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The post Weekly funding round-up! All of the European startup funding rounds we tracked this week (Oct. 13-17) appeared first on EU-Startups.

Copenhagen-based Jabbr.ai, an AI analytics innovator for combat sports, has announced a €4.3 million Seed round to accelerate their mission of becoming the ‘de facto’ OS for combat sports – bringing Silicon Valley-grade AI to an industry “still reliant on 1980s tech“.

The round led by Buckley Ventures, the fund of Josh Buckley, with participation from Seven Seven Six, the fund by Alexis Ohanian (Reddit), John Zimmer (Lyft), and Olympic gold medalist Andre Ward, alongside early backers like PSV Tech.

“Jabbr is basically a plug-and-play streaming and transparent live-scoring solution for combat sports. We let users record and live-stream all their fights and sparring, complete with highlights, stats, AI live scoring, and overlay graphics. It’s like a professional TV production, except better and at a 100x cost reduction,” said Allan Svejstrup, CEO.

Jabbr’s Seed round places it within a broader 2025 trend of European startups combining AI, computer vision, and sports technology.

Across the continent, funding rounds of similar scale have emerged – such as ReSpo.Vision’s €4.2 million to enhance football tracking and ScorePlay’s €12.5 million Series A for AI-driven media automation.

Smaller but notable raises include SponsWatch’s €1 million Seed in Sweden for AI-based sponsorship analytics, Sports Impact Technologies’ €650k pre-Seed in Ireland for impact detection wearables, and Model Health’s €800k pre-Seed in Belgium for video-based movement analysis.

Together, these rounds indicate steady investor confidence in AI-powered sports analytics and media automationacross Europe. While most focus on football, general sports performance, or content management, Jabbr distinguishes itself by targeting the combat sports segment, merging automated video production, real-time scoring, and analytics into one platform.

With backing from Silicon Valley and sports-industry investors, the company’s position reflects both technological maturity and recognition of an underserved market within sports tech.

Alexis Ohanian, Reddit Co-founder and Founder of VC firm Seven Seven Six, has seeded AI pioneers like Flock Safety and with founding control owner of Angel City FC, the most valuable women’s soccer team in the US adds: “I back Founders who break old systems. Jabbr isn’t just disrupting – it’s rebuilding the sweet science from the ground up.”

Founded in 2022, Jabbr is an AI startup building the future of combat sports. After years of R&D, Jabbr built the world’s first computer vision AI dedicated to combat sports: DeepStrike.

DeepStrike tracks every punch, block, and movement in realtime to deliver automated highlights, accurate analytics and transparent judging to the world. Since its public release Deepstrike has been trusted on the world’s largest stage, debuting its signature stats and highlights to millions on DAZN and TNT Sports. ​

EU-Startups previously covered Jabbr’s €685k Seed funding in 2023.

Lyft co-founder John Zimmer, who has long championed tech that increases access to opportunity, adds: “This is bigger than stats and video. It’s leveling the playing field, increasing accountability and giving fighters all over the world a fair shot.”

While other successful startups like VEO changed football by giving every club and team access to pro-grade video streaming and analytics, Jabbr targets combat sports’ €1.7 billion analytics and content creation gap. Their proprietary computer vision AI watches the fight like a coach, scores it like a judge, and produces it like a broadcast crew, automating streaming, highlights, stats, scoring, and overlays in real time.

Josh Buckley, whose early bets include Applied Intuition and AI safety pioneer Flock Safety, foresees how Jabbr: “seamlessly integrates hardware, software, and AI to create a new category experience for combat sports. Much like how Twitch unlocked a community-driven revolution in gaming, Jabbr’s platform can redefine how fighters, trainers, and fans connect and engage.”​

The funding round positions Jabbr at the intersection of Silicon Valley’s tech elite and combat sports royalty, and follows a series of viral moments where Jabbr’s tech and stats surfaced after controversial bouts, racking up millions of views and fueling global debate on judging fairness.

“Jabbr is like Plaid for combat sports, their hardware and API will power everything from automated broadcasts to betting. We’re backing the category king,” says Christian Dalsgaard, who first recognised Jabbr’s potential when their very first AI-generated fight metric tech demo went viral during late 2022.

The post Backed by Reddit and and Lyft Founders, Danish startup Jabbr.ai raises €4.3 million to bring transparency to combat sports appeared first on EU-Startups.

Leuven-based AI Planet, a DeepTech company specialising in enterprise Generative AI and Agentic AI platforms, today announced a strategic joint venture with InfoDrive Analytics who is also backing the move with a €2.5 million investment.

The move will establish an AI and digital transformation powerhouse in the United Arab Emirates (UAE).

Chanukya Patnaik, Founder & CEO of AI Planet, said: “The Middle East is at a defining moment in its digital and AI evolution. The region has consistently leapfrogged traditional transformation cycles through bold investments in innovation and AI will be the next major leap.

“Through this joint venture, we want to empower​ enterprises and governments to harness AI to transform sectors like manufacturing, healthcare, and financial services among others, making AI a true force for progress across the region.”

In Belgium, several startups have recently raised capital to advance AI-driven and agentic technologies.

For instance, Bizzy secured €4 million to expand its AI sales agent platform across Europe, while Eagl raised €825,000 to automate finance operations through AI agents. Another Ghent-based startup, Dalton, obtained €1 million in pre-Seed funding to develop its AI-powered optimisation engine for websites.

Across Europe, funding continues to support both application-layer and infrastructure-layer innovation. For example, Italy’s Lexroom raised €16.2 million to expand its Generative AI legal platform internationally, while Berlin-based Peec AI attracted €7 million for its “Generative Engine Optimisation” product. At the infrastructure level, DataCrunch in Finland raised €55 million to scale GPU and cloud resources across Europe.

Within this context, AI Planet’s €2.5 million UAE expansion aligns with Belgium’s broader push in enterprise and agentic AI, representing a mid-range yet strategically significant investment. It also highlights how European AI startups are increasingly coupling domestic R&D strength with international growth initiatives, particularly in high-demand regions such as the Middle East.

The official signing took place at GITEX Global’s MOU room in the presence of the Ambassador of Belgium & Flanders Investment & Trade team, marking a significant milestone in expanding AI innovation across the Middle East.

On the MOU signing Rino Sabatino, Group Chairman of InfoDrive Analytics and Vardan Global Group added: “We’re excited to partner with AI Planet to build the next chapter of digital innovation. The Middle East and more specifically the UAE’s – momentum in AI is extraordinary, driven by visionary leadership and strong government investment. Together, we’ll bring world-class expertise to help organisations and public institutions accelerate AI adoption, drive operational efficiency, and unlock new opportunities for growth.”

Founded in 2020, AI Planet is a DeepTech Generative AI and Agentic AI platform that enables enterprises to build, deploy, and scale autonomous AI solutions securely. With a strong footprint across manufacturing, finance, education, and public sectors.

Earlier this year, AI Planet built LuxLLama, the first of its kind LLM developed to preserve the culture and history of Luxembourgish language. The project was undertaken with support from Luxembourg’s sovereign cloud and a government innovation grant, marking a national milestone in linguistic AI innovation.

This JV marks AI Planet’s first official presence in the UAE, beyond its established entities in Belgium, Luxembourg, and India, reinforcing its commitment to building global AI ecosystems that enable large-scale digital transformation.

The JV will serve as AI Planet’s regional base in Dubai, focusing on enabling governments and large enterprises in their AI and digital transformation journeys. The investment will be directed toward accelerating market development efforts, strengthening customer acquisition strategies, setting up operations, and hiring regional talent.

In addition, the focus will be on building industry-specific Agentic AI solutions powered by AI Planet’s proprietary platform.

The partnership combines AI Planet’s deep expertise in enterprise-grade AI orchestration with InfoDrive Analytics regional reach and business acumen, setting the stage for scalable impact in enterprise and government ecosystems.

EU-Startups previously covered AI Planet (formerly DPhi) in 2022 when it raised €300k to develop a global community-based AI marketplace.

The post Belgium’s AI Planet announces joint venture with InfoDrive Analytics backed by €2.5 million investment appeared first on EU-Startups.

This week, we tracked more than 85 tech funding deals worth over €2.2 billion, and over 10 exits, M&A transactions, rumours, and related news stories across Europe.

In addition to this week's top financials, we've also indexed the most important/industry-related news items you need to know about.

If email is more your thing, you can always subscribe to our newsletter and receive a more robust version of this round-up delivered to your inbox. Either way, let's get you up to speed.

? Notable and big funding rounds

?? Oura raises over $900M, valuing it at "approximately $11B”

?? Biotech Tubulis secures record-breaking €308M Series C

?? Energy innovator Return raises €300M in growth capital to scale battery storage capacity

??‍?? Noteworthy acquisitions and mergers

?? The Indian company KPIT Technologies (KPIT) is acquiring the Swiss in-car gaming startup AirConsole

??  The Archer Aviation is acquiring the remnants of the insolvent Munich-based air taxi startup Lilium

?? Cooltra has acquired the business operations of urban cycling startup Kleta Mobility

? Interesting moves from investors

?Invalda INVL Private Equity Fund II raises €410M to invest in high-growth companies across the Baltics, Poland, and EU

?Maia Ventures launches €55M Fund to back early-stage agrifood tech entrepreneurs

? Odyssey Ventures comes out of stealth to close the transatlantic valuation gap

?️ In other (important) news

?? Europe’s biggest seed rounds of Q3 2025: Top tech startups to watch

?️ Startups embracing "AI roll-up" strategies

? Waymo to launch in London

? The biggest European gaming deals in H1 2025

? Sort A Brick launches world’s first AI-powered LEGO sorting system

? Recommended reads and listens

Profile: The Serbian maths whizz aiming to crack voice AI

?? Autumn and Arduino Bring Out the Best of Italy

?? Breaking the cybersecurity poverty line: How Stackbob is transforming enterprise IAM

?? Dwarf Engineering is building the universal infrastructure layer for Ukraine’s defence sector

? European tech startups to watch 

?? Fuel Ventures leads $1.3M pre-seed for Theodosian to reinvent cybersecurity

?? Finanz secures €700,000 to expand financial education across Europe

?? Northsea raises €660,000 pre-seed to reinvent customer research with AI

?? Supernaut AI bags €530,000 to help developers resolve stalled tickets and reduce technical debt

?? Orbiri secures £320,000 for community-powered solution to end screen-time nightmare

Lithuania-based tech startup Sort A Brick has launched the world’s first automated industrial-grade system for recognising and sorting pre-owned LEGO® bricks, setting a new standard for the reuse and upcycling of one of the world’s most popular toys. 

This launch comes as the company aims to raise €3 million in its next seed round to scale up its operations.

Sort A Brick is on a mission to bring billions of neglected toy-building bricks back to life! Using AI-powered computer vision and sorting technology, the company cleans, sorts, and repackages the customers’ used bricks into ready-to-build sets, helping them have fun while saving time, money, and the environment.

Check out our earlier interview with Sort A Brick co-founder Ilya Malkin.

Sort A Brick automates LEGO sorting with 99 per cent precision

The company’s inaugural system combines custom-built hardware, software and proprietary AI to tackle a long-standing challenge in the toy reuse sector: processing mixed piles of LEGO bricks quickly, reliably, and at scale. 

Previously, the sorting process required careful manual handling and multiple scans per brick to achieve accurate results

The new system can accurately identify and sort more than 25,000 unique bricks across over 4,000 shapes and the 40 most popular colours, achieving greater than 99 per cent precision. It can also match recognised bricks to over 10,000 unique LEGO sets, organising mixed bricks into selected, build-ready sets in a fraction of the time required by manual sorting. 

With its new system in operation and more than 420 orders totalling over 5,000 kilograms of bricks from 16 countries, Sort A Brick is leveraging advanced engineering to improve families’ access to sustainable play.
Unlocking precision and speed in automated sorting

At the heart of the new patent-pending system is a custom-engineered conveyor that recognises and sorts LEGO bricks automatically using computer vision trained on data from tens of thousands of bricks.  

Loose bricks are poured into a feeder that separates them one by one. 

Each brick then moves into a recognition chamber where AI identifies its specific shape, colour and other distinctive parameters, thus building a precise inventory for each customer’s collection. 

The system can pick out even lookalike pieces with subtle differences while keeping the process moving quickly.

Once the full inventory of a customer’s brick collection is created, it is matched against parts-lists of already existing LEGO sets to find which sets can be rebuilt completely from the available bricks. If some bricks are missing, they will be added to make a set assembly-ready.

“The conveyor we’ve built is the first of its kind — an industrial-grade machine with exceptionally high accuracy that can process around 1,000 parts per hour,” says Ilya Malkin, Sort A Brick’s co-founder. 

According to Malkin, the new conveyor can process up to three times the volume per hour while requiring less than a tenth of the human labour.

Rising demand for second-hand toys

The burgeoning growth in second-hand goods includes affordable toys, especially in the face of rising costs and changing consumption habits. 

“We are seeing faster growth in the market for used toys, as families want options that balance affordability, quality, and a personal connection to what they already own,” says Malkin. 

“We estimate that the secondary LEGO market has outpaced retail for the past five years, reaching around €1 billion in 2024.

Still, only a small fraction of LEGO bricks re-enter the resale market, with the majority confined to fan communities. With the right technology and services, we can unlock massive untapped demand for quality used sets in the mainstream market.”

The recent rise of collection schemes, like LEGO’s own Replay and Brick Take-Back programs, Magic Brix and Fairy Bricks in the UK, and BrickRecycler.com in the US, points to broader support for circular options.

These approaches focus on cleaning and redistributing loose bricks in partly pre-sorted arrangements. In contrast, Sort A Brick’s automated system makes it possible to return customer’s own bricks sorted into 100 per cent complete sets that are ready for rebuilding, thereby moving the industry closer to closed-loop use.

“We are now working on a next-generation conveyor that will operate at 20 times the speed of the current, to deliver unparalleled accuracy and throughput,” says Malkin.

“With every iteration of AI training, we are moving closer to our ultimate goal — recognising all LEGO parts in all colours ever produced.”

Plans are also underway to launch two pilot sorting centres in Western Europe to serve as a foundation for further expansion.

“Enhancing capacity means serving more families and meeting the growing interest in sustainable brick play across Europe and beyond.”

Lead image: Sort A Brick. Photo: uncredited. 

General Intuition, a New York and Geneva-based AI startup has raised approximately €114 million in a Seed funding round – making it one of 2025’s largest early-stage investments in AI.

The round was led by Khosla Ventures and General Catalyst, with participation from Raine.

“This next frontier in AI requires large scale interaction data, but is severely data constrained. Meanwhile, nearly 1 billion videos are posted to Medal each year. Each of them represents the conclusion of a series of actions and events that players find unique – across tens of thousands of environments. The only other platform of comparable upload scale is YouTube,” said Pim de Witte, CEO and Co-founder.

By comparison, most European startups working in embodied AI, agentic systems, or robotics have raised significantly smaller amounts.

For instance, Energy Robotics (Germany) secured €11.5 million in a Series A round to advance its autonomous robot and drone inspection software. Similarly, Unchained Robotics (Germany) raised €8.5 million in an extended Series A to make industrial automation more accessible.

In Southern Europe, Cyberwave (Italy) closed a €7 million early-stage round to build a connective operating layer linking AI agents with real-world machines and sensors. Meanwhile, Omnia (Spain) raised €3.5 million in pre-Seed funding for its agentic AI platform aimed at helping brands interact with AI systems.

Against this backdrop, General Intuition’s Seed funding far exceeds typical European deal sizes in adjacent sectors.

While most 2025 AI and robotics rounds reported by EU-Startups have ranged between €3 million and €12 million, General Intuition’s raise underscores a sharp contrast in both scale and ambition – particularly notable given its early stage and cross-continental structure spanning New York and Geneva.

“When you play video games, you essentially transfer your perception, usually through a first-person view of the camera, to different environments,” added de Witte. “You get this selection bias towards precisely the kind of data you actually want to use for training work.”

Founded in 2025 as a spin-off from the Dutch video platform Medal, General Intuition emerged from Medal’s extensive user base and content pool, which includes over 2 billion gameplay clips annually from 10 million monthly active users. Unlike typical AI startups that rely on curated training data, the company leverages organically uploaded content featuring dramatic successes and failures – ideal edge cases for training systems with spatial and temporal awareness.

It’s able to do this purely through visual input; agents only see what a human player would see, and they move through space by following controller inputs. This approach, the company says, can transfer naturally to physical systems like robotic arms, drones, and autonomous vehicles, which are often manipulated by humans using video game controllers.

The startup will use the funding to scale its research team and advance development of AI agents designed to perform in both virtual and real-world environments.

The company’s research targets include agentic systems capable of learning from unstructured video, world models that simulate dynamic environments for training, and video understanding that applies beyond gaming.

The company is structured as a public-benefit corporation and aims to enhance, not replace, creative roles in the gaming industry.

Commercially, it plans to launch AI-powered non-player characters (NPCs) and simulation tools by the first half of 2026. These NPCs are expected to offer a level of interactivity and adaptability that exceeds the capabilities of deterministic, rule-based bots.

General Intuition’s emphasis on embodied AI also has real-world applications, including search-and-rescue drones that can interpret and navigate unfamiliar terrains without relying on GPS.

This versatility stems from the startup’s belief that LLMs alone are insufficient for achieving artificial general intelligence (AGI), due to their lack of understanding of physical and spatial dynamics

The post Swiss AI startup General Intuition secures €114 million to bridge gaming, robotics, and drones appeared first on EU-Startups.

The UK government is launching a “concierge” service designed to make the UK more appealing to overseas financial services investors.

The UK Treasury said its “one-stop shop” service will help global financial services firms pick locations, navigate regulation and “get to grips with Britain’s business environment”.

The service, which is free of charge, is a partnership between the Treasury, regulators and the City of London.

The move comes amid international investors bemoaning the absence of a dedicated UK resource, unlike in other countries, to help speed up investment in the UK.

Chancellor Rachel Reeves said: “We said we would make it easier to create jobs and grow a business in our country and we’re delivering. This service will drive investment across our United Kingdom, making sure that the world’s most innovative businesses can access the talent found in every corner of our country and that working people feel better off.”

Financial services employ 1.2 million people across the UK, with more than half of those jobs outside London. 

The “concierge” service will draw on the strengths of the UK’s financial services clusters, such as Leeds, Liverpool, Belfast and Bristol, to promote investment opportunities and help deliver the infrastructure, the government said.

Chris Hayward, policy chairman of the City of London Corporation, said: "This marks a defining moment in the United Kingdom’s approach to foreign direct investment. Co-located in Westminster and the City of London, this important step moves us from ambition to action in less than six months.

"The service embodies the strength of public–private partnership, harnessing industry, government, and regulatory expertise to create a streamlined and fully integrated offer. It will make the UK the most attractive destination in the world for financial services.

"For investors worldwide, this represents an unparalleled opportunity to engage with a world-class ecosystem built for growth, innovation, and long-term success."

IMAGE: PIXABAY

You know when you talk to an interviewee about transcribing interviewees and they admit they use AI to summarise notes from a meeting in archaic English, it's going to be a fun interview. 

Dave Colwell, is VP of AI & ML at Tricentis. He also admits that some people he talks to at meetings “are very boring people. They always want an interview, and I’m like: “What are you going to talk about? Same thing as the last call.”

"So once, before anyone else joined, I set the transcript to be written in Shakespearean English. Everyone’s lines came out like “thou so-and-so.” It was hilarious. Prompt injection at its finest.”

He also recommends doing the same in gangster rap. 

But speaking of AI, Tricentis provides a continuous testing platform designed to help large organisations automate and accelerate software testing as part of their DevOps and CI/CD pipelines. Its main goal is to help companies deliver software faster, with fewer defects, by replacing slow, manual testing with AI-powered, model-based, and low-code automation tools.

From testing software to testing AI itself

This week Tricentis unveiled its vision for the future of AI-powered quality engineering at Tricentis Transform, its flagship global event in London, marking a defining moment in how enterprises will build, test and deliver software in the AI era.

This announcement introduces a unified AI workspace and agentic ecosystem that brings together Tricentis’ portfolio of AI agents, Model Context Protocol (MCP) servers and AI platform services, creating a centralised hub for managing quality at the speed and scale of modern innovation.

Testing at the speed (and chaos) of AI

As software creation accelerates through generative AI, organisations face an exponential rise in both code volume and complexity. Traditional testing models can no longer keep pace. Tricentis’ vision reframes quality engineering as a strategic discipline powered by intelligent, autonomous systems where agents work alongside skilled professionals to ensure every release is faster, safer and more reliable. “We give enterprises the ability to test everything."

According to Dave Colwell, VP of AI & ML at Tricentis, the company began with automated testing, performance testing, and test management — essentially making testing easier to create and maintain. 

“Today, we work with companies that run on incredibly complex technology stacks. Some of their systems were built in the 1970s, others were rolled out yesterday.

If any piece of that stack fails, customers feel the pain immediately. That’s where Tricentis comes in: we give enterprises the ability to test everything, across old and new technologies alike.”

Colwell likes to joke that “I’m an ‘AI hipster’ — I joined before large language models were even on the scene. “

His background is in computer vision and natural language processing, and he recounts that early on, Tricentis used computer vision models to analyse user interfaces and figure out how to test them organically, rather than mechanically. 

“That was our first foray into applying AI to testing.

Over the past eight years, we’ve invested heavily in AI, with the main goal of reducing the human effort needed to build and maintain tests. Ideally, the tests build and maintain themselves. That’s the future we’re working toward.

The AI testing paradox: when ‘wrong’ isn’t a bug

I was curious, what makes testing AI solutions so difficult?

According to the 2025 Tricentis Quality Transformation Report, nearly two-thirds (63 per cent) of organisikju65ations deploy code without fully testing it, and over 8 in 10 (81 per cent) report financial impacts from software defects exceeding $500k annually.

As AI accelerates development and delivery, the need for adaptive, autonomous testing becomes critical.  

Tricentis’ agentic AI technologies address this challenge directly, enabling systems that not only generate and execute tests but learn continuously from outcomes to enhance reliability and reduce risk over time.

Colwell detailed that the biggest challenge in AI is that a “wrong” response isn’t necessarily a bug — it’s just another data point. With traditional software, you fix a bug and it won’t reappear if fixed correctly. With AI, you can’t guarantee that:

“Take a customer-support chatbot as an example,” shared Colwell. 

“During testing, someone might ask a question and the bot answers incorrectly.  In a traditional workflow, testers would raise a bug. Suddenly you have thousands of “bugs” — but they’re not fixable in the usual sense because AI is probabilistic. It’s a big ball of math making guesses.”

When not to use AI

The first filter Tricentis teaches customers is: should you use AI at all? According to Colwell, if your use case can’t tolerate persistent error, then AI isn’t the right tool. 

“In drug discovery or hiring, even a single mistake can have catastrophic consequences. By contrast, AI-generated code is a safer use case because humans review it, pipelines catch errors, and the system is designed with verification in mind.”

AI turns startups into giants

Tricentis’ customer base is primarily large enterprises with sprawling, complicated tech stacks and the most to lose when things go wrong.

They’re also the ones most anxious about being disrupted by nimble AI startups. Colwell argues that many large enterprises are intimidated by three-person startups.

“AI makes it possible for a tiny team to look like a big company almost overnight. We’ve seen billion-dollar organisations losing customers to these newcomers because the speed and polish of what they deliver is suddenly competitive.”

The problem for enterprises is that they’re weighed down by technical debt and legacy systems. They’ve never seen customers churn so quickly to younger competitors. Even though most AI startups won’t survive long-term, the disruption they cause is real.

“Vibe coding”: good idea, terrible name

And, of course, I wanted to get Colwell’s stake on vibe coding. He laughs that while it's a terrible name, the concept is real:

“We’ve run AI coding programs internally, and we’ve seen two very different outcomes. One engineer handed almost everything to the AI. He looked highly productive — shipping massive amounts of code.

But when we reviewed it, much of the code was low-quality, because he had surrendered too much control.

On the other hand, teams that built processes around AI coding — with feedback loops, documentation, and review — saw far better results. 

They made the AI explain its reasoning, documented acceptance criteria, and looped back to check whether the outputs matched the original plan. That produced reliable outcomes.”

So the lesson is this: AI coding is about changing how you work — focusing on process, documentation, and validation.  Colwell asserts:

“Done this way, it’s powerful, but done badly, it’s a disaster.”

The “stolen generation” of developers

I’m always interested in what AI means for young developers entering the workforce, especially in many cities in Europe where there are high unemployment rates for early-career roles.

According to Colwell, right now, we have a delicate balance.

"Younger engineers adapt quickly to new tools, but they don’t always recognize what “good” code looks like. Experienced engineers know quality, but can struggle to adapt to the new paradigm. Pairing the two creates strong outcomes.”

He believes that looking further ahead, we’ll flip the traditional learning path:

“Today, junior developers spend years learning by fixing bugs and writing small features before they’re trusted with design.

In the future, people may learn design patterns and architecture first, because AI will handle much of the low-level coding.

However, Colwell also raised concern about what he calls a “stolen generation” — developers trained on coding skills that AI makes less relevant, but who haven’t learned higher-level design thinking. 

“They’ll need to re-skill, which won’t be easy. At Tricentis, we’ve realised that defensibility no longer lies in code — AI makes code almost disposable.

The moat is data, delivery, and customer trust. Code can be reproduced quickly, but real-world data and trusted customer relationships cannot. That’s why enterprises are incredibly protective of their data and why we focus heavily on transparency.”

From ERP overhauls to agentic AI workflows

In terms of AI-first evolution, Tricentis has three main focuses: 

Autonomous testing — essentially, letting users guide the process while AI handles the execution. “We want 'hands on the keyboard' testing to disappear.”

ERP replacement and validation: “Many enterprises are moving to cloud ERP systems while grappling with massive technical debt and vendor lock-in. We see a huge opportunity in helping them test and validate those transitions,” shared Colwell.

Agentic coding and validation — Colwell asserts that the gap in the market is not just in AI coding but in AI validation. 

“You can’t let the same AI that writes code also test it, because it will inherit the same false assumptions. We’ve developed approaches using separate AIs — one to write code, another to test it — communicating through protocols like Model Context Protocol. That separation creates the same dynamic you get in human teams, where developers and testers think differently.”

Tricentis AI workspace offers an enterprise-grade environment for managing AI agents, workflows and governance across the entire software lifecycle.

Coming in 2026, this intelligent workspace allows organisations to:

• Onboard and orchestrate AI agents from Tricentis, partners or third parties;
• Define governance and security policies for responsible AI operations;
• Integrate directly into SDLC workflows using tools like Jira, GitHub and ServiceNow;
• Monitor agent performance and compliance through unified dashboards; and
• Scale quality engineering autonomously, empowering teams to manage agentic AI “workforces” while focusing on higher value initiatives.

The AI workspace unites Tricentis’ agentic portfolio, including Agentic Test Automation (Tosca), Quality Intelligence (SeaLights), Test Management (qTest) and Performance Engineering (NeoLoad), all connected through Model Context Protocol (MCP) servers that enable secure, flexible interoperability across AI systems and enterprise toolchains.

London-based energytech Allye Energy has raised $2.5 million in a seed funding round to accelerate the deployment of its smart battery systems.

The funding round was anchored by Elbow Beach, alongside Alpha Future Funds.

Benedikt Sobotka, General Partner at Alpha Future Funds, said: “Allye's innovative approach to repurposing EV batteries - including those prematurely retired from accidents or early replacements - represents a circular economy breakthrough."

The round combines equity and debt financing and will support scaling up manufacturing and delivery of its technology for both grid-connected and off-grid use cases.

The company plans to expand into Europe within the next 12 to 18 months, having already established sales in the UK and Ireland.

Allye’s technology combines repurposed electric vehicle (EV) batteries with advanced control systems to provide flexible energy storage. Its systems are used in sectors ranging from construction and transport to energy utilities and media production. Customers including Horizon Plant and OnBio have ordered additional units following successful trials, while Roadchef has renewed its subscription contract.

The new funding will enable the further commercialisation of Allye’s MAX range of battery energy storage systems, including the MegaMAX models with capacities of 1 MWh and 1.5 MWh. It will also support the expansion of Allye’s engineering team to develop new power control innovations and battery technologies.

Jonathan Carrier, Founder and CEO of Allye Energy, said: “This funding represents validation of our vision to eliminate energy constraints through intelligent battery storage.

In oncology, progress is often described in cautious terms: a few months’ extra survival, a slightly improved quality of life, a percentage-point increase in remission. These steps matter, but they also reflect an industry built around averages. Clinical trials, treatment guidelines and approval frameworks all optimise for the “median” patient outcome.

Yet hidden inside every dataset are extraordinary outliers: cancer patients who, against all statistical odds, live far longer, and far better, than predicted. These “exceptional survivors” have traditionally been dismissed as anomalies. But what if, instead of treating them as medical curiosities, we saw them as the prototypes of a new standard? That is where I believe the opportunity lies, not just for science, but for startups, investors and healthtech pioneers.

From medical curiosities to a startup opportunity

The stories of exceptional survivors are not just inspirational; they are a largely untapped data source. Their biology, immune responses, genetic variants, lifestyles and psychosocial environments may hold clues to survival mechanisms that medicine has not yet translated into treatments.

This opens a massive white space for innovation. Startups are uniquely positioned to explore it because they can move faster than incumbents, cross traditional silos and experiment with technologies that scale. Agile startups can start from this observation and ask the question: what is right in the biology of survivors, and how can we replicate it?

For founders, this is a frontier market. For investors, it represents an underexploited therapeutic category with the potential for cross-cancer applications, lower toxicity profiles and reduced costs compared with late-stage interventions.

The tech enablers are already here

Until recently, resilience research was not feasible. Today, technology has rewritten the rules, and many of the leaders and drivers of this change are based in Europe.

Exceptional survivors are rare by definition and geographically scattered, making a large-scale study nearly impossible. But technology has changed the game overnight. AI and big data can now analyse billions of biomedical data points to spot survival patterns invisible to the human eye. Biobanking and sequencing provide high-resolution biological samples from patients worldwide. Digital twins allow researchers to model patient responses and simulate resilience mechanisms. Global data platforms can pool survivor cases across borders, creating the statistical power needed to extract actionable insights.

A nascent ecosystem and room to grow

Resilience-focused oncology today is where precision medicine was 15 years ago: rich in promise but still underfunded and under-recognised. Dedicated funding streams are needed, both public and private, to support early-stage ventures in this space. Regulatory pathways must also adapt to encourage resilience-driven endpoints, not only median survival metrics.

At the same time, cross-disciplinary collaboration is key.

Startups that can unite oncologists, immunologists, geneticists, data scientists and behavioural researchers will have an edge. Building resilience profiles requires a true 360° view of patients, not just tumours. That means integrating lifestyle, psychosocial and environmental data alongside biological samples. This is not a trivial challenge. But it is precisely the kind of complex, boundary-crossing problem where startups thrive and have a clear advantage over traditional health organisations, which tend to be siloed.

What is next for founders and investors

• If you are a founder, resilience research is not just about biology; it is about data ownership, patient engagement and platform design. How can you create spaces where survivors contribute their stories and samples in exchange for transparency, support and real-world impact? How do you make data collection longitudinal, global and scalable? These are product and business model questions as much as scientific ones.
• If you are an investor, resilience-focused oncology may be the next big therapeutic category. The potential for multi-cancer treatments, faster clinical trial recruitment and lower systemic costs is enormous. Just as rare disease startups reshaped biotech over the past decade, resilience startups could define the next one.
• If you are a policymaker or ecosystem builder, the priority should be enabling global data collaboration. Exceptional survival cases are few; without international pooling, the statistical power is too weak. Europe has an opportunity to lead here by fostering data-sharing frameworks that respect privacy but allow startups to innovate on top of shared knowledge.

From outliers to new standards

The shift from focusing on “median patients” to learning from “exceptional survivors” will not replace oncology as we know it, but it could enrich it and accelerate transformative breakthroughs. Imagine clinical trial endpoints that do not just ask, “How long did the average patient live?” but also, “How many crossed into the realm of exceptional survival?”

The vision is clear: if startups and investors lean into this space, if regulators and funders support it, and if global data networks scale it, then what we currently call “exceptional” could one day become normal. The future of oncology will not be built on averages. It will be built on resilience. And startups have a once-in-a-generation chance to lead the way.

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Lithuanian AI startup Supernaut AI has raised a €530,000 pre-seed investment from Helsinki- and Vilnius-based venture capital fund Superhero Capital. 

Supernaut AI is building an “AI-native” tool for engineering teams, designed to accelerate software development by automating repetitive, time-consuming tasks and turning them into tested, documented code within minutes.  The solution integrates with commonly used work platforms such as Jira and GitHub, acting as a proactive team member that helps resolve stalled tickets that often lack time or motivation to be addressed.

Supernaut AI stands out from competitors (such as individual developer tools like Vibe Coding) by focusing on team-based workflows. The solution helps not only with code generation but also with reducing technical debt.

Supernaut AI was founded by Mantas Konstantinavičius and Olga Maslova.

Mantas has years of experience leading engineering teams across five startups and applying AI-driven automation solutions in workflows.  Olga Maslova, who holds a PhD in physics, brings deep technical expertise and experience in leading machine learning and data science projects as well as building complex systems.

“We’re building Supernaut to eliminate the biggest productivity barriers engineers face gradually,” shared Mantas Konstantinavičius, co-founder of Supernaut AI.

“Our first version solves a problem every developer knows – when Sentry floods you with errors, the whole team suddenly ends up fixing bugs instead of building the product. 

Supernaut automatically investigates, documents, and fixes these issues with full transparency.

Our long-term vision is simple: an AI team member that reliably handles monotonous work so humans can focus on what truly creates value.” 

The investment was led by Gytenis Galkis, Partner at Superhero Capital, responsible for expansion in the Baltic region.

"Mantas and Olga’s team has a unique market understanding and the technical competence needed to bring this solution to life. We see strong potential for both the product and the team to scale globally — their tool gives engineering teams back the time to innovate instead of dealing with backlogged tickets,” says Gytenis Galkis.

The product is currently being tested in a closed environment, and the startup plans soon to launch an open beta program with its first customers.

The funds raised will be used to expand the team and develop the product toward its first commercially viable version. Supernaut AI is targeting the global market, and investors see significant potential in proactive AI tools that enhance team productivity.

Amsterdam-based energy scale-up Return has entered a long-term partnership with APG, on behalf of pension fund ABP – the former of which is investing €300 million in new growth equity for a minority stake to support the platform.

“Partnering with APG marks an important step toward a more connected and resilient European energy system,” said Willem-Jan Schutte, Founder and CEO of Return. “Together, we can turn today’s fragmented energy landscape into one that truly works for customers, communities and the climate.”

Return’s growth equity investment from APG places it among the largest European storage and flexibility financings of 2025.

The deal surpasses most peer rounds, with only Terra One (€150 million) showing a comparable scale in grid-scale battery deployment. Within the Netherlands, Sympower and iwell also secured new capital this year, highlighting sustained investor confidence in Dutch energy flexibility platforms.

On a broader European level, green flexibility and Voltfang demonstrate continued institutional interest in scalable battery infrastructure.

Against this backdrop, Return’s partnership with APG reinforces the trend of large, long-term investors supporting capital-intensive, grid-balancing storage networks across Europe.

“The energy transition requires shared responsibility,” added Sjoerd Bazen, Managing Director at Return. “With APG we align interests, improve performance and create opportunities that benefit markets and society.”

Founded in 2021, Return is an energy scale-up specialising in grid-scale battery energy storage systems (BESS) and flexibility services. The company connects storage sites across countries through a data-driven platform that balances renewable generation, alleviates grid congestion, and enhances system reliability.

Active in the Netherlands, Germany, Belgium, and Spain, Return operates 70 MW of storage capacity with an additional 450 MW under construction.

With over €2 billion in long-term customer contracts, Return is on track to meet future demand with a pan-European storage network of around 5 GW by 2030, supporting flexible, reliable access to clean energy.

The transaction was signed in October 2025 and, subject to regulatory approval, is expected to close by year-end.

“APG’s investment aligns with its client’s strategy of supporting clean, connected infrastructure that delivers stable, long-term returns while advancing net-zero goals, in the interest of ABP and its participants. Grid-scale battery storage is key to reliably integrate renewables and to ease grid congestion,” said Bart Saenen, Senior Investment Director at APG. “Return’s integrated platform, long term vision on relations, and de-risked pipeline make it a strong partner for building grid resilience across Europe.”

Across Europe, the increasing share of renewables is creating fluctuations in electricity supply and demand. Energy customers need flexibility to balance portfolios and use renewable power more effectively. Return’s high-tech battery energy storage system (“BESS”) platform aims to tackle this challenge by connecting storage sites across countries, showing real-time insight where energy is available and needed to ease congestion and strengthen the grid.

The partnership reinforces Return’s role as an independent player in Europe’s energy system, connecting stakeholders through data-driven storage.

APG’s long-term involvement adds financial stability and supports continued system-focused delivery.

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Amid record funding and growth, Britain is shaping itself as a top innovation powerhouse – and it’s doing so by reinvesting in an age-old advantage: its universities. This time, however, it’s not just academia leading the charge.

A three-pronged alliance between researchers, investors, and AI infrastructure is shaping a new wave of tech commercialisation that could reshape the UK economy for decades.

Record-breaking year for university spinouts

According to data received by EU-Startups this week, UK university spinouts raised a record €3.8 billion in equity investment during 2024, beating the previous high of €3.1 billion recorded in 2021. The findings, published by Parkwalk Advisors – a notably active investor in UK spinouts – and analytics platform Beauhurst, show a strong rebound from 2023 and renewed investor confidence.

This resurgence stems from several converging forces: a reawakened venture capital market, the return of ‘megarounds’, and stronger government focus on AI and digital infrastructure. Together, these trends are not only helping more companies spin out of academic institutions, but also laying down a path – albeit an uneven one – towards scale-up and global impact.

Challenges and disparities remain

Why uneven? Well, despite the impressive overall growth in UK innovation and investment, there are still significant imbalances and challenges within the ecosystem:

• Regional Disparity: Nearly 78% of spinout investment still goes to the South East, London, and the East of England. Regions like the North, Scotland, and Wales receive comparatively little, although initiatives like the Northern Universities Venture (as covered by EU-Startups) Fund aim to change that.

• Scale-Up Gap: While hundreds of spinouts are raising early rounds, few surpass the €22 million mark, stalling before commercial maturity.

• Foreign Capital Dependence: The biggest rounds increasingly rely on US investors – valuable, but a sign of weak domestic risk appetite for late-stage venture.

Life sciences and DeepTech lead the way

Equity investment into UK spinouts in 2024 rose 44.3% compared to the previous year, with average deal size climbing from €5.6 million to €8.5 million. Life sciences led with 182 deals between H2 2024 and H1 2025, followed by DeepTech sectors like AI and data infrastructure with 152 deals.

Moray Wright, CEO of Parkwalk, said: “Spinouts are the future of this economy […] The companies raising record sums of investment in 2024 are tackling the biggest challenges of our time – from climate change to AI and healthcare.

They added that long-term support for the Enterprise Investment Scheme and full implementation of the Mansion House reforms could help the UK fully leverage its potential in frontier innovation.

The scale-up bottleneck

And yet, the findings illuminate difficult truths.

While early-stage investment is flourishing, scale-up funding remains limited. Of the hundreds of spinouts launched in recent years, only 57 raised between €20 million and €29.9 million, and just 42 reached €30 million to €39.9 million. Many are more than a decade old, suggesting even strong IP-based startups struggle to access growth capital for international expansion.

Greg Smith, CEO of IP Group, said: “The UK has nurtured one of the world’s leading ecosystems for academic innovation – but without scale-up capital, we risk missing a once-in-a-generation opportunity.”

Foreign capital, particularly from the United States, is filling part of this gap. US-based funds participated in 113 UK spinout deals in 2024, with average co-investment deal size rising from €15.4 million to €26.1 million year-on-year. Foreign-only rounds also grew, from €11.4 million to €18.4 million.

Five of the eight largest transactions in 2024 involved international investors.

Regional rebalancing takes shape

While the South East (€6.3 billion), London (€4.8 billion), and the East of England (€4.8 billion) still dominate, signs of rebalancing are emerging.

Manchester-based spinouts raised €64 million in 2024, a new record, while universities in Edinburgh, Sheffield, and Leeds are gaining momentum. Initiatives like The Northern Universities Venture Fund aims to unlock the research potential across the ‘Northern Arc’ – home to underfunded yet high-potential institutions.

Beyond spinouts, wider signs suggest Britain’s innovation economy is regaining its footing.

A Q3 2025 report by HSBC Innovation Banking and Dealroom shows UK startups and scaleups secured €7.6 billion in venture capital funding that quarter – the second-highest Q3 total on record and the strongest since 2021. With €14.7 billion raised so far in 2025, the UK has already matched its entire 2024 total and is on track to reach about €19.7 billion.

To put these numbers into perspective, the amount invested so far this year is reportedly greater than the combined totals of the top 2-4 countries: France (€5.3 billion), Germany (€5.1 billion) and Switzerland (€2.3 billion).

FinTech once again led, raising €4.5 billion across the first three quarters, including Revolut’s €1.7 billion round and Xelix’s €136 million Series B. Series A activity hit a seven-quarter high with 46 deals, signalling strong early-stage interest.

“UK venture capital has rebounded with strength across all stages,” said Simon Bumfrey, Head of Banking at HSBC Innovation Banking UK. “The return of billion-dollar megarounds, alongside record early-stage activity, signals renewed investor confidence […] FinTech remains the UK’s flagship sector, while the strength of HealthTech and other high-growth areas demonstrates the breadth of our ecosystem.”

He added that regional hubs are attracting a growing share of capital, positioning the UK as “a global centre where innovative ideas scale into successful, impactful businesses.”

AI infrastructure and the rise of UKAIFA

Nowhere is this convergence of research, capital, and policy clearer than in Edinburgh, where the EPCC (the UK’s first National Supercomputing Centre) is spearheading the €10 million UK AI Factory Antenna (UKAIFA). Supported by the UK Government and the European High Performance Computing Joint Undertaking, the project aims to mainstream AI across British industry and academia.

Set to employ 20 full-time staff and operate from early 2026, UKAIFA will support sectors such as health, FinTech, energy, creative industries, and robotics. It is part of a wider EuroHPC strategy placing supercomputing centres at the core of Europe’s digital transformation.

“This significant investment underlines Edinburgh’s world-leading capabilities in supercomputing and AI. It also shows the important role universities have in deepening our understanding of cutting-edge technologies,” said Professor Sir Peter Mathieson, Principal and Vice Chancellor of the University of Edinburgh.

The Antenna will work with Germany’s HammerHAI AI Factory to share best practices and provide scalable, secure infrastructure for businesses and researchers.

“By working with our neighbours, we’re giving our best and brightest access to the processing power, data and training needed to develop new breakthroughs in everything from healthcare to climate change,” said Kanishka Narayan, UK Government AI Minister.

A balanced innovation economy in the making

Britain’s strength in science hasn’t yet translated into scaled commercial success at the pace of the US or China. But as more spinouts raise larger rounds, regional universities gain access to capital, and AI infrastructure expands, the pieces of a more balanced and future-proofed innovation economy are falling into place.

Whether this becomes a launch pad for the UK – or just another spike in a notoriously cyclical tech sector – depends on the support of European investors and the innovation of their academic institutions.

For now, however, the message is clear: the UK is playing to its strengths.

The post Inside the UK’s innovation surge: record spinout funding, AI initiatives, and academic momentum appeared first on EU-Startups.

Right now, one of the most common threads in innovation is the use of AI. Whether it’s designed for rapid drug discovery or drug repurposing, medical diagnosis, digital therapeutics, or fine-tuning a service delivery model, AI is everywhere and increasingly baked into the process of inventing.

But it’s not simply the adoption of AI that matters; it’s how it’s being used. When you’re a startup trying to secure investment, claiming you’re using AI is no longer enough. We’ve moved on from the days when buzzwords like AI or blockchain were sufficient to open funding doors. Investors are now more discerning, and importantly, so are patent offices.

Not all AI innovation is equal, and what makes AI patentable

Just because something uses AI doesn’t mean it’s patentable. Take, for example, a dating app versus an app that recommends whether you need to return to the hospital for an eye check-up based on analysis of longitudinal data from retinal scans. Both rely on AI and pattern recognition in the data, but one is viewed as a technical solution to a medical problem and associated healthcare risks, while the other might be dismissed as an obvious, non-technical business method that merely automates what has been done for many years, albeit with some additional sophistication. The AI itself doesn’t intrinsically know the difference, but the patent office certainly does. The real value often lies not only in the final trained model, but also in how you got there, especially your selection of training data.

The general position of most patent offices is that using AI to solve a big data problem, or spot a pattern, is often seen as obvious to try. So, when companies say they’ve innovated using AI, figuring out which side of the patentability line they are on is essential. Are you solving a genuinely technical problem or providing a new technical effect, or are you merely automating something that has been done manually for years?

Take financial risk profiling. AI can help maintain a client’s investment risk below a certain threshold in real time. That’s mathematically complex, involving data analysis, real-time inputs, and automation. Yet it’s still often viewed as non-technical. Why? Because the use case is finance, and that can then drag it to the wrong side of the line for patentability, a line drawn several decades ago.

Patenting AI vs keeping it secret

There’s another layer: even if something is patentable, should you file a patent application, or instead keep it as a trade secret? If your competitive edge lies in the trained model or the training data, secrecy might be the better strategy.

AI-based inventions in areas like healthcare, diagnostics, or engineering tend to get more traction from the patent office. But shift the focus to finance or admin, even if the technology is equally sophisticated, and it is often dismissed out of hand as an unpatentable business or mathematical method.

Startups should consider what exactly the inventive step is. Is it the technical problem solved, the selection or curation of training data, or the insights revealed? The answer will guide whether to patent or protect through secrecy. If the edge lies in the trained model or unique training data, secrecy may be the right approach, but you will need a trade secrets policy for this.

If, on the other hand, your innovation lies in the novel insight AI helped discover, and that insight can be articulated clearly, a patent for that will likely add real value. This is particularly true for drug discovery and drug repurposing, as well as novel dosage regimens.

AI is just a tool, but the human inventor is still key

Startups should also be cautious about saying their AI invented something. Instead, the focus should be on highlighting the ingenuity in how the team selected data, trained the model, and interpreted the outputs. That’s where the innovation lies, and that’s what patent law currently rewards.

Attributing the innovation to an AI platform may have PR value, but it carries real dangers, as only human inventors can be named on a patent application. You might be setting up a case for challenging the validity of the patent, either because there is no real human innovation or because you misrepresented it.

If a startup is using AI, the key question is whether it is implementing AI to deliver a technical solution or using AI to discover something new. In both cases, there’s real value, but the approach to IP protection will differ. And as policy slowly catches up with the pace of AI, navigating this grey area successfully will be a vital part of the innovation journey.

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