AI-native restaurant management platform Nory has raised $37 million in a Series B led by Kinnevik, bringing total funding to $62.6 million. The round comes just one year after the company’s Series A, led by Accel, which also participated in this round alongside existing investors. Nory is an AI-powered restaurant management platform that unifies business intelligence, inventory, workforce, and payroll into one control centre to streamline operations and boost margins. It plugs into a restaurant’s existing tech stack and uses real-time data plus predictive analytics to forecast demand, optimise labour and inventory, and deliver actionable recommendations to frontline teams. Built for independent, multi-location, franchise, and enterprise groups, Nory replaces scattered spreadsheets with a single source of truth for consistent, profitable execution. Created by industry insider Conor Sheridan, it’s purpose-built for hospitality and has helped restaurants cut operating costs by nearly 20 per cent and lift core net profits by up to 50 per cent. By automating time-consuming back-office tasks like business analysis, digital guest engagement, rota planning, procurement, and finance, Nory saves over 100 hours of admin per site each month, while its AI learns from historical operations and sales to deliver real-time insights and recommendations. Conor Sheridan, Founder and CEO of Nory, commented: At a time when hospitality is under pressure, we are putting restaurants back in control of their profitability and their destiny. The future of hospitality isn’t robots or gimmicks. It’s AI that makes restaurants smarter, leaner, and more profitable, with automation that frees teams up to focus on what matters: great food and even greater customer experiences. The Series B will fund AI enhancements to Nory’s platform, including hiring world-class data scientists, advancing proprietary algorithms, and deploying autonomous AI assistants. It will also accelerate the company’s US expansion.

Madrid-based Lightbase, an AI-powered developer tools platform, announced its official launch along with a €2.2 million pre-seed funding round. The investment will fuel Lightbase’s mission to accelerate the pace at which engineering teams deliver value by eliminating one of their most persistent bottlenecks: knowledge fragmentation. The round was led by Picus Capital, with participation from Kfund, Helloworld, and angel investors Jorge Poyatos, Albert Nieto, Christian Beedgen, and Rodrigue Schäfer. In growing engineering organisations, the real productivity bottleneck isn’t writing code, it’s finding and sharing the knowledge needed to change it. Developers spend roughly a third of their time coding, with the rest lost to meetings, interruptions, and coordination. Senior engineers carry the heaviest load, fielding questions and mentoring. The problem deepens with new hires, who face a steep learning curve and remain dependent on teammates because there’s no reliable, self-serve way to navigate the codebase. When experienced engineers switch teams or leave, critical context disappears, creating costly, hard-to-close knowledge gaps. Lightbase, an AI-powered code intelligence platform, solves this by turning codebases and engineering tools into a living knowledge system. It plugs directly into repos and workflows, analyses the code, and uses AI to deliver instant, accurate answers about how your systems work, far beyond what generic AI coding assistants provide. The result: fewer interrupts, faster onboarding, preserved institutional knowledge, and a meaningful lift in real engineering throughput. As teams scale and systems grow more complex, Lightbase gives engineers, product managers, and new hires rapid insight into architecture, data flows, and dependencies. This reduces constant pings to senior developers and can free up to 50 per cent of time lost each week to onboarding, meetings, and repeated explanations. This pre-seed investment will accelerate Lightbase’s product development and expand its engineering team. Following strong results with early customers, Lightbase is opening its platform to more companies across Europe and North America.

Portuguese-founded defencetech startup Tekever has opened its biggest UK site, where it will manufacture drones for surveillance and intelligence purposes. The 254,000-square-foot facility is located in The Spectrum Building, a historic Grade 11-listed building designed by architect Sir Norman Foster in Swindon and is expected to open in 2026. The defencetech startup, which became a unicorn in May this year, says it will produce one of its largest drones in the UK for the first time, and increase production of another from the site. The UK has already brought £270m of Tekever drones supporting Ukrainian forces attacking Russian air defence systems. The opening of the new site forms part of a five-year Tekever initiative aiming to create over 1,000 highly skilled jobs in the UK and invest more than £400m into British drone production and advanced AI warfare capabilities. It will be the manufacturer's fourth UK site and its largest so far. Swindon has a long-standing history linked to UK defence.  It produced the Supermarine Spitfire during the Second World War while drone companies Stark and Munin Dynamics are located in Swindon. Karl Brew, Tekever, head of defence unit, said: "Our new facility will not only increase Tekever’s capacity to innovate and meet the rapidly evolving needs of our clientele, but also enable our business to operate more efficiently as we continue to scale our ambitions in line with our fervent commitment to transforming the UK’s defence industry into a leading powerhouse on the global stage.”  Will Stone, MP for Swindon North, said: "This announcement supports my ongoing commitment to establishing a Drone Cluster of excellence in Swindon, creating highly skilled, well-paid jobs while also fostering new education and training opportunities for young people in our community.”

Turin-based Plino, which uses generative AI to streamline analysis of accounting, cost, revenue, and cash-flow data for SMEs, has closed a €650,000 funding round. Investors include Exor Ventures, Berkeley SkyDeck Europe (UC Berkeley’s accelerator with Cariplo Factory and Lendlease), and a syndicate of Italian backers led by Techaround.vc, joined by Zooga.vc and several business angels, including CFOs and accountants. Incubated since 2024 at I3P, the Innovative Companies Incubator of Politecnico di Torino, Plino was founded by Pietro Galimberti, Viola Bonesu, and Enrico Castelli. The founders combine backgrounds in philosophy, engineering, finance, and AI, convinced that innovation happens at the intersections. Italian SMEs struggle with fragmented financial workflows - data scattered across accountants, software, and banks; manual analysis spread over dozens of spreadsheets; and delays that push managers to rely on instinct rather than evidence. Plino replaces this with a single platform for real-time tracking of sales, costs, revenue, and cash flow, liquidity forecasting, and automatically generated, easy-to-read reports. Today, Plino supports more than 100 SMEs across Italy in sectors such as manufacturing, services, food, hospitality, and construction. The goal is simple: give SMEs a fast, accurate system for making strategic, data-driven decisions. The new capital will accelerate the development of AI features such as cash-flow forecasting, natural-language report generation, and profitability analysis at the product or project level. In parallel, Plino will grow its product, technology, and sales teams and deepen partnerships with professional firms and trade associations, bringing AI-driven innovation into the accounting profession.

It's not every day that someone leaves a job in one of the world's most successful fabless semiconductor companies – ARM – to join a startup, but Noel Hurley met a startup that was solving a problem in Edge AI that had plagued the sector for decades. When he first came across Literal Labs in the summer of 2023, it was spinning out of Newcastle University in collaboration with the Centre for AI Research in Norway. They had been working for five years on logic-based AI and what's called Tsetlin machines – more on that shortly. Having spent 30 years in the processor and computer science space, Hurley was familiar with the challenges around AI adoption — especially in industrial markets.  He admits, "promises were made about edge AI, but progress was limited." "Neural networks required expensive new hardware, consumed a lot of energy, and were slow to deploy." When he saw Literal Labs' research results, he had an "aha!" moment. Here was a technology that solved many of those problems — and could run on existing hardware.  "That meant we could engage customers early and deploy quickly. It was clear to me this wasn't just interesting research; it was the basis for a company," he shared. I sat down with Hurley to learn about Literal Labs.  What exactly is a Tsetlin machine?  Today's neural networks are built around multiplication — multiplying numbers together. Multiplication is an expensive operation on a chip: it requires large circuits and burns a lot of energy.  That's why our power consumption skyrocketed.  "Many chips now advertise 'neural network accelerators,' which are essentially just large arrays of multiplication circuits," contends Hurley, explaining that a Tsetlin machine works differently.  "Instead of heavy mathematics, it uses propositional logic—'if/then" statements — combined through a voting algorithm.  During training, the model decides whether to include, exclude, or ignore each of these statements. The result is a dense network of logic that can be deployed onto silicon far more efficiently." Low-cost meets low power Literal Labs' AI models are designed to run on very low-cost, low-power hardware — specifically, devices priced under $5. dollars. These devices are typically modest microcontrollers or system-on-chip units rather than sophisticated, high-performance computing platforms. The key point is that no GPU or specialised accelerators (like TPUs or custom AI chips) are required for inference. Hurley attributes Literal Labs' lower-energy results to logic-based circuits, which are more energy-efficient than multiplication circuits. "Our approach is about matching algorithms to the strengths of existing silicon, rather than forcing silicon to handle operations it wasn't optimised for." Most of the operations come down to lookups or comparisons, which microprocessors already handle extremely efficiently, according to Hurley. By replacing multiplication-heavy circuits with logic-based circuits, you can achieve similar outcomes at a fraction of the cost and energy. 54× faster, 52× greener If this all sounds a bit complicated, well, the results speak for themselves when it comes to MLPerf benchmarking standards — these provide fair, representative, and repeatable ways to measure how well different hardware and software systems run AI workloads. Literal Labs' benchmarks show dramatic results: 54 times faster performance and 52 times less energy use compared to equivalent neural networks.  According to Hurley, when he joined in October 2023, the team were already seeing speedups ranging from 5x to 250x over traditional algorithms.  "Last year, when we published our MLPerf benchmarks, we confirmed 54x faster performance with 52x lower energy consumption. What was even more encouraging was that the datasets used in MLPerf were significantly larger and more complex — up to 400 gigabytes compared to the one-megabyte sets we tested earlier. Despite this increase in complexity, the gains held up. That demonstrated the robustness of our approach." Further, logic-based AI is naturally explainable, ensuring accountability for the model's decision-making.  Literal Labs shows a cheaper path forward in edge AI Literal Labs sees immediate traction in industrial and edge AI.  All in all, Literal Labs creates true commercial value because it reduces system costs by lowering compute complexity, inference costs, and bill of materials: "Think about battery-powered devices, safety-critical products, or heavily regulated markets. In these environments, explainability, energy efficiency, and compute constraints all matter," Hurley explains.  Historically, attempts to apply AI in these markets either failed or were severely limited. Companies couldn't afford to replace equipment already in the field, so they tried to bolt on connectivity, send data to the cloud, and process it there. That added costs, dependencies, and supply chain complexity without delivering a clear bottom-line return. "By contrast, what excites customers about our approach is the ability to deploy AI directly onto existing devices—without expensive upgrades. We can bring intelligence to the edge in places that were previously off-limits," he shared.  Literal Labs empowers engineers to train their own models Part of Literal Labs' vision is to let customers train their own models. Literal Labs' commercial product is a toolchain that allows customers to train models on their own datasets. The target user is a competent software engineer — not necessarily a machine learning specialist. According to Hurley, the tool is highly automated:  "Typically, you don't just train a single model—you train hundreds, then prune and select the best. We've built automation into that process. Customers can run it on-premise, in their private cloud, or directly at the edge. This has several advantages: it addresses data sensitivity concerns for customers unwilling to send datasets off-site, and it makes adoption easier by fitting into their existing infrastructure." Company CTO, Leon Fedden, previously led the deep learning platform at AstraZeneca. He brings that expertise in combining classic AI techniques with automation to ensure its toolchain is robust and scalable. The company is collaborating with utilities to develop smart wastewater systems, where sensors can identify what constitutes "normal" and "abnormal" flows, triggering early warnings. The same applies to electricity networks or other utility grids with vast numbers of remote sensors. Another key area is machine health, which involves predicting wear and tear and sending maintenance before a machine fails. That's hugely valuable in industrial settings. Right now, it's focusing on time-series data — such as vibration sensors or audio — and on tabular data. These domains are full of opportunities for better forecasting and process decisions. "We're building capability for image data as well, but our initial focus is time-series and tabular," explains Hurley.  By avoiding costly hardware swaps, Literal Labs eases Edge AI adoption Many startups in edge AI have struggled to commercialise, due to the challenge that deploying AI in many instances requires changing hardware. Companies didn't want the expense or disruption of installing new equipment. Hurley explained: "Our advantage is that we don't require special accelerators—just a standard microprocessor, which every industrial IoT device already has.  The only fundamental constraint is whether there's enough memory available for an additional function. That's a big difference from approaches that depend on entirely new hardware." Currently, Literal Labs is running five proof-of-concept projects with customers and aims to launch our product in the second half of this year. Hurley admits that AI is a noisy space for startups:  "A lot of promises get made. But we see ourselves as a disruptor. Our strategy is to stay focused: find strong problem areas, work closely with customers, and deliver measurable value. That was something I learned early on at ARM. Robin Saxby, ARM's first CEO, always stressed focus. I joined as employee number 40-something, and that lesson still applies today." Literal Labs' focus this year is on execution: expanding the team, delivering proof-of-concepts, and preparing for its product launch. From there, it'll broaden its data capabilities beyond time-series and tabular, and continue building out customer-facing tools. In the longer term, the vision is to make logic-based AI a mainstream alternative to neural networks, especially in energy- and compute-constrained environments.

1.7 million people who aren’t formally registered as visually impaired, but still suffer from sight loss severe enough to affect their daily lives. While services such as Be My Eyes – an app which connects blind and low-vision users with sighted volunteers and companies, through live video and AI to tackle the inaccessible parts of everyday life – do a stellar job in providing support for blind and low-vision people, there is always room for more, especially in real-time, hurried scenarios such as navigating public transport. Many people in the UK struggle to navigate public transport because they simply can’t read the signage.   Zooming in with a smartphone only distorts the text further, while mainstream transit apps often lag or fail to capture real-time updates. The result? Missed buses, wrong trains, the risk of getting stranded and dependence on strangers. But now there’s a solution. Founded in March by UCL students, Solora has developed the RideOnTime app, which uses AI to translate transport signage into clear visuals—and audio if desired—in real time, offering people with sight loss a dramatically easier way to navigate bus and train stations. Despite being in the thick of his dissertation in Human-Computer Interaction, CEO Jun Bak was kind enough to offer some insights into the solution and the company behind it.   From academia to an app store Bak has a background of around a decade in UX design and digital strategy, with deep experience in user experience, conversion optimisation, and product strategy across in-house and agency roles. More recently, he completed a Master’s in Human-Computer Interaction at UCL. During the course, he met four classmates, and together they worked on a disability interaction module, co-designing an application with a visually impaired user, which eventually became Solora. The technology is both simple and powerful. The app detects the signboard using AI.  “Then, we adjust technical factors like shutter speed and exposure to reduce distortion," explained Bak. “Combined with additional coding and AI enhancements, we’re able to “fix” the display so users can clearly read the information. We’ve gone through several rounds of testing, and the results have been very positive.” UX-testing with those with lived experience I was curious about the UX testing, as I’ve unfortunately met a robotic wheelchair startup that only tested its tech in able-bodied people and a smart home platform for blind and low-vision people, which was only put forward for testing weeks before its launch.  According to Bak, the team was fortunate that the project began as part of a disability interaction module, which allowed them to co-design the solution directly with a visually impaired user living with Stargardt disease. “By learning about her daily transit challenges, we identified LED signboards as a major issue.” For broader testing, Solora collaborated with Vision Ability, a nonprofit in East London.  “We hosted a workshop with about 20 visually impaired users, took them to a station, and allowed them to try the app in real-world situations.  Their feedback was overwhelmingly positive. Some participants told us they were just beginning to travel independently, and that this was one of their biggest frustrations.” Solora launched on the UK App Store as a pilot and now has about 50 active users.  “We’re continuously monitoring performance through analytics and recordings to measure accuracy and optimise further,” explained Bak.  Why mainstream transit apps and support services aren’t enough In the UK, disability rights in public transport are primarily protected under the Equality Act 2010 and the Public Service Vehicles Accessibility Regulations, which require transport providers to make reasonable adjustments, so I was curious why public transport authorities weren’t doing more about the problem. According to Bak: “Quite rightly, there is extensive guidance and regulation concerning the level of support that should be offered to sight-impaired and severely sight-impaired people on our transport network.  And visual cues, such as a guide dog or mobility cane, mean it can be easier for passenger assistants to proactively identify when a sight-impaired or severely sight-impaired individual may require additional help in a bus or train station.  But there is a massive group of underserved people in the UK who suffer from varying degrees of sight loss.  We know that individuals with different forms of sight loss find it difficult to navigate the transport network, but for a number of reasons, they may be reluctant to ask for assistance." Further,  some larger authorities may be aware of the specific challenge with the signage, but they often assume that having a live feed solves it.  “The issue is that LED signboards display the most accurate, real-time information — based on the actual movement of buses and trains.  Apps may lag or require multiple steps to check timetables, but with RideOnTime, users can just point their camera and instantly get the information.”   Solora has already been recognised with awards, including Most Inclusive Product at UCL’s latest Venture Builder Programme and the SustainTech Pitching Competition, winning £1,500 and £1,000, respectively. Now its applying to UCL’s Hatchery program, which supports spin-off startups over two years.”  In terms of business model, the app will always be free for visually impaired users. Long term, Solora is looking at white-labeling — integrating its solution into existing platforms run by transit authorities. According to Bak, the current UK launch is essentially a pilot to gather data, prove impact, and run focus groups.  “We’re already in conversations with transport authorities about integration, and we’re actively seeking our first client.” The team is also exploring EU mobility funding opportunities and ways to expand beyond the UK. However, the biggest challenge has been accommodating individuals with varying levels of vision loss — some people are severely visually impaired or blind, and they want to use the app too. “We’re developing features like AI-guided detection: users can wave their phone, and the app will guide them with audio cues to point toward the signboard.  This requires extensive testing with blind users, but it’s our next major step,” shared Bak. Solora is proving that startups can tackle real-world problems when they put lived experience at the heart of design. By working directly with people across different levels of vision loss to shape and test new features, the team is building technology that doesn’t just work in theory — it genuinely meets the needs of those who rely on it every day. Its a valuable playbook for all social impact startups.

Germany-based agricultural photovoltaics company feld.energy has closed a seed round of more than €10 million led by HV Capital, with participation from Future Energy Ventures, AENU, and Angel Invest. feld.energy enables farms to grow food and generate solar power on the same land with modular, machine-friendly agricultural photovoltaics (Agri-PV) systems for arable fields, pastures, and speciality crops. Operating end-to-end, from feasibility to construction, the company makes dual land use easy to deploy and economically attractive, even without subsidies. Under its lease model, farms can earn over €100,000 across 20 years while maintaining agricultural output. This supports the company’s vision to show that farming and renewable energy can reinforce one another to create lasting value. By pairing clean energy with agriculture, feld.energy strengthens farm income and resilience, reduces water use, and advances Germany’s energy transition. The opportunity is significant, as Germany targets about 60 per cent renewables in gross final consumption by 2050, and Fraunhofer ISE estimates 2,900 GW of technical Agri-PV potential nationwide. Co-founder and CEO Dr. Adrian Renner says feld.energy aims to bolster agricultural resilience and accelerate the shift to a climate-neutral economy by enabling farmers to generate clean power without reducing food production. This funding will help us strengthen our team and scale our solution so that farms everywhere benefit from this dual-use approach, Renner added. With fresh funding, feld.energy will accelerate growth, expand operations, and strengthen its team. Its long-term aim is to make dual-use farmland, boosting farmers’ income while helping the planet, the rule rather than the exception.

Last week, we tracked more than 95 tech funding deals worth over €3.1 billion, and over 10 exits, M&A transactions, rumours, and related news stories across Europe.Click to read the rest of the news.

German software company encentive has raised €6.3 million to expand its AI platform, connect more industrial assets, enter new markets, and strengthen its technological leadership. The round was led by General Catalyst, with participation from existing backers Summiteer, SIVentures, Vireo Ventures, HelloWorld, and angels Stefan Müller and Bernhard Niesner. As industry, the world’s largest energy consumer, electrifies to reach net zero, power demand is rising, while expanding renewables increase supply and price volatility. In this environment, harnessing flexibility becomes a decisive lever for competitiveness and decarbonization. encentive reduces industrial energy costs and emissions with its AI energy-management platform. Its core product, flexOn, serves as an intelligent control centre that aligns bidirectional energy flows with local and market renewable availability, automatically shifting consumption to green, low-cost periods and leveraging existing storage and flexibility. By unlocking flexibility in refrigeration, heating processes, batteries, and production lines, flexOn generates optimised schedules and autonomously controls assets in real time, helping medium and large industrial users (≥2 GWh/year) cut electricity costs by up to 20 per cent while significantly reducing CO₂. Already deployed at leaders such as Metro Logistics, Dachser, and Klingele, and now used by major utilities as a flexibility platform, encentive will use the new funding to hire talent and scale core capabilities. This will enable large customers and partners to integrate flexOn independently via a dedicated onboarding suite as it expands into new sectors and markets.

Evertrace – the founder detection engine for data-driven VCs – today announced the acquisition of Whisper AI. Whisper AI brings deep expertise in company data, trade registry integrations, and a strong foothold in the DACH market – a key step in Evertrace’s wider European and global expansion. The acquisition accelerates Evertrace’s mission to give investors the earliest and most precise signals on emerging founders and companies. By combining Whisper AI’s registry and company data with Evertrace’s detection engine, the company moves closer to executing on this mission and be the key player in the market. "Whisper AI’s expertise in company registries and their position in the DACH region give us access to a unique set of data sources and a crucial market. Together, we can strengthen our ability to surface the founders and companies investors need to know about - earlier than anyone else,” said Jacob Graubæk Houlberg, Co-founder at Evertrace. We founded Whisper AI to make company and registry data more accessible and actionable to VC investors. Becoming part of Evertrace allows us to scale that mission significantly - and directly contribute to building the leading sourcing engine for early stage investors,” said Nikolai Niklaus, founder of Whisper AI. Whisper AI’s technology will be fully integrated into the Evertrace platform, giving customers richer signals, faster updates, and broader geographic coverage. About Evertrace Evertrace is the founder detection engine for data-driven venture capital investors. Using machine learning and unique data signals, Evertrace helps funds identify founders earlier than anybody else About Whisper AI Whisper AI specializes in advanced company data and registry integrations, with a particular focus on the DACH market. Its technology enables the early detection of new companies and founders for European early stage investors by turning complex data pipelines into actionable insights

This week, we tracked more than 95 tech funding deals worth over €3.1 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 ?? Mistral bags €1.7B funding round as ASML takes significant stake ?? EcoDataCenter secures €600M for sustainable high-performance AI and cloud growth ?? Fintech Factris secures €100M funding facility ??‍?? Noteworthy acquisitions and mergers ?? Bending Spoons to buy Vimeo in $1.38B deal ?? Hedepy acquires HearMe to become CEE’s largest online psychotherapy platform ?? fonio.ai acquires fluently to strengthen DACH presence ?? Opus acquires Embarc to accelerate early-stage entrepreneurship  ?? Opper AI acquires FinetuneDB for AI model tuning ? Interesting moves from investors ? Claret Capital Partners secures €350M second close for Fund IV ?Quadrille Capital raises €500M to invest in European and US tech ? From Lovable to ElevenLabs: Antler study charts Europe’s fastest-ever unicorn boom ?️ In other (important) news ?? OpenAI to roll out ChatGPT Edu in Greek schools and support startups ? ElevenLabs confirms employee share sale at $6.6BN valuation, double valuation of nine months ago ? BlackRock-backed Scalable Capital wins European banking licence ?? Quantum Systems commits €50M to UK expansion ?? AI coding assistants save UK government workers 28 working days a year, claims government  ? Recommended reads and listens ?? One year on from Draghi report: Europe’s innovation future hangs on the 28th Regime ? “European startups are asked to run a marathon with their shoelaces tied” ☕ The LAP coffee Berlin backlash: when innovation meets resistance ?? CUTISS secures €57.9M Series C to advance regenerative skin therapies ?? Innovation lives on: European startups shine at IFA 2025 ? Beyond the hype cycle: Why retention and community will decide the winners in vibe coding ? European tech startups to watch ?? Kashimi raises $1.36M to expand alternative payment infrastructure ?? Renewcast raises €1M from 2C Venture to accelerate global expansion ?? Saltfish emerges from stealth with $730,000 in initial funding ??  uRoutine raises £555,000 to fight doomscrolling with a ‘productive social network’ ?? Eterny raises €400,000 to tackle the problem of forgotten assets ?? Innovate UK backs Hormona with £100,000 grant for menopause diagnostics

PayPal-backed UK fintech Modulr has reported a reduction in annual pre-tax losses of £11m in 2024, as it targets US expansion and pulls back from working with crypto clients. Modulr provides white-label payment infrastructure for businesses, calling itself an “embedded payments platform”. Modulr, which has an Electronic Money Institution (EMI) licence and employs over 300 people, provides payment services for the likes of Sage, Wagestream and HMRC. Modulr is backed by PayPal's VC arm. Financial results for Modulr Holdings show pre-tax losses of £11m in the year ending 2024, a reduction compared to losses of £13.9m the year previous. Revenue came in at £52.8m, compared to £47.9m the previous year. Modulr says its losses were funded by its 2022 £83m Series C funding raise and that Modulr remained “well funded” at year-end 2024, with £31m of cash. Modulr said that during 2024, it focused on client sectors of travel, merchant payments and lending but “ceased active marketing” into non-focus sectors, including crypto, remittance, and consumer banking. Modulr is understood to have previously worked with crypto outfit Ripple but it's unclear how many crypto clients it had. It does, however, have some crypto clients, it said. It cited the “increasing complexities, risks and costs” of operating in these sectors as the reason for pulling back. Additionally, it cited new Consumer Duty rules, aimed at setting strict standards of consumer protection in financial services, and Authorised Push Payment rules, which it said “disproportionately impact those sectors”. Separately, the UK fintech said it had made its first international move, securing a contract with a “major" US financial technology firm. Last year, Modulr acquired UK-based accounts payable fintech Nook.  Modulr processes over 200m transactions and over £100bn of payment value on its platform, on an annualised basis. It has over 240 enterprise and over 4,000 SME customers. Modulr said: "Our statutory group accounts for 2024 show double-digit growth and a strong balance sheet. We are growing strongly in 2025 and are on track to be profitable. "We are scaling across a number of verticals and have seen particular growth in payroll, accountancy, travel and lending. In addition, we continue to serve some customers in other sectors, including crypto companies, remittance firms and consumer banking, which continue to become a declining proportion of our revenue."

Patents are the backbone of protecting innovation, yet the process of securing them in Europe can take years and cost founders precious time and money.  Swedish startup Lightbringer, founded in 2023, believes it has a better way.  I sat down with CEO and co-founder Dominic Davies to hear how his journey from software engineer to patent attorney — and a breakthrough moment with GPT-3 — sparked the creation of a category-defining legaltech company.  Lightbringer aims to transform how patents are created and managed. It combines AI-powered tools with experienced patent attorneys to offer a faster, clearer, and more accessible patent process for innovators, startups, and tech teams. I spoke to CEO and co-founder Dominic Davies to learn more. A eureka moment with GPT-3 sparked Lightbringer’s creation Davies originally studied software engineering at Imperial College London and started out working for Merrill Lynch. He admits,“after a few years in banking, I realised it wasn’t as exciting as I’d hoped. I wanted to work with cutting-edge technology, and one route was through intellectual property. So I retrained as a patent attorney at the world’s oldest patent firm in London and became fully qualified.” Over the past 20 years, while practising as a patent attorney, he continued writing software to solve problems in his field. At one point, he founded a law firm called Invent Horizon, where he developed software to automate all administrative work so that the firm could operate with only lawyers and no administrative staff.  He had also been working for years on software to write patents.  According to Davies, “for nearly a decade, it didn’t work — the AI just wasn’t good enough yet.”  “Then, in 2022, I read that GPT-3 was available via API. I plugged it into my project, and suddenly it sprang to life. That moment was both euphoric and terrifying. Euphoric because the software finally worked.  It was terrifying because I immediately realised the key problem I’d spent ten years grappling with — and that underpinned my career—had just been solved. I couldn’t sleep for a month. Eventually, I decided I had to act. I approached a couple of former founders, showed them a demo, and they said right away: “Let’s build this.”  That was the beginning of Lightbringer. Slow, costly, complex: the reality of filing a patent in Europe The current patent process looks something like this: Imagine you’re building a product and preparing to show it to customers, partners, or investors. Someone advises you that unless you file a patent application, you won’t be able to protect your technology. All in all, patents are a laborious process. The European patent grant procedure takes about three to five years from the date your application is filed. It is made up of two main stages.  The first comprises a formalities examination, the preparation of the search report and the preliminary opinion on whether the claimed invention and the application meet the requirements of the European Patent Convention.  But before you get to filing your patent, you usually need to find a patent lawyer. You book a meeting, explain your business and your technology in detail, and only then does the lawyer begin drafting an application. According to Davies, “it’s expensive because you’re working with highly qualified people, and it’s slow — it usually takes at least a month before you have a draft. The lawyer has to spend significant time building context for your invention and conducting research.” Reimagining patents with SaaS-style onboarding  Lightbringer aims to speed up the legal part of the process by replicating the seamless onboarding you’d expect from SaaS tools.  “Think of signing up for Google or HubSpot—you just create an account and you’re off. That’s what we’ve built for patents,” explains Davies. On the Lightbringer homepage, inventors can immediately begin describing their ideas. The system guides them through the process, helps them articulate the details, and explains how the patent process works.  Drafts can be generated within hours instead of months.  It’s largely self-serve, but with a human in the loop: qualified attorneys review the AI’s work, speak with inventors, and ensure everything is accurate and aligned with their needs. Since launching its subscription model in May 2024, Lightbringer has already filed more than 100 patents, attracted over 500 users, including founders and legal teams, and achieved a 90 per cent success rate for patents filed within just 30 days. The platform reports 95 per cent user satisfaction and delivers workflows up to ten times faster than traditional drafting processes. The company’s customers are early adopters, companies that want to buy legal services the way they buy SaaS. According to Davies: “They’re used to tools like Vanta or HubSpot, so they expect a consumer-like experience. That’s what we deliver.”  While the company is primarily working with smaller companies right now, it’s built an AI-first virtual patent department that can scale to any company. Davies admits that the company would love to work more with law firms, but they can be conservative, and there’s an inherent business conflict.  “Their model is built around billing by the hour, and we’re reducing the time it takes. Some firms are becoming more open, but our core users are technology companies themselves.” How Lightbringer keeps startup IP safe I was curious about data security in that founders are essentially putting their intellectual property into a startup’s software platform. According to Davies, security was a priority from day 1. Lightvringer is SOC 2 Type II certified. Customer data is protected and segregated. Its contracts with LLM providers, such as Google and OpenAI, ensure that it does not train on customer data: “We actually have stronger data security provisions than many alternatives.” That said, the company is very aware of developments — like the New York Times lawsuit against OpenAI that exposed private data — and for that reason doesn’t use OpenAI for certain key functions.  Lightbringer raised a €4.2 million Seed round in 2024 and is growing quickly. It has over 70 customers, many of whom, explained Davies, previously worked with traditional firms.  “They love being able to handle patents in a modern way.” Lightbringer eyes expansion as patent automation takes off Looking ahead to 2026, Davies believes companies will take a hard look at how they buy business services — legal, accounting, patents — and will demand more modern, efficient options.  “We’re placed to meet that demand. We also plan to expand to the US, which we see as a key market. For now, our core market is northern Europe and the UK.” Lightbringer describes itself as “category creators.” According to Davies, investors see what’s coming, sharing: “They know the way business services are sold is changing, and they see us as well-positioned to grab the market. It’s disruptive, especially for the patent industry, which could be one of the first legal sectors to undergo major automation.”

AI coding assistants are saving UK government workers 28 working days a year, the government claims, as it looks to leverage AI to save £45bn across the public sector. AI coding assistants are becoming increasingly common in the private sector, and the UK government is hoping to use them to make billions in savings across government departments. New trial results from the UK government show that government coders and tech engineers have saved almost an hour a day by using AI assistants to help them write code and build new technology. This is equivalent to 28 working days a year, the government said. The trial involved more than 1,000 tech experts using AI coding assistants across 50 different government departments. They used coding assistants such as Microsoft GitHub Copilot and Google Gemini Code Assist. It helped them build more tech like Whitehall’s Humphrey AI assistant and healthcare tech, the UK government said. The government said savings from the AI assistants mostly came from using them to write first drafts of code that experts then edit, or using them to review existing code. It said just 15 per cent of code generated by the AI coding assistants was used without any edits. The results show that 72 per cent of users said the tools offered good value, while over half ( 58 per cent), said they would prefer not to return to working without AI assistance, whilst 65 per cent reported completing tasks faster and 56 per cent said they could solve problems more efficiently. Technology Minister Kanishka Narayan said: ”This is exactly how I want us to use AI and other technology to make sure we are delivering the standard of public services people expect – both in terms of accuracy and efficiency. With a £45 billion jackpot at stake, it’s not an opportunity we can pass up, as it can help cut backlogs and save money.”

Ukrainian defense technology company Falcons has raised funding from US-based Green Flag Ventures to scale production of its radio frequency (RF) direction-finding system and work toward NATO certification. Founded in 2022 following Russia’s full-scale invasion, Falcons develops cost-effective systems designed for GPS-denied environments. Its flagship product, ETER (Direction Finder Set), helps detect enemy devices emitting radio signals, including drones, communication equipment, relays, and electronic warfare assets. According to the company, ETER has already seen combat use and contributed to the destruction of a Russian system valued at around $90 million. Falcons positions the device as a compact, GPS-free alternative that is up to 30–50 times cheaper than comparable NATO systems, with operational coverage exceeding 600 km. Falcons’ CEO and co-founder Yehor Dudinov, an active-duty serviceman with experience in strategic planning and product management, said the investment demonstrates the wider potential of technologies developed under fire in Ukraine. The funding will support Falcons in scaling ETER’s production, growing its team of engineers and frontline practitioners, and developing a NATO market-entry strategy. Green Flag Ventures, co-founded by Justin Zeefe and Deborah Fairlamb, invests in dual-use startups with both defense and civilian applications, with a particular focus on Ukraine’s defense technology ecosystem. The investment comes as Western investors show increasing interest in Ukrainian defense startups, many of which have rapidly developed solutions in response to wartime needs. NATO nations have also signaled interest in cost-effective and agile alternatives to traditional, often slower-moving defense procurement.

French deeptech company Cailabs has raised €57 million to accelerate its industrial expansion and global growth. The round of structured financing, led by the European Investment Bank (EIB), combines a €37 million financing from the EIB and a €20 million investment from Definvest and Fonds Innovation Defense (Armed Forces ministry and Bpifrance), NewSpace Capital, the European Innovation Council (EIC) Fund, Starquest Capital, and CAIVE. Cailabs is a deeptech photonics company founded in 2013, operating in France and the United States. Leveraging expertise in photonics and systems engineering, it designs and manufactures laser-light solutions for the space, telecommunications, industrial, and defence markets. Its portfolio includes turnkey optical ground stations that use atmospheric turbulence compensation to enable high-throughput, low-latency links across space and terrestrial networks, with a focus on precise light control to deliver faster, safer, and more reliable performance. Commenting on the strategic importance of Cailabs’ work and the rationale for the investment, Ambroise Fayolle, Vice-President of the European Investment Bank, noted that space technologies are increasingly vital for civilian, security, and defense applications: As the bank of the European Union, the EIB supports Cailabs’ investments in manufacturing capabilities and in research & development of its laser communication technologies. Fayolle added that the project fully aligns with the EIB’s strategic priorities in security and defence, as well as technological innovation, under its TechEU programme. Securing this structured financing signals Cailabs’ growing commercial maturity, supported by a backlog of more than ten optical ground stations already under contract. The funds will accelerate manufacturing scale-up and strengthen the supply chain. A new industrial platform, capable of assembling and validating five stations in parallel, will support the goal of producing up to 50 OGS annually by 2027. The financing will also support international expansion and advance the product portfolio with turnkey 100+ Gbps solutions, transportable optical ground stations, and expanded orbit coverage. This funding round reflects our solid fundamentals and the confidence investors have in our strategic vision. It enables us to scale up industrial capabilities and prepare for the next stage of growth, concluded Jean-Francois Morizur, co-founder and CEO of Cailabs.  

Barcelona-based Altan, a platform that assembles teams of AI agents to autonomously design, build and operate software, has raised $2.5 million in a pre-seed round. The round was co-led by VentureFriends and JME Ventures, joined by 4Founders Ventures and ElevenLabs’ Carles Reina. Angel investors participating in the round include Pau Suris and Pau Sabria (Remotely), Albert Armengol (Doctoralia), David Baratech (Yaba), and Lluis Faus (vLex). Altan is an agent-native platform that reimagines how software is built and run. Founded in Barcelona in 2024, Altan set out to make production-ready software creation accessible to everyone, from individuals to enterprises and agencies. Users describe a product via text or voice, and Altan orchestrates role-based AI squads, full-stack engineers, UX designers, and product managers to design, build, and deploy production-ready applications. Because the software is created to be operated by agents, not just humans, Altan enables autonomous operations after launch, making it possible to stand up entire businesses rapidly and move from idea to revenue in hours. Albert Sagueda, Altan’s CEO and co-founder, emphasised that conventional no- and low-code solutions produce software intended to be run by people. At Altan, we're pioneering a completely new category of software: fully autonomous software designed to operate without human intervention. Our goal is to let you be the “idea” person, and let the agents do everything else. Altan’s agents collaborate to handle the entire software lifecycle (design, build, and deploy), including front- and back-end development, payment integrations, workflow design, and customer-database hosting. The platform can also embed agentic interfaces (voice, text, or video), making projects ready for autonomous operation from day one.

A new report by Antler, published today reveals a new generation of ‘rocketship’ unicorns —  tech companies, like Lovable, Mistral and ElevenLabs, that were founded since 2020 and have already achieved billion-dollar valuations — have disproved the myth that it is impossible to scale tech companies in Europe as fast as the US.   The report, Europe’s Era of Execution, is one of the largest studies of European founders ever conducted. It analyses 3,400 founders of 900 unicorns in Europe and the US, 35 founders of the fastest-growing software companies of all time, 1,200 Antler-backed founders, and 60,000 aspiring entrepreneurs. Europe’s rocketship Unicorns There are 14 rocketships in Europe. On average, they have taken two years to reach a billion-dollar valuation. This is significantly faster than the previous rate of 7.2 years. And they are keeping pace with the US, where the average time to unicorn is now 1.6 years. Contrary to misconceptions that European companies need American capital to scale, two-thirds of the VCs backing European rocketships are from the local ecosystem. Accel is Europe’s most prolific rocketship backer, investing in Lovable, Fuse Energy and Helsing.  Christoph Klink, Partner at Antler, comments:  “We are seeing a wave of European rocketships led by a new generation of technical founders using AI to smash through Europe’s scaling bottleneck.  As a result, Europe is producing unicorns faster than ever before. In fact, two of the top five fastest-growing software companies of all time are now European (Lovable & ElevenLabs)." He contends that while Europe may never match the US dollar-for-dollar in fundraising, “it can compete, and win, through relentless execution." "The Execution Era has begun, and Europe’s founders are redefining what is possible.” Rocketship Fuel - AI and Technical Founders AI is the driving force behind the execution era. In a survey of 1,200 European founders, 93 per cent said that AI has allowed them to execute faster, with half saying AI allows them to move 5x faster than before.  85 per cent of companies have used AI to build their MVPs. And for products in full production, up to 40 per cent of the code is AI-generated, which is 3x higher than 2020.  And Europe’s unicorn founders are more technical than ever before. 90 per cent of the founders who started rocketships since 2022 have technical backgrounds. In fact, Europe is now producing a higher share of technical founders than the US, where 80 per cent of unicorn founders since 2022 are technical. This is the first time that has happened.  Unsurprisingly, technical AI founders are the fastest-growing breed among founders starting businesses today.  Between 2023 and 2025, the number of AI engineers becoming founders in Europe increased by 14x.  And since 2022, the number of founders who previously held AI engineering roles has increased by 4x.  Europe’s challenges: London, diversity and Big Tech Despite this momentum, the report highlights a number of hurdles that Europe’s tech ecosystem still needs to overcome:  AI founder talent is not gender diverse: Europe has only produced one female AI unicorn founder, and none of the AI unicorns in the last five years have female foundersRocketships are leaving London behind: only one rocketship has come out of London, raising questions about the future dominance of the world’s third largest tech ecosystem.  Europe needs big tech engine rooms: 50 per cent of US rocketship founders hail from big tech companies, whilst only 30 per cent of European founders do The Lovable Effect In the study of 1,200 European founders, when asked to name a tech company they admired the most in the world, 40 per cent named Lovable.  80 per cent of founders said they wanted their speed of execution to be faster.  And, for the first time, speed of execution (44 per cent) has overtaken access to funding (40 per cent) as the biggest challenge facing European founders.  Rocketships such as Lovable are driving increased velocity in Europe that is also being seen at the early-stage. Startups founded in the last year in Antler’s European portfolio get to first revenue 3x as fast, and generate up to 10x more revenue in their first year, compared to startups founded three years ago.  Anton Osika, co-founder of Lovable, comments:  “The speed at which AI capabilities have been advancing mean we couldn’t have launched Lovable a couple of years ago. We have focused on building in a capital efficient way that is very common to Europe but doesn’t fit with the traditional US startup playbook.”  Marius Meiners, co-founder of Peec AI, comments:   “In the AI space, the companies that win are the ones that scale the fastest. Now more than ever, most ideas with potentially huge outcomes are fairly obvious.  Working on these ideas where you might face 50 competitors requires more than just the belief that “I can build a big company. You need a deep conviction that you can outperform everyone else, and then the discipline to execute on that belief.”

For many European startups, the US is seen as the ultimate market to scale into. Since we often frame competitiveness in terms of Europe versus the US, I wanted to hear the perspective on the 28th Regime from a founder now operating in the US. Goedele "G" Mangelaars is the founder and CEO of Pink Notebook, a travel venture built on the belief that trip planning shouldn't have to start with fixed dates. Instead, her company helps travellers secure the best offers across destinations, accommodations, activities, and transportation — with greater flexibility and inspiration. Having seen first-hand how the US ecosystem enables innovation, she is a strong advocate for Europe adopting a 28th Regime to create a more unified and competitive environment for founders. I spoke to her to learn more.  Europe has the talent, the US has the infrastructure Originally from the Netherlands and now based in New York, Mangelaars brings extensive international experience in strategy, partnerships, and marketing across the travel and technology sectors.  About 85 to 90 per cent of Mangelaars is spent in the US, where her startup Pink Notebook is headquartered. Her investors are split between the US and Europe — "I have one American investor and two European ones who also invest in US companies", she explained. When it comes to the US vs Europe, Mangelaars' perspective comes as no surprise. She contends that the US is built for startups: "You eat, sleep, breathe entrepreneurship in places like New York or San Francisco. The infrastructure is designed to help companies start and scale. In Europe, the entrepreneurial spirit is definitely there — citizens are highly educated and incredibly entrepreneurial — but the environment is slower, more fragmented, and often bogged down in bureaucracy." "European startups are asked to run a marathon with their shoelaces tied" When it comes to investment, Mangelaars believes that Europe is playing a completely different ballgame to the US: "In Europe, even at pre-seed, investors often want detailed user data — attrition rates, user metrics—before they'll even consider investing.  In the US, it's more of a people play. If you can sit across from an investor and convince them you'll 10x their fund, they'll back you." Mangelaars contends that on the founder side,  "European startups are often asked to run a marathon with their shoelaces tied." "They get smaller rounds, which makes it harder to take risks, test theses, and experiment.  Bigger rounds in the US give founders more room to try things out." From hours to weeks: the startup incorporation lottery across Europe Starting a company in Europe can mean anything from a few hours online in Estonia to several weeks of notary visits in Germany — while in the US, you can set up a Delaware C-Corp in 1–5 days. Some European countries do it well — in Estonia, through its e-Residency program, you can incorporate a company online in as little as a few hours to a day. In the UK, forming a private limited company can be done online in 24 hours. In Ukraine, startup formation can be done entirely online in minutes using the Dia platform, even during wartime.  But in Spain and Italy, it can take a couple of weeks. And in places like Germany, incorporation requires a notary – this is also the case in the Netherlands —, bank account setup, and registration with the commercial register and can take several weeks. Even logistics like opening a startup bank account can be a daunting task in Europe. According to Mangelaars, opening a corporate bank account in the Netherlands took two weeks.  "In the US, it took two hours at Chase—even without a Social Security number, just with a visa and a passport. Those little differences add up, they take founders away from critical work, and they make Europe less competitive." Europe is "committeed to death" Mangelaars and I share the opinion that Europe is obsessed with meetings and committees. She contends that while Europe's strength is its consultative approach — "every voice is heard, legislation is carefully crafted, and that creates stability. " But it also means things move very slowly. "Startups don't have the luxury of waiting years for decisions. At some point, the EU has to take a risk. Even if the 28th Regime isn't exactly ironed out on all counts, being 80 per cent right and moving quickly is better than standing still." Although many Europeans still view the US as the ultimate destination—"the ecosystem, the infrastructure, and the opportunities are stronger there, so many still want to spend a few years in the States before coming back," says Mangelaars — she notes a growing trend in startup circles of Americans heading the other way, often joining scale-ups rather than founding their own companies:  "Portugal has been popular because of its visas. I've also seen more people interested in the UK post-Brexit." "'Just try it'" Mangelaars has advice for anyone in Europe looking to form a startup: "Just try it. Start small. Test your idea in the scrappiest, cheapest way possible.  The best advice I ever got — from an Italian founder — was to find the simplest way to get user feedback. For us, it was to build an email list, ask people about their next dream trip, and then handcraft an itinerary.  It doesn't have to be perfect. Ship something, learn from it, and keep going." Europe's hubs will survive, but without the 28th Regime, scaling will suffer. Mangelaars urges Europeans pushing for the 28th Regime to keep going. "I believe deeply in rewriting the rules for startups in Europe. If legislation takes years, then founders themselves need to build networks—mentor, share contacts, make introductions." She also contends that European founders who've scaled to the US should give back: "Mentor others, share investor contacts, review MVPs. If we can't move legislation, the best thing we can give is our time. Saying "I believe in European startups" isn't enough if you're not actually helping." Ultimately, Mangelaars believes that if the 28th Regime doesn't succeed, Europe will still have strong hubs — London, Amsterdam, Berlin, Paris, Lisbon, Barcelona.  "We want Europe to thrive, we can't just wait for Brussels. We need to make it happen ourselves. But the landscape will remain fractured. Startups won't be able to scale across borders easily, and investors will continue to face obstacles in cross-border deals.  That's the real loss—not the hubs themselves, but the ability to grow and invest seamlessly across Europe."

Vibe coding is a relatively new term people are using to describe building software through natural language prompts instead of traditional programming. The term first entered commercial consciousness in a X post by OpenAI co-founder Andrej Karpathy in early 2025, marking a shift in how people interact with code and software creation. Instead of writing lines of code, you type what you want an app or feature to do in plain English (or another language), and an AI system generates the code or even the full application for you. It's often seen as the next evolution of low-code/no-code platforms, powered by AI. It promises to democratise software creation, allowing anyone to build products, reduce costs and time, as AI handles repetitive coding, and shift competition from pure technical ability to product quality and user experience. However, it also presents challenges such as technical debt, enterprise readiness, and the risk of a market flooded with replicable tech without commercial traction. Thomas Cuvelier is a partner at early-stage VC RTP Global and was an early angel investor in the red-hot coding startup Lovable, which in July 2025 raised $200 million in a Series A round, reaching a valuation of approximately $1.8 billion just eight months after founding.  I spoke to Cuvelier to learn more.  Where are we in the hype cycle for vibe coding? According to Cuvelier, we're still early.  "This isn't hype based on nothing — it's hype based on revenue. Companies are scaling quickly, going from one to 10, one to 20. The growth is real, so I don't think we're at the peak yet." According to Cuvelier, most vibe coding users are non-technical people: "We see a lot of school kids creating simple apps and products with zero technical knowledge." The second group consists of technical or semi-technical users who utilise it to speed up coding. They might still go into the code to make adjustments for more complex applications, but the repetitive work is abstracted away. While Cuvelier predicts that most markets will be big, his interest lies in giving "superpowers" to the 99 per cent.  "These tools let anyone become a developer. No one should have that moment of thinking, 'I have a great idea, but I need to find a developer and I don't know how.' That's a huge problem to solve." However, AI code tools can’t escape technical debt or the need for review I wondered about the problem of vibe coding generating technical debt, in the context of the hidden "cost" of quick coding decisions that trade long-term stability for short-term speed. "That's the biggest issue with vibe coding today," shared Cuvelier.  "These products are great for simple apps, but enterprise use is another matter. They can create a significant amount of technical debt, and the code still requires review. Tools like GitHub Copilot have been generating code for years, but you still need to review it. That won't go away anytime soon. Right now, the apps aren't entirely enterprise-ready. This will get fixed in time, but today it's a limitation." What about explainability?  Coding is also about communicating and reasoning through ideas—pair programming, design processes, and peer reviews. Does a vibe coding approach change that? "You'll always need an audit trail," contends Cuvelier.  "These tools will increasingly include features showing how something was built — like an ingredient list on food packaging. Transparency will remain essential, even as more gets automated." Vibe coding to fundamentally change how entrepreneurs work While Cuvelier contends that technical skills are indeed necessary for startups, he argued that vibe coding democratises entrepreneurship.    "Anyone — a business leader, a biochemist — can now get started.  Over time, people won't compete on who has the best technical team, but on who builds the best product. User experience will be the differentiator, and the winners will ultimately be the users." Cuvelier contends that the core concepts will remain, such as building products and adding features, but developers will spend less time on repetitive tasks and more time on design, user experience, and creativity.  He suggests that education must change, too. "If you're learning to code today, you should also learn how to use vibe coding tools alongside traditional coding." Looking forward, Cuvelier predicts that as coding becomes accessible to everyone, the cost of building software will fall close to zero, like the cost of storing data "We'll see more apps, more products, and much better quality overall, because competition will push companies to focus on user experience. Incumbents with average, clunky software will be disrupted. This shift will be visible within the next 12 to 24 months." Cuvelier: In 24 months, software costs could fall to zero — and incumbents should worry However, more access to product-building tech means more products and even with easy tools, teams still need to focus on building something users actually want. Cuvelier admits, "That's always the hardest part. It will come down to empathy — understanding how consumers think and giving them a great experience. You won't be able to get away with forcing users to adapt to bad software or locking them in." It's somewhat reminiscent of how "plug-and-play" and no-code transformed industries like IoT. Suddenly, traditional companies could implement digital tools in-house, without huge deployments. AI is finally making that possible.   However, Cuvelier cautions that incumbents should be worried: "If you're a large company with mediocre software, and you've survived by locking in customers, you're in trouble." Cuvelier sees consumer applications as particularly ripe for disruption, but also enterprise tools like CRM, accounting, and productivity software — "basically anything you use every day that you don't like." "These tools will be disrupted quickly. Some areas, though, are more protected, like apps with strong network effects.  For example, it's going to be hard to build something better than WhatsApp because all your contacts are already there." Retention is the ultimate metric As an investor, Cuvelier looks for startups with retention. "Do users stick with your platform? That's the key metric," he shared.  While a few dominant players are already emerging with strong communities, and they're hard to catch up with, there's still room for niche players—startups that specialise in verticals or unique use cases.  "If you can build community and keep users engaged, that's a good sign." Ultimately, Cuvelier contends that Europe's strength lies in its talent.  "We have deep pools in AI and machine learning. The startup ecosystem is improving, with more funding available, and companies like Lovable show that European startups can attract strong backers.  But Europe still lacks the large-scale funding rounds —€10, 20, 50 million — that Silicon Valley can provide.  That needs to change.  At the same time, the US is a huge part of the market, so European companies must think globally from day one."