This week, we tracked more than 70 tech funding deals worth over €1.6 billion and over 15 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

?? Elvy raises €500M to power its next-generation energy solution

?? Iceye raised €150M in Series E funding

?? Fal raises $140M Series D to power the next era of real-time generative media

??‍?? Noteworthy acquisitions and mergers

??  Mollie buys GoCardless in €1.05bn deal

?? Tekpon’s bold bet: Why a SaaS marketplace bought TNW without seeing the numbers

??  Sortlist acquires Overloop AI and becomes a complete commerce platform by focusing on AI

?? The Canadian company Senstar is acquiring the Munich-based 3D LiDAR technology company Blickfel

? Cofounder VC launches new early growth Fund to back CEE startups beyond Seed stage

? Interesting moves from investors

?  Inside Ignite Next: the new scaleup program supercharging Europe’s deeptech

? Hiro Capital snaps up Nick Clegg and Yann LeCun, as launches fund

?? KBC unveils €100M Start it Fund, targeting Belgium’s most promising startups from idea to IPO

? U2V launches €60M fund for deeptech university spin-offs in Europe

? betacluster Ventures launches new early-stage fund to support AI-driven innovation

? Cofounder VC launches new early growth Fund to back CEE startups beyond Seed stage

?️ In other (important) news

?? UK tops Europe’s €4.6B funding as fintech dominates November

?? Applied Computing opens Bangalore office as India becomes ground zero for next-gen industrialAI

? Internxt AI debuts as Europe’s answer to ChatGPT — with total user anonymity

?? The biggest European foodtech deals in H1 2025

? Recommended reads and listens

? “Our strategy is to build and control as much as possible”, says Nebius co-founder

?? The Ukrainian startup turning sorted waste into cash

?? How an Irish startup is turning speech into a dementia early-warning signal

? The bug-bounty court bringing order to DeFi

? European tech startups to watch 

??  Zentio raises €1.4M for AI-native production planning

?? FION Energy secures €1.4M for AI-optimised battery systems

?? Freepress raises €1M to make global news more accessible through AI

?? Sprouty raises $550,000 to expand its AI-based parenting support app

? Backed by Nordic VCs, CYBRET AI bets on autonomous systems to redefine cyber defence

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The post Weekly funding round-up! All of the European startup funding rounds we tracked this week (Dec. 08-12) appeared first on EU-Startups.

This week sees the launch out of stealth of CYBRET AI, an autonomous security and development lab building autonomous systems that understand modern attack behaviour, reason across complex environments, and operate at machine speed.

From deep attack understanding to real-time reasoning and response, its work focuses on pushing security beyond human-only operations.

Although the financials have not been publicly disclosed, CYBRET AI is backed by leading Nordic funds and experienced operators, including Skyfall, Inception Fund, Visionaries Club, Wave Ventures, FR8, and founders from companies such as F-Secure, AMD Silo AI, and Hoxhunt.

Founder and CEO Adrian De Gendt is a Nordic child prodigy — Norway’s youngest cybersecurity analyst in history, a two-time finalist (and the youngest ever) in the Norwegian Astronomy and Astrophysics Olympiad, and the youngest student to attend both high school and university.

After dropping out of a Masters degree in Artificial Intelligence at just 19, Adrian has been deeply immersed in hacking, programming, and cybersecurity since his early teens. He is now determined to build a world-class team and a global category-defining company with strong Nordic roots but a global mindset.

According to Ernesti Sario, Co-founder, FR8, it's rare to see someone this young carry such technical depth with such relentless drive:

“From our first conversations, it was clear that Adrian was onto something special. He is one of those few builders who refuse to accept the limits everyone else quietly lives with. We’re proud to be among the early believers.”

For Oliver Molander, General Partner, Inception Fund, Adrian represents the new generation of technical talent emerging from the Nordics in AI — founders like those behind Lovable and Legora –- marked by fearlessness and a global-maximum mindset from day one.

"We’re extremely excited to back him and equally excited about the talent the Nordics and Europe are currently producing.”

British AI company Applied Computing, which develops foundational AI for energy operators, today announces the opening of its new office in Bangalore, marking its official expansion into India and deepening its commitment to one of the world’s most strategically significant energy markets. The expansion will create new jobs across AI research, engineering, energy modelling and commercial operations.

The move follows significant traction in India, where Orbital has already been proven inside major refining environments and is now being actively deployed with leading operators.

Applied Computing’s flagship platform, Orbital, is the first foundation model built specifically for energy operations, bringing superintelligent, physics-grounded optimisation to some of the most complex industrial environments in the world.

Applied Computing has built-up a senior team in India, including the appointment of former Shell executive Dan Jeavons, one of the world’s leading industrial AI figures, who relocated from London to Bangalore several years ago.

Following his decision to join the firm this summer, Dan decided to remain in India. 

Jeavons previously led Shell’s global AI programme and brings two decades of experience spanning upstream, downstream and integrated gas. I spoke to him to learn more about the country, why it’s been gaining so much traction when earlier startups haven't, and its market expansion into India.

Jeavons spent almost 20 years with Shell in different capacities, always in the data and analytics space. And then data and analytics blurred into AI as the world headed in that direction.

For the last 13 years, he was leading Shell’s core AI program; his last role at Shell was VP for Computational Science and Digital Innovation. 

He explained, “I led about 350 researchers globally, working on everything from seismic processing to wind turbines, manufacturing plants, and electric vehicle charging—building various types of AI for all of that.”

During this time, he got to know Sam Tukra, “an incredible talent we quickly identified at Shell, but he was very convinced he needed to go and start his own company. So he built what is now Applied Computing, where he now works as Chief AI Officer.”

‘My ChatGPT moment’: why Orbital convinced a Shell veteran to switch sides

Tukra visited him after putting together a research team from Imperial and partnering with Callum Adamson, the CEO and co-founder, and an Entrepreneur-in-Residence at Imperial.

He recounts:

“He came to see me and showed me what Orbital is, the foundation model we’re developing at Applied Computing.

I always say it was my own personal ChatGPT moment. 

I’d been very close to the developments of large language models, so ChatGPT itself didn’t really surprise me."

The real breakthrough he saw in Orbital was the ability to combine physics, time series and language into a common foundation model. 

“For our world — the world of energy operations — that is an absolute game-changer because it brings into one integrated model almost every question you could ask about the operations of a site.

So it becomes a true general AI you can deploy into some of the world’s most complex industrial landscapes.

I got very excited, and long story short, they convinced me to come over and help build the company. It wasn’t in the life plan — but here I am as President.”

Why industrial AI struggled — and why that’s now changing

I’ve written 100s of thousands of words about industrial IoT throughout my career. However, Industrial IoT, in many respects, failed to deliver on its promise.

Most factories are built on decades-old machinery, proprietary protocols, and safety-critical systems that are difficult or costly to connect, making integration economics unattractive. Projects also suffered from unclear and slow ROI: large upfront investment in sensors, connectivity, integration, and security often delivered only incremental savings, so pilots rarely scaled.

Further, while IIoT generated vast amounts of data, organisations lacked the analytics maturity to turn that data into actionable outcomes as they depended on an AI capability that didn’t yet exist. Only now, with foundation models, edge AI, and domain-specific intelligence, is it becoming feasible to rethink industrial systems.

Jeavons admits that, as someone who spent a decade working on Industry 4.0 projects, data-driven methods only really impacted the peripheral operations.

“You could do equipment failure prediction, integrity management, inspection, rust detection, classification — those worked and delivered value.

But the utopia we are glimpsing now with AI? I felt that was achievable with the prior generation of tech. But it wasn't.

It wasn’t explainable enough. It was too black box. It wasn’t appropriate to deploy into the core of operations. With the next generation of models, all of that is changing. And I think we will see a radical transformation in heavy industry in the next few years.”

According to Jeavons, most critical infrastructure runs on physics-based simulations. When you design a facility, these are the equations that govern its operation, because they’re governed by the laws of physics. 

“We can say that if we operate within these constraints and boundaries, we can produce the desired output from the process. We run that process a lot of times, then embed that into a control system.

What that allows you to do is run the facility in steady state within those boundary conditions. Operators are there to make sure those operating limits aren’t breached.”

However, this fails to integrate all the data the plant generates continuously. That data gets used, but only for root-cause analysis or incident detection, but its siloed and disconnected from operations. Then you have a whole variety of engineering disciplines sitting around the plant using subsets of that data to derive insights that operators might want to know.

Orbital completely rethinks this. It can combine the physics from the simulator and integrate it with the data — not just time-series data, but also language data: the reports written, the work orders generated, the inspection reports created five years ago. Jeavons equates it with the aeroplane and the control tower. 

“The pilots are flying it — that’s what operators do. But in these sites, you don’t have the control tower where you can see everything else going on. We’re saying: you can build a control tower.

Across not just one site, but 40 sites. You can compare operations. You can look at when a piece of machinery failed and ask: where else is that likely to happen next? You can say: I’ve seen this integrity condition here, under these conditions—have we checked over there? Your ability to look across the entire business and empower that with A I— that’s where the transformation comes from.”

Asking operational questions in natural language while protecting proprietary data 

For Jeavons, the language interface makes an enormous difference:

“The ability to ask simple questions in natural language and interrogate all the data — engineering drawings, shift logs, maintenance history, time series — that ability to cut across silos is game-changing.

Each engineering discipline is looking at one slice. Orbital lets you ask questions across all of them.”

I was curious about how Orbital handles proprietary data, a major issue in industrial environments. Crucially, Applied Computing brings its model to the customer’s data. Orbital has a foundational understanding of physics, the domain language, and time-series behaviour. 

“It’s a transfer-learning principle. We augment it with the customer's data—in their environment," explained Jeavons.

“Training happens inside their infrastructure, or an environment they control. That means we don’t expose their data to the world or to other customers.

We do not ask for their data to train a global model. The model remains our IP, but everything produced in the customer’s environment is theirs to use under the contractual terms. And the data never leaves their environment."

From pilot to production in under a year

Less than a year into the market, the company is deploying into real customer environments and seeing strong outcomes. 

According to Jeavons, “The biggest thing customers tell us is the ability to approach a problem from multiple different angles, unlike before, where you needed a whole team of experts. The biggest benefit is the ability to use AI to rethink how you run your business and answer questions you couldn’t answer before. That’s where senior leaders are really engaging—because they believe this will change the game.”

Applied Computing raised £9 million in May this year. The funds are being used for research: “At our core, we are a research company developing a next-generation foundation model for the energy industry,” explains Jeavons.

“AI moves daily, and we must stay at the cutting edge.”

The second use is go-to-market strategy. The company has hired domain experts as “it’s great having a killer model. The challenge is deploying it, solving users’ problems, and earning the right to expand within accounts,” shared Jeavons. 

He sees his role as to bridge the tech with industry needs and shape the narrative and deployment to drive impact. 

“To drive material change in these organisations, you have to work at the C-suite level. It’s not just technology—it’s rethinking how you run your business.

That’s why we focus on a few strategic customers and high-level conversations to drive outcomes.”  

Rising energy demand meets India’s leapfrog-ready infrastructure

Applied Computing’s expansion comes as India’s energy landscape reaches a pivotal moment.

While global policy trends push towards decarbonisation, India’s energy demand continues to rise sharply, driven by industrial growth and a rapidly expanding population.  According to Jeavons, India is the fastest-growing energy economy in the world.

“There’s incredible talent here. I lived in Bangalore for three years — I moved here with Shell and stayed because I’ve been so taken with the country and its potential. We’re celebrating the opening with friends, customers, and partners. We’ve already had customers come into the office to work with us and see the research team. It creates a phenomenal space for accelerating the technology."

He believes that. while Europe has been phenomenal in many areas— "just look at the startups that have emerged from the region." India can leapfrog in areas where it isn’t constrained by legacy systems.

"That entrepreneurial instinct is very real. That’s why I’m excited about Applied Computing being here: we can run the leapfrog playbook.”

He shared: 

“Orbital is already delivering results with customers here, including at some of the largest refineries on the planet.

By establishing our base in Bangalore, we’re investing directly in the talent, partners and ecosystem that will define the future of industrial intelligence.”

It's a sentiment echoed throughout the company. According to Callum Adamson, CEO and co-founder of Applied Computing,  “India is not just another geography for Applied Computing - it is our primary market and a proving ground for the future of industrial AI."

"The country’s refining and petrochemical sectors are central to the global economy, and the decisions made here will influence energy stability and emissions worldwide. 

Orbital is already deployed in India, delivering impact at unprecedented scale, and our investment in Bangalore strengthens our ability to support operators as they modernise and transform their most critical infrastructure.”

Why India is becoming ground zero for industrial AI

India's country’s refining and petrochemical sectors are set to grow substantially over the next decade, and many of its critical assets rely on ageing infrastructure where AI-driven optimisation can have outsized impact.

India’s openness to technology adoption and its willingness to deploy AI at an operational scale make it one of the most important markets globally for industrial intelligence. 

The combination of demand growth, infrastructure complexity and a culture of technological experimentation positions India as the ideal environment for Orbital to deliver immediate system-wide benefits.

Jeavons is joined by Hari Ramani, Vice President of Commercial Markets, who will lead customer engagement and global market development:

“Energy operators in India are managing extraordinary complexity across ageing and emerging infrastructure. They’re looking for solutions that improve efficiency today while preparing for a more sustainable tomorrow. 

Orbital provides that bridge — delivering actionable, physics-grounded intelligence across entire facilities. The appetite for real-world AI adoption here is unmatched, and today’s expansion positions us to serve this demand at scale.”

Lead image: Dan Jeavons, Applied Computing.

Venture capital can be a mysterious space to outsiders. Discovering your route into the industry, or trying to decode the path to fundraising as a founder, can often feel challenging. Without a base level of familiarity, understanding the tangled web of relationships, norms, and practices that make VC tick can seem almost impossible.

What can make this even more difficult is getting to grips with some of the language used in the venture ecosystem. Even for those relatively familiar with the space, the VC phrasebook is always evolving, and it’s easy to be caught off guard when you hear people in the industry casually slip in new catchphrases you’ve never heard before.

With that in mind, I’ve put together a little pocket guide of five industry terms, some new, some not so new, to help you feel a bit more confident in ‘speaking VC’.

1. Signals: Beyond tangible metrics of startup progress such as revenue or number of customers, “signals” are subtler indicators that VCs use to decide which startups to back.

Far from being an exact science, these are breadcrumb-like cues that suggest a company has real potential, things like having founding team members who’ve previously worked for other high-growth startups, or receiving support from a renowned startup accelerator. (This list is non-exhaustive, of course, as there are many other signals one can consider.) None of these factors guarantees success, but they act as shortcuts for time-poor investors to quickly decide which startups to look into more deeply. For founders, understanding and emitting these signals can make the difference between getting lost in a sea of pitch decks and standing out in a crowded market. For VCs, it’s important to be mindful of the right signals that correlate to founder success and resist the urge to rely on vanity signals that might look good on the surface but have little bearing on future company performance.

2. Pattern-matching: Based on these signals, VCs ultimately have to make a judgment on whether or not a startup is worthy of investment (and even before that, whether or not to take the time to evaluate it as a potential investment). That’s where pattern matching comes in. At its core, the idea is simple: investors use previous experience to guide their decision-making.

For example, when weighing up a potential investment, they may be drawn to founders who have worked or studied at the same institutions as previous successful founders in their portfolio. Beyond this, VCs often lean on their own experience and network within a startup’s target market to assess its likelihood of success.

While there’s nothing revolutionary about this idea, it’s easy to see how relying on subjective, informal judgements can create conditions for various cognitive biases to play out. A seasoned and skilled venture investor will regularly break from their usual decision-making patterns and lean into contrarian bets.

3. Moat: So, you’ve established a top team and built a great product. But what stops the next business down the road from replicating exactly what you’re doing? That’s where “moats” come in.

These are a company’s built-in shields, the competitive advantages that make products hard to replicate and allow startups to stay ahead of their competitors over time. With advances in AI and no-code tools making it easier than ever for developers to build “bolt-ons” or even clone new products, tech founders must find ways to hold on to what makes them unique.

For investors, being able to see this defensibility is critical. Whether it’s fostering communities that encourage users to keep coming back (think Strava’s competitive social platform) or harnessing proprietary data to build something unique (think Spotify’s Wrapped campaign), moats are what make a startup sustainable over time in the face of competitive pressure.

4. Thoroughbred: You might be familiar with the term “unicorn”, used to refer to startups that have reached a $1 billion valuation. This simple signal of high growth potential is often held up as the holy grail for founders and VCs. Along similar lines, tech heavyweight and Phoenix Court co-founder Saul Klein recently coined the term “thoroughbred” as a new way to assess startups’ potential.

Instead of looking at valuation, “thoroughbred” refers to any company with annual revenues of $100 million or more. In his view, focusing on revenues is a stronger indicator of success and will encourage more policymakers and large investors to support those in the “innovation economy”.

5. Colt: Alongside thoroughbreds, Klein coined the term “colt” to refer to companies with annual revenues of $25 to 100 million.

While these companies may not have the same impressive track records as their thoroughbred counterparts, the idea is similar. High revenues sustained over time suggest a strong customer base and product–market fit, both of which are essential to growth and signal high potential to investors.

To sum up, the best route to learning VC lingo, as with any new language, is through immersion. If you truly want to understand the ecosystem and its rhythms, you need to learn from others who are fluent in the language. This could mean attending organised networking events for industry newcomers, building and maintaining relationships with contacts who already have experience in VC, taking an online training course for beginners, or subscribing to industry podcasts or newsletters.

As daunting as it may seem at first, exposing yourself to this language as often as possible is the quickest way to bring yourself up to speed, and once you are adept at speaking it, your arc of development will be poised for exponential growth. Before long, you won’t just be speaking the language, you’ll be shaping the conversation.

The post Translating VC: A pocket guide to venture capital keywords appeared first on EU-Startups.

A new report, The European Open-Source AI Landscape, has just been released by the StepUp Startups project. The report offers a snapshot of where Europe currently stands in the global AI race, and explores how faster adoption of open-source AI could boost competitiveness while strengthening the EU’s digital sovereignty.

Open-source AI refers to models, tools and datasets whose components (such as source code, model weights and documentation) are openly available. This transparency lowers the barrier for universities, public institutions, startups and established companies alike, allowing them to develop and deploy AI without being tied to proprietary systems.

According to the report, open-source is already embedded across the AI tech stack: more than half of developers rely on open models, datasets or tools on a regular basis. It also supports safer AI, giving researchers the visibility they need to test and evaluate models in depth.

A fast-moving global race

Since 2022, the number of publicly released AI models has more than doubled, and more of them now come with open weights. This gives developers far greater insight and control. Open models are also rapidly catching up with proprietary systems and, on some benchmarks, even matching expert-level performance.

Europe’s strengths: Collaboration and trust

Europe comes to this challenge with real advantages. The region boasts top-tier research, close collaboration between academia and industry, and major contributions to tools like scikit-learn, spaCy and PyTorch, which underpin thousands of commercial AI systems worldwide.

Many European AI startups are also releasing open-source models under open-source licences, providing building blocks that others can use and scale.

Yet adoption in European businesses remains relatively low: in 2024, just 14% of EU firms were using AI. To tackle this, the EU launched its Apply AI strategy in October 2025, focused on increasing uptake across European companies. The report highlights that open-source AI can play a key role in closing this ‘use gap’, offering transparent, reusable, and cost-effective tools aligned with EU values.

Scaling open-source AI: Europe’s opportunity

Access to computing remains a major challenge for European innovators. The 19 EU-funded AI Factories and expanded EuroHPC supercomputers aim to change that, giving startups and SMEs free access to the GPU capacity they need to develop European models, including open-weight systems.

This public infrastructure is already bearing fruit. In September 2025, Latvian SME Tilde launched TildeOen LLM, a 30-billion-parameter open-source language model, trained using 2 million GPU hours on the EuroHPC LUMI supercomputer.

A path towards sovereign and competitive AI

With inference costs falling by more than 99% in just two years, AI is rapidly becoming low-cost and widely accessible. Combined with Europe’s research strengths, multilingual talent and regulated approach, open-source offers a real opportunity for the EU to carve out a leading position.

Rather than focusing only on building the largest frontier models, Europe can take the lead by developing open, trusted, multilingual and sector-specific AI aligned with its industrial and societal priorities. Doing so will require investment, easier access to compute, and targeted support to help organisations – particularly SMEs – adopt and deploy open-source AI effectively.

Download the report to explore the full findings.

The post New StepUp Startups report: Scaling Europe’s open-source AI landscape appeared first on EU-Startups.

Antwerp-based cybersecurity company XFA has announced the closing of its €1.5 million Seed round to scale its platform and build a safety net for the modern, hybrid, and AI-native workplace.

This round was led by ScaleFund (Belgium) and Curiosity (the Netherlands), with participation from previous investors PMV, Seeder Fund, as well as experienced entrepreneurs from within and outside the tech sector, grouped under Investee.

This investment will allow XFA to expand beyond its current platform as well as harness the latest advances in cryptography and AI. 

“Throughout our careers, we saw the same problem everywhere: IT teams invest heavily in forcing control over devices, yet the majority of devices remain unmanaged and vulnerable,” said Lars Veelaert, CEO and co-founder of XFA.

“Our technology discovers every device, guides users to make required security updates, and verifies security without requiring management or prior knowledge of the device,” added Gijs Van Laer, CTO and co-founder of XFA.

XFA was founded in 2023 by Lars Veelaert, a former cybersecurity advisor, and Gijs Van Laer, who holds a PhD in cryptography from Johns Hopkins University. 

The company has a technology that verifies the security of any device at login without invasive management software or prior knowledge of the device. It states, “Traditional device security relies on invasive management software (MDM), a model increasingly incompatible with today’s flexible work environments. Research shows that the average work device is 350 days out of date on security updates, and current approaches only cover about 40% of devices. The remaining 60% – often personal devices, BYOD, freelance hardware, and other unmanaged tech – remain unaccounted for due to privacy concerns and logistical complexity.” 

XFA claims to have closed this gap with a privacy-first technology that detects every device used for work and verifies its security instantly at the moment of login.

The company’s solution can be deployed organisation-wide with a single 15-minute setup, enabling businesses to achieve complete device security coverage in a few weeks. 

“Security is undergoing a fundamental shift. With remote work, the rise of bring-your-own devices (BYOD), and flexible talent becoming the norm, companies can no longer rely on traditional ways of keeping devices safe. What’s needed is a simple, reliable way to know whether a device can be trusted the moment it connects. We invested in XFA because the founders understand this change better than anyone and bring the drive and expertise to build the next generation of cybersecurity at scale,” said Lisa Brouwer, Principal at Curiosity.

XFA partners with automated compliance platforms like Vanta to streamline device security evidence for certifications such as ISO 27001, SOC 2 and NIS2. It has customers across Europe, North America, and Asia.

The post Antwerp-based XFA raises €1.5 million to tackle this critical blind spot in modern workplace cybersecurity appeared first on EU-Startups.

Swedish energy company Elvy has secured a €500 million financing package from Scayl and a banking partner to fund home energy packages offered through a monthly subscription model. The packages include solar panels, heat pumps, and home battery systems, and are designed to remove the need for large upfront investments.

Elvy is providing integrated home energy solutions, combining smart technology with installation services and customer support to help households reduce energy costs and emissions as it expands across Sweden. Under the subscription, homeowners receive equipment, installation, maintenance, and coverage for the home’s electricity needs at a fixed monthly cost. The system is managed by Elvy’s AI engine, which monitors and optimises household energy generation and consumption.

Elvy’s CEO and co-founder, Johan Outinen, says the focus is not primarily on the technology itself, but on delivering peace of mind to homeowners:

Our customers want heating, warm water, and reasonable electricity costs. It shouldn’t require big investments or that they become energy experts in their free time to optimise energy consumption.

As electricity prices remain volatile across Europe, more homeowners are looking for solutions that offer cost predictability alongside environmental benefits. Elvy’s model is intended to help households reduce dependence on the grid, lower long-term energy expenses, and improve home sustainability and potential property value, while lowering barriers to adopting modern energy systems.

Supported by the €500 million financing, the company expects to make these systems available to tens of thousands of households and increase its capacity to onboard up to 15,000 new customers.

Stockholm-based energy company Elvy has secured €500 million from Scayl, a Swedish debt funding platform, and one of its banking partners to enable homeowners to adopt modern energy systems easily and affordably. 

With this funding, Elvy aims to finance subscription-based home energy packages for homeowners, which include solar panels, heat pumps, and home battery systems. 

“It’s less about the technology and more about what the homeowners actually want, peace of mind. Our customers want heating, warm water, and reasonable electricity costs. It shouldn’t require big investments or that they become energy experts in their free time to optimise energy consumption,” said Johan Outinen, CEO and co-founder of Elvy.

The rising volatility of energy prices across Europe, especially in Sweden, has prompted homeowners to seek solutions that provide both financial stability and environmental benefits. This shift in consumer demand is also driving a noticeable surge in investor interest across the home energy sector. 

Earlier this year, in August, Swedish CleanTech Aira raised €150 million to accelerate the electrification of residential heating in Europe. In July, London-based Sunsave raised €130 million to take solar mainstream with zero-upfront subscription model. Similarly, in January, German climate fintech Bees & Bears secured €500 million in financing commitments to fund home energy solutions. 

Founded in 2023 by Johan Outinen and David Wedar, Elvy provides fully integrated home energy solutions, including solar panels, heat pumps, and battery systems. It offers an energy package consisting of hardware, installation, maintenance and the houses’ electricity needs, at a fixed monthly subscription. 

According to the company, the package is managed by Elvy’s proprietary AI engine to control and optimise the energy generated and consumed by the households.

Elvy mentions that this new financing from Scayl will enable it to further accelerate growth and expand its capacity to onboard up to 15,000 new customers.

Debt funding platform Scayl provides non-bank lenders with access to flexible and transparent financing structures through API-driven integrations. 

“Elvy’s approach to home energy immediately stood out to us. Solar financing has existed for decades, but Elvy has created something fundamentally different: a product where customers see a net-positive economic effect from day one, rather than waiting years to break even. We’re excited to help scale this model in Sweden,” stated Medjit Yalmaz, CEO and co-founder of Scayl.

By partnering with banks and offering them exposure to European SME and consumer credit markets, Scayl enables its lending partners to deliver fully customised financing solutions to their end customers.

The post Elvy powers up with €500 million to help Swedish households beat soaring energy costs appeared first on EU-Startups.

Dutch payments firm Mollie is acquiring UK payments fintech GoCardless in a €1.05bn deal, the two fintechs have confirmed.

The two fintechs have billed the combination as creating a “payments powerhouse”, confirming rumours of the tie-up which surfaced in the summer.

GoCardless, which employs around 800 people, is a payment platform that lets businesses collect one-off and recurring payments, such as subscriptions and membership fees, via direct debit, rather than credit cards or bank transfers.

The fintech, which has also made a play in open banking, is headed up by Hiroki Takeuchi, a well-known figure in the UK fintech ecosystem.

Mollie, which employs more than 900 people, is primarily known as a payments fintech, focusing on the European SME market, processing tens of billions of Euros in transaction volumes each year. Mollie competes against the likes of PayPal, Stripe, Adyen and legacy players like JP Morgan.

The FT reported that the deal was made up of 90 per cent stock and a small cash element.

A spokesperson for GoCardless said it was too early to say if the deal would lead to job cuts.

The fintechs said that the combination creates a company serving over 350,000 businesses that integrates card payments and bank payments into a single offering.

Koen Köppen, CEO of Mollie, said: "GoCardless built the definitive solution to optimise this process with its global bank payment network. By bringing them into Mollie, we take a huge step towards fulfilling our vision and creating one complete platform for sustainable growth."

Takeuchi, co-founder and CEO, GoCardless, said: "This deal brings together two highly complementary businesses that have built best-in-class products across Europe and beyond.  

"By combining our expertise in card, bank and hyperlocal payments into one provider, we can better serve our customers, accelerate growth and raise the bar for the industry. It’s a win for European fintech and we’re confident that the new company will be greater than the sum of its parts.”

GoCardless, which is profitable, was valued at $2bn in 2022.  It is backed by Balderton Capital, Accel, Permira and BlackRock.

Mollie, which is backed by Blackstone, was valued at around $6.5 billion in 2021.

The British Business Bank has announced a €5.7 million (£5 million) commitment to the London-based British Design Fund (BDF), an early-stage fund and angel network that backs UK product-focused businesses, through its Regional Angels Programme.

The fund is managed by Sapphire Capital Partners LLP and seeks to support UK-based startup enterprises that design and manufacture physical products.

Damon Bonser, CEO of BDF Advisors, says: “We welcome this commitment from the British Business Bank, which supports our continued efforts to back UK product innovation. We meet founders every day who are addressing fundamental problems in the world through innovative manufacturing and engineering technologies. This commitment enables the British Design Fund to continue its work with more founders and to help founders progress their ideas into viable early-stage businesses.”

In 2025, UK activity in early-stage manufacturing and product-centric innovation has been reflected in several targeted investments, particularly through regional funds.

The British Design Fund’s new €5.7 million commitment sits alongside deployments from the Northern Powerhouse Investment Fund II, which backed Atomik AM with €713k to scale its advanced manufacturing operations, and Holdson with €1.7 million to expand its electroform surface-finishing technology for aerospace, automotive, defence and fusion applications.

These rounds illustrate sustained public–private support for physical product development across UK regions, complementing the British Business Bank’s broader efforts to reduce geographic disparities in access to early-stage equity.

Mark Barry, Senior Investment Director at British Business Bank, adds: “The UK has an abundance of worldclass talent in advanced engineering and manufacturing and we’re delighted to partner with BDF to invest in these early-stage opportunities right across the country.”

Founded in 2016, BDF engages with founders developing UK-based product businesses across a range of sectors, such as health, sustainability, and assistive technology. The fund’s portfolio includes a diverse range of companies located across the UK, from the South West to Scotland.

The Regional Angels Programme, launched in 2019 with the objective of addressing regional imbalances in access to early-stage equity finance, targets angel networks and other early-stage investors outside of London.

This commitment supports this mission, enhancing access to capital for early-stage businesses across diverse sectors.

Chancellor of the Exchequer, Rachel Reeves, said: “We want the UK to be the best place to startup and scale-up. Half of new jobs in this country are created by scale-ups, and our tech, health and manufacturing sectors are second to none.

“This commitment by the British Business Bank will support even more entrepreneurs to take the leap and we have increased incentives at the Budget giving companies the talent and capital to grow. Our message is clear – if you invest here, Britain will back you.”

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