well and those that don't keeps widening. When more companies can build credible products with similar tools, product alone becomes less decisive, and the rest of the business has to carry more of the weight.

For Europe, that is an uncomfortable prospect. The continent's institutional strengths have often been more visible upstream, in research, technical talent and public innovation infrastructure, than in commercialisation and scaling. The European Commission's 2026 Innovation Scoreboard shows a relatively strong EU research and innovation base, and at a European Economic and Social Committee debate on the scaling gap in May, one speaker noted that only one in three university patent applications is successfully commercialised. Several speakers agreed that Europe's main problem is not generating ideas but scaling them.

AI does not fix that. If anything, it removes one of the things that used to buy time: the difficulty of building something at all.

For investors, the practical shift is in where diligence spends its hours. A strong product increasingly looks like the entry ticket rather than the differentiator. The question worth asking earlier and harder is who in the company can actually sell it, and how its numbers compare with the companies pulling away.
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From MVP to first customers

Two of our team, Andrei Dudoiu (CEO) and Bogdan Stoian (Head of Investment Syndication), have joined the mentor lineup for the Rubik Hub MVP Accelerator, open to Romanian and Italian founders.

Building an MVP has rarely been easier, and everything after it has become correspondingly harder. The programme focuses on that part: customer validation, pricing, and preparing for a pre-seed round.

Read more about the programme.
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Italy 🇮🇹
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Exein raises $270M

Rome-based Exein raised $270M led by Headline at a $1.7B valuation, making it Europe's most valuable cybersecurity startup at thirty times its valuation of two years ago. Its software runs at the kernel level of more than two billion connected devices, and the bet now is on securing robots, vehicles and drones as AI moves into physical machines.

Read more

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Finland 🇫🇮

Verda raises $189M Series B

Helsinki-based Verda, formerly DataCrunch, raised $189M led by Emergence Capital at a valuation of at least $1B. Its annualised revenue run rate reached $165M in July, up from over $60M at the time of its April round, as it expands the data centres, hardware and software of a full-stack European AI cloud.

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Romania 🇷🇴
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FintechOS raises $28M
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The Romanian-founded company raised $28M in equity from existing investors and a senior debt facility from Santander CIB, after turning profitable in the first half of the year with recurring revenue up 40% and US revenue up 130%. The debt is itself the signal: bank lending became available because the profit line did.

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Product management is still all about telling stories
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a16z's Josh Elman, formerly at LinkedIn and Twitter, on what AI changes in building products and what it leaves untouched: the cost of making things has collapsed, the cost of judgment has not. Demos are almost free now, he writes. Working products are not.

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Europe at "acute risk of marginalisation" without billions in AI investment

‍A new report co-authored by Nobel laureate Philippe Aghion and former Commission executive vice-president Margrethe Vestager calls on Europe to commit €100 billion to data centres, tripling its share of global computing capacity from 5% to 15% by 2030, and to attract €1.5 trillion in private investment alongside it.

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The mega-million dollar customer

Kyle Harrison on why the logo wall is the wrong way to judge a startup. Across the 39 software companies that publish it, net dollar retention alone explains around 56% of the variation in revenue multiples, and AI's thinner margins mean a company needs roughly 1.5 times the contract value to keep what a SaaS business keeps.

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