European AI Venture Strategy and Market Gaps
An analysis of Merantex's investment thesis for the European AI ecosystem, highlighting the critical gap in B2B adoption speed and capital efficiency. The discussion covers the shift toward application-layer AI, the strategic importance of sovereign solutions, and the emerging role of world models in industrial automation.
The European AI Investment Gap
The European AI venture ecosystem faces a structural challenge: a significant disparity in capital deployment and adoption speed compared to the United States. While the US saw approximately $250 billion in AI investments in 2025, Germany allocated only $2 billion to AI startups. This gap is not merely a funding issue but a systemic one, rooted in the slower decision-making processes of traditional European industries. Rasmus Rothe, Co-Founder and CEO of Merantex, identifies that German B2B sales cycles often extend to 12-18 months, whereas US counterparts decide within weeks. This friction slows revenue growth for startups, making subsequent fundraising rounds more difficult and limiting the scale of European AI companies.
Strategic Focus on the Application Layer
Merantex’s investment thesis centers on the "application layer" of AI, predicting that the next decade will be defined by the integration of AI into specific verticals rather than general-purpose infrastructure. The firm targets B2B sectors such as FinTech, Cybersecurity, Life Sciences, and Industrial Manufacturing, where domain expertise combined with AI capabilities can create defensible market positions. The strategy involves early-stage, pre-revenue investments, allowing the firm to identify high-potential teams before market saturation. By incubating 20-30 teams annually, Merantex aims to create companies that might not otherwise exist, leveraging their network to connect founders with industry stakeholders and regulators.
Sovereignty and Product Quality
A critical insight from the discussion is the reality of "sovereign AI." While there is political and corporate desire for European-controlled AI solutions, customers will not adopt inferior products for the sake of sovereignty alone. Rothe emphasizes that European firms must achieve product parity with US competitors to succeed. The focus must remain on building superior, efficient solutions that solve specific business problems, rather than relying on regulatory protection or national identity as a value proposition. This pragmatic approach ensures that European AI companies remain competitive in a global market.
Emerging Technologies and Future Trends
The conversation also highlights the rising importance of "world models" in AI development. These models allow AI agents to simulate physical interactions, reducing the cost and risk of training robots and autonomous systems in the real world. Additionally, the role of AI in scientific discovery, particularly in biology and chemistry, is seen as a major upcoming trend. As hardware constraints remain a limiting factor, the focus on efficient algorithms and new architectures will be crucial for the next phase of AI advancement. The shift toward generalist founders with strong business skills reflects the changing nature of AI entrepreneurship, where commercial execution is as vital as technical innovation.
Key insights
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The primary barrier to European AI growth is not a lack of talent or capital, but the slow adoption rate of traditional B2B industries. Long sales cycles in Germany and Europe prevent AI startups from achieving the rapid revenue growth needed to scale and attract further investment.
Impact: Addressing this friction through faster procurement processes and pilot programs could unlock significant value for European AI startups, allowing them to compete more effectively with US counterparts.
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The investment opportunity in AI is shifting from foundational models to vertical-specific application layers. The next decade will see value creation in industries like healthcare, finance, and manufacturing, where AI is integrated into specific workflows rather than offered as a generic tool.
Impact: Venture capitalists and founders should focus on deep domain expertise and specific use cases to build defensible businesses, rather than competing on general-purpose AI capabilities.
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Sovereign AI initiatives will only succeed if the products are competitively superior or equal to US alternatives. Customers are unwilling to switch to inferior European solutions solely for geopolitical or regulatory reasons, making product quality the paramount factor for adoption.
Impact: European AI companies must prioritize performance and user experience over national branding to ensure market penetration and long-term sustainability in a globalized tech market.
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World models are becoming a critical technology for physical AI, enabling the training of robots and agents in simulated environments. This reduces the cost and risk associated with real-world testing, accelerating the deployment of AI in robotics and industrial automation.
Impact: Companies investing in world models will have a significant advantage in deploying AI in physical spaces, opening up new markets in logistics, manufacturing, and autonomous systems.
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The ideal AI founder profile is evolving from a technical specialist to a generalist with strong commercial and interpersonal skills. As AI tools automate coding and technical tasks, the ability to build a business, attract talent, and navigate complex B2B sales cycles becomes the key differentiator.
Impact: Investors should look for founders with a balanced skill set, emphasizing business acumen and leadership, to ensure that technical innovations are successfully commercialized and scaled.
Action items
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Accelerate B2B sales cycles by implementing agile procurement processes and pilot programs in traditional industries. This involves reducing bureaucratic hurdles and encouraging risk-taking in AI adoption to match US market speeds.
Impact: Faster sales cycles will improve revenue predictability for AI startups, making them more attractive to investors and enabling faster scaling in the European market.
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Focus investment and development efforts on vertical-specific AI applications in high-value industries such as FinTech, Cybersecurity, and Life Sciences. Avoid competing in the general-purpose AI infrastructure space, which is dominated by hyperscalers.
Impact: Targeting specific verticals allows for deeper integration and higher customer retention, creating defensible market positions that are less susceptible to competition from large tech companies.
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Prioritize product quality and performance in sovereign AI solutions to ensure customer adoption. Do not rely on regulatory mandates or national identity as the primary value proposition; instead, demonstrate clear competitive advantages in functionality and efficiency.
Impact: High-quality products will drive organic adoption and customer loyalty, ensuring the long-term viability of European AI companies in a global market.
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Invest in and develop world models for physical AI applications, particularly in robotics and industrial automation. This technology enables safer and more cost-effective training of AI agents in simulated environments before real-world deployment.
Impact: Leveraging world models will accelerate the commercialization of physical AI, opening up new revenue streams in sectors where real-world testing is expensive or risky.
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Recruit and support founders with strong commercial and interpersonal skills, rather than solely technical expertise. As AI tools automate technical tasks, the ability to build a business and navigate complex sales cycles becomes the primary driver of success.
Impact: Founders with balanced skill sets are better equipped to commercialize AI innovations and scale their businesses, leading to higher success rates for AI startups.
Quotes
“In den USA wird es auch noch weiter wachsen. Ich glaube, wir müssen einfach gucken, dass der relative Abstand nicht größer wird.”
“Die US-Kunden viel schneller größere Tickets lösen bei den Startups. Und das gibt mehr Umsatz. Und das wiederum macht Finanzierungsrunden einfacher.”
“Ich glaube, das Ziel sollte immer sein, gleich gute oder bessere Produkte anzubieten.”