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European tech activity in March 2026 eased slightly compared to February, while overall market conditions remained stable.

The ecosystem recorded 292 funding deals and €7.5 billion raised, down marginally from 296 deals and €7.8 billion in February, reflecting declines of 1.4 per cent and 3.8 per cent respectively.

At the country level, a more significant shift was observed. UK funding fell to €2.6 billion from €3.8 billion in February, a 31.6 per cent decrease, indicating lower capital concentration month-on-month.

Sector trends also evolved, with AI leading in March at €1.8 billion, compared to transportation in February at €1.5 billion, signalling a rotation of capital toward artificial intelligence and related technologies.

Tech.eu’s Cate Lawrence commented on the March numbers within the European tech investment landscape in our March Tech.eu Pulse, a compact version of the monthly report:

European tech in March 2026 looked less like a market pulling back and more like one settling into a new rhythm. AI (albeit ubiquitous across sectors) attracted €1.8 billion and is overtaking other sectors as the primary destination for capital. At the same time, large rounds continue to account for a disproportionate share of total funding, pointing to sustained conviction in companies building core infrastructure, from compute to platforms that underpin entire industries.

There are also some notable geographic shifts. The UK remains the dominant market despite a sharp drop in funding, while France, Sweden, Germany, and the Netherlands continue to form the backbone of European dealmaking.

Beyond these, a broader mix of countries is starting to appear more consistently, suggesting the ecosystem is widening rather than further concentrating.

For her more detailed review and more in-depth analyses of the European tech ecosystem, including industry and country performance, exit activities, and more, check out our March report.

Here are the 10 largest tech deals in Europe from March, accounting for 62.7 per cent of the month’s total funding.

Amount raised: $2B Nscale is a London-based AI infrastructure company that builds and operates vertically integrated GPU cloud platforms, combining data centres, high-performance computing, and software to enable large-scale AI model development, training, and deployment. It provides enterprises and governments with scalable, energy-efficient compute capacity and end-to-end tools designed to support the growing demands of advanced AI systems. In March, Nscale raised $2 billion in a Series C funding round, valuing the company at $14.6 billion.

Amount raised: $1B AMI (Advanced Machine Intelligence) is a frontier AI research lab developing a new class of systems that understand and interact with the real world. It focuses on building “world models”, AI that can reason, plan, and operate safely across complex physical environments, with applications in areas such as robotics, healthcare, and industrial systems. Founded by a global team of leading researchers and engineers, the company aims to advance reliable, controllable AI and enable real-world intelligence beyond traditional language-based models. AMI raised more than $1 billion in what it describes as Europe’s largest-ever seed funding round.

Amount raised: $830M Mistral AI is a Paris-based AI company founded in 2023 that develops high-performance, open-weight large language models and enterprise AI systems, enabling organisations to build, customise, and deploy advanced generative AI and autonomous agents. The company focuses on combining strong model performance with openness and efficiency, offering scalable AI solutions for both developers and large enterprises. Mistral secured $830 million in debt financing to acquire Nvidia chips for its initial data centre.

Amount raised: $550M Legora is a Sweden-based legal AI company developing a collaborative workspace that helps lawyers automate tasks such as document review, research, and drafting, integrating both public and proprietary data to streamline legal workflows and improve productivity. The platform is designed to support legal professionals across law firms and in-house teams, enhancing efficiency while maintaining accuracy and control over complex legal processes. Legora raised $550 million in Series D at a $5.55 billion valuation to accelerate US expansion.

Amount raised: $225M Kandou is a fabless semiconductor company that develops high-speed, energy-efficient chip-to-chip connectivity solutions used in advanced computing and data infrastructure. Its technology focuses on enabling scalable, cost-efficient AI and data centre systems by improving how processors, memory, and networks communicate, helping reduce power consumption while increasing performance. Kandou AI closed a $225 million Series A round to break memory bottlenecks in AI.

Amount raised: €180M PLD Space is an aerospace company that designs, manufactures, and operates reusable rockets to provide reliable and cost-effective launch services for small satellites. Founded in 2011, the company develops its MIURA family of launch vehicles to enable flexible access to space, positioning itself as a key player in Europe’s emerging commercial space sector. PLD Space raised €180 million in Series C equity funding to scale satellite launch infrastructure.

Amount raised: $170M 9fin is a fintech company that provides an AI-powered data and analytics platform for debt capital markets, combining real-time news, financial data, and predictive insights to help credit professionals analyse deals and make faster, more informed decisions. The platform is used by investment banks, asset managers, and law firms to streamline workflows and improve transparency across leveraged finance and credit markets. 9fin raised $170 million, reaching a $1.3 billion valuation.

Amount raised: $150M Wonderful is an enterprise AI agent platform that enables organisations to build, deploy, and manage AI agents across customer-facing and internal workflows, helping integrate AI directly into core business operations. The platform provides a unified infrastructure for creating, monitoring, and optimising agents at scale, supporting complex, multilingual, and compliance-driven environments across global markets. Wonderful received a $150 million in a Series B funding round, reaching a valuation of $2 billion.

Amount raised: €113.8M Iron Fuel Technology (developed by RIFT) is a cleantech energy solution that uses iron powder as a circular, carbon-free fuel to generate high-temperature heat for industrial processes and district heating. The system works like a rechargeable energy carrier: iron powder is burned to produce heat without CO₂ emissions, leaving iron oxide that is then regenerated using hydrogen and reused, enabling a closed-loop, scalable alternative to fossil fuels. RIFT has secured €113.8 million in combined financing (Series B and EU grant) to advance its Iron Fuel Technology from pilot projects to commercial deployment and to develop its first commercial production facility.

Amount raised: $125M Upvest is a fintech infrastructure company that provides banks, brokers, and fintechs with a unified, API-based platform to build and scale investment products, including trading, custody, and back-office services. Its technology enables businesses to offer seamless, cross-border investment experiences, such as stock and ETF trading, savings plans, and fractional investing, while handling the underlying regulatory and operational complexity. Upvest secured a $125 million financing round to support the modernisation of legacy banking systems across Europe and the UK.

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Verne today announced the launch of Europe’s first commercial robotaxi service, starting in Zagreb, Croatia.

Beginning today, members of the public can now book and pay for a Pony.ai-powered autonomous ride through the Verne app.

The service will soon also be available through the Uber app, following a recently announced strategic partnership between the three companies.

The commercial service is the result of several years of development and close collaboration with regulators, positioning Verne among the leaders of autonomous mobility in Europe.

“For the first time in Europe, there is a real commercial robotaxi service. People can use it and take real autonomous rides,” said Marko Pejković, co-founder and CEO of Verne.

“We said we would launch in Zagreb in 2026. Today, we did. This is just the start.”

Start of service in Zagreb

The initial commercial deployment will use electric vehicles equipped with Pony.ai’s seventh-generation autonomous driving system.

These vehicles ​will ​operate autonomously, with trained autonomous vehicle operators onboard during the early phase of the rollout.

The initial service zone covers key districts of the Croatian capital, with plans to expand coverage across the city.

The companies aim to transition to fully driverless operations as soon as possible, subject to regulatory approvals and the service meeting the required safety and reliability standards.

From Zagreb and beyond

Verne has begun permitting discussions with 11 cities across the EU, UK, and the Middle East, with more than 30 additional cities currently under consideration.

Verne​​ ​​ will also eventually deploy the company’s purpose-built autonomous vehicle, a two-seat robotaxi designed specifically for driverless ride-hailing.

From EasyMile to Einride, and now Verne: Europe’s autonomy stack evolves

Verne marks a shift from earlier paths to vehicle autonomy in Europe. Until now, one of the region’s most prominent players has been the French company EasyMile, which was the first to offer a fully driverless L4 autonomous shuttle, the 12-seater EZ10, across locations such as business parks, campuses, and commercial roads. EasyMile operates throughout Europe, including autonomous shuttles operational on public roads in Bad Birnbach, Monheim am Rhein, and Munich in Germany, as well as Toulouse, France.

Earlier this year, the company announced a strategic pivot to heavy-duty applications for airports and industrial sites. The company is focusing on software licences for these markets, where it considers autonomy is commercially viable today, with growing deployments and a clear path to scale for heavy-duty vehicles that transport parts, goods, baggage, cargo etc. on airports and industrial sites.

In parallel, German autonomous trucking company Fernride develops human-supervised autonomous trucking systems used in container terminals, industrial yards and defence logistics, retrofitting existing vehicles with AI, sensors and software to automate repetitive transport tasks. Its technology has already been deployed in real-world operations and, in 2025, it became the first company to receive TÜV approval for autonomous trucks in Europe.

The company was acquired by Quantum Systems in late 2025 as part of a broader push to build a multi-domain autonomy stack spanning air and ground systems.

Meanwhile, Swedish-founded Einride deploys electric fleets and its driverless “Pod” vehicles, which can operate autonomously or be remotely controlled by human operators when needed. Alongside its hardware, the company runs a digital platform that plans routes, manages charging, and optimises deliveries, positioning itself less as a truck manufacturer and more as a software-driven freight operator. Already working with companies like Maersk and Oatly, Einride is part of a broader shift toward cleaner, more automated, and data-driven supply chains.

In September last year, Einride completed the first successful European cross-border operation of a cableless electric autonomous vehicle without a human driver onboard.

Against these efforts, in January, US company Waymo announced its intention to launch a fully driverless ride-hailing service in London by the fourth quarter of 2026. The company will soon begin conducting extensive trials of Waymo’s technology as part of our mapping and safety validation work across select boroughs in London. Testing hours typically run 24 hours a day, 7 days a week, to ensure its technology can safely handle all of London’s road conditions.

Teledriving as an alternative path

In commercial passenger transport, Estonia’s Elmo and Germany-founded Vay pioneered a different approach to vehicle automation, using teledriving to bring vehicles to users before switching to manual control for the trip itself.

Using an app, users can request the delivery of an electric vehicle to their location. After the car arrives, the user takes over and drives it like a regular car. 

At the end of the trip, the user ends the rental in the app, exits the car, and a remote driver takes over, eliminating the time-consuming search for parking. 

Combined, these approaches highlight a fragmented but interconnected approach to vehicle automation in European mobility, which straddles controlled environments and industrial use cases against complex urban settings.

The London startup emerged from stealth on 7 April with a layered agentic security solution and a seed round backed by LocalGlobe and Cambridge Innovation Capital. Its co-founders include a Cambridge professor who was previously Amazon’s director of machine learning. Trent AI, a London-based agentic security company, has raised $13 million in a seed round […]

In short: Uber has expanded its AWS contract to run real-time ride-matching infrastructure on Amazon’s Graviton4 processor and is piloting AI model training on Trainium3, joining Anthropic, OpenAI, and Apple on a customer list that is becoming the clearest evidence yet that Amazon’s custom silicon strategy is working. Uber’s infrastructure runs on milliseconds. Every time a […]

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Fund VI ($720M) targets early-stage companies in robotics, manufacturing, and energy. Early Growth Fund III ($591M) supports companies scaling toward Series A. Total AUM is now approximately $10 billion. Eclipse, the Palo Alto-based venture firm that backs companies rebuilding physical industries, has closed $1.3 billion across two funds simultaneously. Eclipse Fund VI has raised $720 […]

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Eilla AI has completed Europe’s first M&A deal executed by an AI-native advisory firm, advising on the acquisition of two Central and Eastern European digital marketing agencies, CreateX and Native Digital, by Swedish listed company White Pearl Technology Group.

Its proprietary technology, built in-house over three years, combines AI infrastructure with experienced M&A advisors who oversee AI-generated work, manage transaction processes, and coordinate communication between both sides.

I spoke to Petar Petrov, Chief Commercial Officer and co-founder of Eilla AI, to learn more.

A shift driven by a lagging industry and an underserved market

Eilla AI was founded in 2022. Initially, it was selling AI tools to the M&A industry. Over the past year its spoken to more than a thousand M&A firms and private equity funds.

According to Petrov, two things became clear. First, the M&A industry is quite behind in terms of AI adoption — “even large boutiques were only just integrating tools like ChatGPT internally,” he shared. Second, the SMB segment is underserved. The team decided to combine the AI it has built with the expertise of experienced advisors. According to Petrov:

“We partnered with our Head of M&A, Dmitry, a senior investment banker with over 13 years of experience at firms like Jefferies and Citibank.”

Eilla AI’s customer is typically the founder or owner of an SMB business looking to sell. 

What “AI-native advisory” means in practice

Eilla AI’s technology enables it to reach hundreds of high-fit buyers across multiple countries within days, each with messaging built on in-depth research into what makes the acquisition compelling for that specific buyer. 

Eilla AI runs a structured process similar to what top-tier investment banks use, but applied to the SMB market. The AI handles large parts of the workflow, but humans step in where full automation isn’t yet reliable — especially for customisation and judgement.

First is preparation. It identifies a broad universe of potential buyers — often larger in SMB deals, where smaller companies attract a wider range of acquirers.

“We use AI to identify these buyers. Eilla has built a large proprietary database with detailed information on companies, and uses AI to identify the right buyers from that database based on similar deals and synergies,” explained Petrov.

Eilla uses its AI automations to build key materials, including the confidential information memorandum (CIM), the core document used to present the business to potential buyers. 

“Traditionally, this process can take one to two months. We can do it in a few days.”

Next is outreach. While the company utilises its existing relationships, it also deploys highly personalised outreach to new buyers. It built a database of around nine million companies, tracking their products, tech, and other signals. This enables it to send highly tailored messages at scale, resulting in higher response rates.

“The goal is to create competitive tension — ideally by arranging five to ten meetings,” explained Petrov.

Buyers then submit non-binding offers, which are reviewed with the client before moving into due diligence. Due diligence is usually the longest stage — one to two months — and depends on multiple parties.

Where AI stops, and judgment begins

Petrov emphasised that humans remain in the loop, particularly in judgment-heavy tasks such as responding to buyers. While AI drafts outputs based on available data, all materials are reviewed by humans and given final approval.

“These are judgment calls — what to include, what to emphasise. AI can assist, but humans make the final decision.”

Eilla AI is already seeing early traction in both deal speed and buyer reach. One recent transaction moved from outreach to non-binding offers in around 15 days, with the full process completing within a few months — despite involving multiple companies, shareholders, and a non-obvious buyer. According to Petrov: 

“It was a complex deal — multiple companies, multiple shareholders, and a buyer that wouldn’t normally be identified through traditional relationships.”

Rather than relying on existing networks, the firm identified the buyer through pattern matching at speed against previous acquisitions, surfacing a publicly listed Swedish company that would likely have been missed in a traditional process.

Nikola Lazarov, CEO and co-founder, contends that this pace and depth would be impossible to replicate without the infrastructure it has built. 

“Our work with CreateX and Native Digital is not just proof of concept. It is a completed deal.”

The founders of both acquired companies credited Eilla AI with making the transactions possible.

“Honestly, without Eilla, this deal would not have happened,” said Aleksandar, founder and CEO of CreateX.

The reaction from Native Digital was similar.

Early traction across deal speed and buyer reach

Adoption of AI in M&A is still in its early stages, particularly in a sector long defined by relationships and traditional processes. For Eilla AI, client response tends to fall into two distinct categories, according to Petrov.

The majority of its clients come through its automated sourcing using AI rather than referral. 

“They typically need to see the technology — once they do, the reaction is generally very positive.”

Some clients come through referrals and already understand the process. 

“For them, we demonstrate how we’re different.“

While M&A remains relationship-driven, Petrov argues that this model has clear limitations, particularly in the lower and mid-market segments.

“Relationships only take you so far. A typical advisor might know 10–20 relevant buyers. In SMB deals, the real buyer universe is much larger.”

Instead of relying on a narrow pool of known acquirers, Eilla AI’s approach is designed to expand buyer discovery and increase competitive pressure within deals.

“We focus on creating competitive tension, rather than running bilateral processes with just one buyer. That’s a key advantage.” 

Eilla AI’s models are probabilistic, and the system does not rely on generic model outputs or training data alone. Instead, it works with structured context provided by the client, combined with data extracted from proprietary databases and licensed external sources — including a dataset built from tens of millions of scraped pages covering around nine million companies. Petrov explained:

“Importantly, everything is reviewed by humans, and critical information is validated with the client. The goal is not to replace people, but to make one person as effective as a much larger team.”

When software becomes the service

Eilla AI’s model reflects a broader shift already underway in the US.

Firms including General Catalyst, Founders Fund, Sequoia, a16z, YC, Blackstone and others have converged on a shared thesis: the next generation of category-defining companies won’t sell software to professional services firms — they will become them.

Across legal, accounting, insurance and consulting, over a billion dollars has been deployed into companies that own the outcome rather than sell the tool.

General Catalyst committed $1.5 billion to acquiring traditional service businesses and rebuilding them with AI. Sequoia and a16z co-led $108 million into Rillet, an AI-native accounting firm. Emergence Capital led a $47 million round into Harper, an AI-native insurance brokerage. Lawhive, an AI-native law firm, raised $60 million on the back of 7x year-on-year revenue growth. 

Sequoia partner Julien Bek crystallised the thesis in a widely circulated essay earlier this month titled “Services: The New Software.” His core argument: for every dollar spent on software, six dollars are spent on services. He contends that the next trillion-dollar company, he wrote, will be a software company masquerading as a services firm.

Scaling M&A for the long tail of businesses

The deal executed by Eilla AI arrives at a moment of acute structural pressure on the European M&A market. The European Commission estimates that a third of EU entrepreneurs will exit their businesses over the coming decade, putting roughly seven million businesses and 30 million jobs at risk. 

In Germany alone, 626,000 businesses plan to transfer ownership by 2027. Traditional boutique advisory firms cannot economically serve the vast majority of these transactions. A proper sell-side process requires hundreds of hours of work, and for deals below a certain size, the fees do not cover the cost of running that process properly. The result is a market where most business owners either cannot access quality advisory or receive a diminished version of it.

Eilla AI’s cost structure is fundamentally different. Because AI handles the volume-intensive work, buyer sourcing, outreach and document creation, the firm operates on a success-fee-only basis with no retainers. 

A model already proving out globally

The pattern has a precedent. In Japan, Shunsaku Sagami built M&A Research Institute to address a similar succession crisis, using AI to compress deal timelines from over 12 months to an average of 6.2 months. The company is now publicly listed, and Sagami, at 33, became Japan’s youngest billionaire. In the United States, OffDeal raised $17 million to build an AI-native investment bank. 

Eilla AI launched its advisory practice at the end of last year and now has around 20 active mandates, with a fee pipeline of approximately €20 million — up more than 15-fold from roughly €1.6 million at the start of the year. M&A advisory is inherently transactional, raising questions about how firms build sustainable businesses without recurring revenue.

For Petrov, the answer lies in deal size, volume, and execution. Rather than relying on repeat subscriptions, the model is driven by the economics of individual transactions.

“In our segment, average deal sizes are around €10–20 million, and we charge about a 5 per cent success fee. So a single deal might generate around €500,000.”

Petrov argues that long-term strength comes not from recurring revenue, but from consistently generating and closing deals.

“You don’t need recurring revenue to build a strong business — you need deal flow and execution.”

AI plays a role not only in deal execution, but also in sourcing opportunities, while brand becomes increasingly important over time. Across its processes so far, Eilla AI reports that around 80 per cent of companies reach the stage of presenting to buyers, suggesting a higher level of early-stage engagement.

“In one case, a company that previously secured one NDA with a traditional advisor reached nine NDAs using our process.”

Although the M&A practice only launched at the end of last year, the company says momentum is building quickly as more deals move through the pipeline. 

"We’re still early, but we’re already seeing strong momentum.”

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