Last week, we tracked more than 50 tech funding deals worth over €1 billion and over 10 exits, M&A transactions, rumours, and related news stories across Europe. ? The top three industries that raised the most were cleantech (€431.7 million), fintech (€158 million), and robotics (€138.5 million). At the country level, ?? the UK took first place (€629.5 million), followed by ?? Germany (€295.9 million) and ?? Italy (€34 million). ❗ Be sure to check out the Tech.eu Funding Explorer, free and open to everyone, for deeper insights into funding data, investor activity, company profiles, and market trends. Now, let's get you up to speed on everything that happened last week. Have a great week! Funding deals by amount UK: Jeff Bezos and Sovereign AI back CuspAI in $450M raise GERMANY: Augustus secures $180M Series B UK: Robotics startup Humanoid hits $1.35B valuation with $152M Series A GERMANY: Voodin Blade Technology secures €48.18M EU Grant for Spain's first automated wooden turbine blade factory UK: Arrakis has emerged from stealth, raising $38M in over three months UK: Agricultural biotech firm Moa Technology raises £22.2M FINLAND: AI infrastructure company Verda secures €22M NIB loan NETHERLANDS: Tempress receives $20M investment from Jolt Capital SWITZERLAND: Hilo raises $19M Series B extension for Fitbit-style blood pressure health system UK: Modo Energy secures €14.9M to scale its AI-powered energy benchmarking and valuation platform GERMANY: telli secures $15M seed to automate customer-facing operations GERMANY: Passionfroot raises $15M to expand its B2B creator marketplace to the US GERMANY: kausable raises €12M to rethink how AI learns ITALY: Circular Materials secures €11.8M to scale critical raw material recovery technology UKRAINE: Yope raises $12.3M in pre Series A funding GERMANY: deltaVision raises €10.2M to accelerate orbital refuelling technology GERMANY: Deutsche Sanierungsberatung raises over €10M to accelerate climate-neutral home renovations ITALY: AI startup Datapizza secures €10M Series A to expand enterprise offerings GERMANY: Omio raises €8.7M strategic investment for Asian expansion UK: Healthtech challenger using AI to cut lung disease test time, TidalSense, clinches $19M UK: Mach42 raises £7M in pre-Series A funding GERMANY: BeatSquares closes a $2M seed funding round GERMANY: Zalando joins Sereact's $116M Series B to accelerate AI-powered warehouse automation ITALY: ORiS raises €5M to build laser-powered energy infrastructure for space GERMANY: Aampere raises €4.2M in its second round in 9 months GERMANY: Prodlane snaps €4M to build an AI assistant for technical teams SWEDEN: imagi raises $4.5M to help teach students how to vibe code UK: Cybersecurity provider Xentra secures £2.7M ITALY: HRtech startup Talentware secures €3.3M seed round led by CDP Venture Capital UK: AI engineering project predictor startup Cascade has raised a $3.5M seed round from a16z accelerator ITALY: Agrifoodtech startup Vinhood secures €3M Series A round led by Linfa SWEDEN: Y Combinator startup Scape emerges from stealth with $3.2M to rethink email SWITZERLAND: ImmitraBio secures €2.6M in pre-seed funding UK: Ossprey secures $2.65M to stop software supply chain attacks UK: Ponda raises £1.8M to develop textiles from regenerative fibres SPAIN: CoCircular closes a €1.9M funding round to accelerate its expansion and prepares its entry into the industrial and textile sectors IRELAND: Nernst Electric raises €1.7M to scale on-site oxygen generation technology for aquaculture and heavy industry SPAIN: PageMind raises €1.2M to scale AI for e-commerce product discovery ITALY: Ulisses closes €1.09M seed funding UK: PolyBox reveals £700,000 funding boost GERMANY: The Fundernation community is investing around €780,000 in hydrop systems SPAIN: Mentelem closes a €600,000 investment round TÜRKİYE: RABAM received a $500,000 investment at a valuation of $10M SPAIN: ART Technologies closes a €200,000 funding round with REDIT Ventures to accelerate its industrial scaling SWITZERLAND: goNEON Agentic Systems secures €160,000 to accelerate AI-powered infrastructure planning SWITZERLAND: SeaSON Energy receives millions in funding for seasonal energy storage FRANCE: Pelico receives strategic investment from AE Ventures UK: Novum Studio closes new funding LUXEMBOURG: ATOZ Services receives investment from Bregal Sagemount GERMANY: Lockheed Martin Ventures is investing an undisclosed sum in Spread as part of a Series B funding round ICELAND: Sowilo raises pre-seed to expand AI-powered fashion product intelligence platform SWITZERLAND: Maus Robotics has obtained €161,000 from Venture Kick Exits and M&A activity SWEDEN: Einride acquires electric vehicle charging startup Flipturn for $38 million NETHERLANDS: Havas acquires Dutch sport-marketing agency SportVibes to strengthen Benelux presence UK: $87M deal enables global swoop for UK's Secaro GERMANY: Cologne-based InsurTech Genki is acquiring Wave Claims ROMANIA: Baltic ticketing group PLG acquires Romanian platform iaBilet in rapid growth play GERMANY: The Cologne-based e-mobility company chargecloud is acquiring assets from the insolvent charging station startup elvah FRANCE: Vienna outdoor platform checkyeti acquires France's Manawa UK: Lightning Reach acquired by ETG as mission-driven govtech group expands portfolio SPAIN: Milan-based Contents acquires Spanish financial wellbeing platform Balio in sixth buy-and-build deal AUSTRIA: Swedish racket-sports platform Matchi merges with Austrian competitor Eversports FINLAND: Finnish Aiven acquires Flow AI to expand production AI infrastructure capabilities POLAND: SINGU expands industrial maintenance capabilities through QRmaint acquisition FINLAND: Monterro acquires Finnish fintech MORS Software to bolster banking compliance solutions GERMANY: The US life sciences company Bruker is acquiring the insolvent Duisburg-based medtech company Noscendo

A BAE Systems spinout whose tech could help generate electricity at one-fifth of the cost of today’s nuclear power plants has come out of stealth, securing a £15m funding round led by IQ Capital. Manchester-based Nuclear Turbines is an energy startup developing compact modular nuclear systems to help make clean nuclear power cheaper than fossil fuels. It is looking to reduce the high cost of generating nuclear power by replacing expensive steam turbine systems with “highly efficient” high-temperature turbine technology normally found in jet engines and gas-fired power plants, combined with a novel nuclear reactor design. It says its tech is so compact that it can be deployed “behind the meter” on industrial sites, powering infrastructure such as industrial facilities and data centres and manufacturing facilities. It says its tech is building on advancements by small modular reactors by solving cost and scale challenges. Other participants in the £15m funding rounds were Rhapsody Venture Partners, Zero Carbon Capital and Empirical Ventures. The startup, founded in 2025, says it will use the funding for design purposes, build large-scale test rigs and expand the team. The startup was founded by former BAE Systems principal engineer Jeremy Owston and internationally renowned nuclear engineer professor Tim Abram, in partnership with Empirical Ventures' venture studio and spun out of BAE Systems, the defence giant. It emerges out of stealth as the UK government looks to build a new generation of nuclear plants to meet the future energy needs of a country- where electricity prices are amongst the highest in Europe- and meet net zero targets. It also says its vision aligns with the 2025 government-commissioned Nuclear Regulatory Review, which called for a “radical reset” for UK nuclear regulation. Owston said: "The nuclear industry has always designed reactors first, then figured out what to do with the heat. We flipped this script: we started with the cheapest way to generate power and designed a reactor to fit. If we're serious about reindustrialising while meeting climate goals, we need energy that's clean and cheap. We’ve created the only tech that solves both, from the UK."

An AI unit has been set up at the centre of the UK government to drive overall AI strategy, following a major AI shakeup inside the government this week. The unit, called the Prime Minister's AI Taskforce, will be led by new AI minister Kanishka Narayan and report to Downing Street. It aims to transform public services with AI and help drive growth and AI adoption across the country. The government claims it is the first time AI will be positioned at the centre of government. The setting up of the unit, which will be chaired by Lord Vallance, follows a major AI shakeup inside the government, under new Prime Minister Andy Burnham. The changes saw Narayan appointed AI minister, who will attend cabinet meetings, and the axing of department of science, innovation and technology (DSIT) as a standalone entity. The government gave few details about the unit’s remit but said the unit would learn lessons from the Vaccines Taskforce, which, it said, showed it can “drive extraordinary outcomes and deliver real benefits for people across the country”. The unit will report to cabinet secretary Antonia Romeo, the head of the civil service and Narayan and will be based with first secretary of state Louise Haigh in the new office for the prime minister and the cabinet (OPMC). Responsibility for the existing AI Security Institute will move to the OPMC, the government said. Burnham said: "AI is rapidly changing our world and we need to make sure it works for everyone. The opportunities are huge if we get it right and I want AI to power a new industrial revolution that drives good growth in every postcode. Lord Vallance is a true public servant with decades of experience, expertise and a track record of delivery. I’m delighted he’ll be chairing the AI Taskforce, putting AI at the centre of all our work to change people’s lives for the better."

This week, we tracked more than 50 tech funding deals worth over €1 billion and over 10 exits, M&A transactions, rumours, and related news stories across Europe. Alongside the week’s top funding rounds, we’ve highlighted key industry developments, as well as notable trends in European venture activity, investor moves and emerging sectors shaping the current funding landscape. 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. ❗ Want to explore the data in more detail? The free, open-access Tech.eu Funding Explorer offers deeper insights into funding rounds, investor activity, company profiles and market trends. Either way, let's get you up to speed. ? Notable and big funding rounds ?? Jeff Bezos and Sovereign AI back CuspAI in $450M raise ?? Augustus secures $180M Series B ?? Robotics startup Humanoid hits $1.35B valuation with $152M Series A ??‍?? Noteworthy acquisitions and mergers ?? Einride acquires electric vehicle charging startup Flipturn for $38 million ?? Lightning Reach acquired by ETG as mission-driven govtech group expands portfolio ?? SINGU expands industrial maintenance capabilities through QRmaint acquisition ?? $87M deal enables global swoop for UK's Secaro ? Interesting moves from investors ? Airbus anchors €500M European defence tech fund as E2D makes first investment in Alta Ares ?  Resist.UA launches €50M European fund to scale Ukraine's battlefield-proven defencetech ? EHE Ventures opens second cohort for £15m fund backing AI-native firms ?️ In other (important) news ? AI minister to attend cabinet, as DSIT axed ? Revolut confirms fresh secondary share sale, at reported $115BN valuation ?️ Voodin consortium secures €48M EU grant to build Spain’s first automated wooden blade factory ? Recommended reads and listens When Hollywood feared AI, Filmustage bet on pre-production instead ? Google Cloud and NVIDIA power microagi's embodied AI ambitions ?  kausable raises €12M to rethink how AI learns ? European tech startups to watch  ?? Y Combinator startup Scape emerges from stealth with $3.2M to rethink email ?? Ossprey secures $2.65M to stop software supply chain attacks ?? PageMind raises €1.2M to scale AI for e-commerce product discovery ?? goNEON Agentic Systems secures €160,000 to accelerate AI-powered infrastructure planning ?? Sowilo raises pre-seed to expand AI-powered fashion product intelligence platform

Startup founder Egor Dubrovsky told me that he won't trim his beard until Filmustage's monthly recurring revenue triples. Today it's more than 15 centimetres long. Ironically, beards have also become a useful way of explaining what his company actually does. During development, Filmustage analysed a screenplay and flagged a character's beard as an important production element. Someone questioned why facial hair mattered. For Dubrovsky, the answer captured the difference between generative AI and production AI: if an actor shaves between shooting days, makeup, continuity and scheduling all need to know. A simple beard can be critical to getting a film made. When AI became Hollywood's biggest controversy From May to September 2023, the Writers Guild of America (WGA), representing 11,500 screenwriters, held a 148-day strike against the Alliance of Motion Picture and Television Producers. One of the key issues was the use of AI in scriptwriting and rewrites. The resulting agreement introduced landmark protections. AI cannot receive writing credit, and AI-generated material cannot be treated as source material in ways that diminish a writer's authorship, credit or compensation. Writers may use AI tools voluntarily, but studios cannot require them to do so. They must disclose when material provided to writers has been generated or incorporates AI-generated content. The agreement also preserves the WGA's right to challenge the use of writers' work to train AI models under existing contracts or copyright law. As Hollywood debated where AI belonged in the creative process, another group of startups was taking a different approach. Rather than trying to replace writers, Belarusian-founded Filmustage applies AI to one of filmmaking's least glamorous tasks: pre-production. Its origins, however, were anything but planned. A stolen passport sparked a startup Filmustage was co-founded by Egor Dubrovsky, Ruslan Khamidullin, and Andrei Karalkou, who are originally from Belarus. Dubrovsky’s background combines both the film and tech industries. Before Filmustage, he built websites, online shops and other digital products, while also working in film production for companies including Uber, the United Nations and TikTok.  The idea for Filmustage came after he visited Los Angeles several years ago to help a friend on a film production. During this time, the worst happened — someone stole his backpack containing his passport and documents. “I ended up staying in the US for about six months while I waited for replacement documents and worked on productions for companies including Netflix and Amazon,” he explained. That experience exposed him to a major problem across the industry. At the time, people in film production relied on spreadsheets, paper, pens and manual processes for almost everything. He realised this was a problem worth solving. ​ Taking the pain out of pre-production Filmustage is intentionally focused on pre-production, where filmmakers spend an enormous amount of time on repetitive manual work. “They have separate spreadsheets for budgeting, scheduling and script analysis, and then another spreadsheet that combines all of those together,” shared Dubrovsky. He often compares it to building a house. “Before you build anything, you have to create the plans, hire the team, organise the equipment and prepare everything. Film production works the same way.” Before filming begins, production teams have to coordinate actors' schedules, locations, props, permits and hundreds of other details. They also need to identify potential risks. For example, a scene may require animals, children or special safety conditions. All of this traditionally takes weeks. “This is exactly the kind of work where AI is most valuable because it's about analysing information rather than replacing creativity,” contends Dubrovsky. Reimagining film pre-production Filmustage automates many of the time-consuming tasks involved in taking a screenplay from script to shoot. After a script is uploaded, Filmustage automatically generates a detailed script breakdown, identifying characters, locations, props, costumes, vehicles, VFX requirements and other production elements. It then creates shooting schedules with stripboards, Day Out of Days (DOOD) reports and conflict detection, while AI-assisted budgeting tools generate draft production budgets with cost estimates. Additional features include call sheet generation, storyboard creation, VFX breakdowns, project collaboration and exports to industry-standard software including Final Draft, Movie Magic Scheduling and Movie Magic Budgeting. It also creates optimised shooting schedules with stripboards, Day Out of Days (DOOD) reports and conflict detection, while AI-assisted budgeting tools generate draft production budgets with cost estimates. Helping crews, not replacing them ​ Given Hollywood's concerns over AI replacing creative workers, I asked whether Filmustage had eliminated pre-production jobs. ​ Dubrovsky asserts that this has not been the case: “Every technological advance has changed how people work rather than removing the need for skilled professionals. Editing software didn't replace film editors. Digital cameras didn't replace cinematographers. CGI didn't eliminate visual effects artists. Our platform helps people complete repetitive work much faster, but humans still make the final decisions. AI supports professionals—it doesn't replace them.” Protecting scripts in the AI era Intellectual property is a major concern in film production. To protect customers' scripts and other sensitive material, Filmustage does not use customer scripts to train its AI models. It also has agreements with AI providers including OpenAI and Google that prevent customer data from being used for model training. Dubrovsky explained: “We understand how sensitive scripts are. If a script leaks before release, it can jeopardise an entire production. Some television series even produce multiple fake versions of scripts so that only the real version is revealed on set. Security is therefore a major priority for us. We comply with industry security standards, including the Entertainment Partners Network requirements and SOC 2 certification. Our infrastructure is protected at both the cloud and device level, allowing us to meet the security requirements of major studios.” From Star Wars to AI-powered pre-production Filmustage’s tools are already used by over 34,000 students and independent filmmakers, as well as established producers like Steve Clark-Hall and Roger Christian, on titles including Masters of the Air and The Gentlemen. ​ Roger Christian, the Academy Award-winning set decorator behind the original Star Wars films, is one of Filmustage's users. Best known for creating many of the franchise's most iconic props, including the lightsabers and droids, he is now using the platform to help prepare his documentary about Star Wars. He uses generative AI to visualise ideas, create pitch decks and develop concepts that would otherwise take much longer to communicate. French cinematographer and director Franck Onouviet, who works across fiction, documentary and television productions in Gabon and France, uses the platform to automatically break down scripts before reviewing them manually, calling it a "second brain" that helps identify production elements he might otherwise overlook. According to Onouviet, script breakdown and production planning account for more than 80 per cent of his use of the platform, enabling him to prepare shoots with a small crew, generate schedules and call sheets more efficiently, and hire additional team members only when needed. ​ Giving smaller productions studio-grade tools ​ Filmustage is also designed to make professional pre-production tools accessible to smaller teams. ​ According to Dubrovsky, “pre-production can account for around 20 per cent of a film's overall budget. Smaller productions often don't have the resources to hire large production teams or experienced specialists." AI helps level the playing field. Smaller teams can generate professional production documents, follow industry-standard workflows and learn best practices without needing large budgets. Filmustage also works with film schools across the US, offering educational discounts for students and free access for professors. Independent filmmakers receive free collaboration tools, reflecting the company's goal of making professional production workflows more widely accessible. Dubrovsky predicts that the film industry will change significantly in the next few years as AI lowers the barriers to filmmaking, allowing more creators to bring their ideas to life. “Many talented filmmakers have great stories but lack the resources to develop them. Generative AI can help them visualise projects before production begins. It can create concept art, characters, environments and presentation materials that make it much easier to pitch films to investors or studios. Personally, I don't believe generative AI replaces filmmaking itself," he said. "I believe it helps filmmakers communicate their vision much more effectively." Investors appear to share that view. Filmustage closed its seed round in 2023 at the height of the WGA strike and went on to raise a total of $2.5 million over the following year. From pre-production to product placement Filmustage has also expanded beyond production software with the launch of Filmustage Placement, an AI-powered marketplace that connects brands with film and television productions during the script stage, before creative decisions are locked in. Filmmakers can upload their screenplays for AI analysis, which identifies potential product placement opportunities while generating audience insights and scene-level brand safety scores. The platform then matches productions with brands based on audience demographics, budgets and campaign goals, allowing advertisers to integrate products organically into a story rather than retrofitting placements during post-production. By replacing the traditional agency-led model with an AI-driven marketplace, Filmustage aims to make product placement faster, more transparent and more accessible for both filmmakers seeking financing and brands looking for authentic on-screen exposure.

For a decade, virtual try-on technology has been the industry's perennial "almost." The idea—letting shoppers see how a jacket or a shade of lipstick would actually look on them—was always compelling. The execution was not. Brands had to feed in expensive 3D product data, tools choked on badly lit selfies, and the results looked more uncanny than useful. That changed fast. Generative AI can now turn a standard product photo into a 3D model that simulates cut, drape and fabric in real time, without the manual 3D pipeline that made earlier versions unworkable. ASOS now lets shoppers upload a photo or build a digital twin from their proportions and preferences. Breuninger became the first German fashion retailer to integrate Google's virtual try-on technology into its app. Maybelline lets users try shades via upload, digital model, or live camera. None of this is a lab demo. It is live, in production, driving measurable results. That distinction—between AI as a pilot and AI as infrastructure—is exactly why virtual try-on has become a reference case for an entire industry. Fashion e-commerce has quietly carried two expensive, unsolved problems for years: purchase hesitation from not knowing how a product will look, and return rates driven by size uncertainty. In the US, the National Retail Federation estimated that 19.3% of online fashion purchases were returned in 2025, with Gen Z shoppers returning close to eight garments on average. Arnold Pötsch, lead author of the BVDW working group paper on 3D in e-commerce, put it plainly: advances in computer vision, AI and real-time rendering have turned virtual try-on into "a clear competitive advantage for forward-looking retailers," blurring the line between physical product and digital twin, and giving retail the key to a personalized shopping experience, fewer returns, and greater sustainability. The reason this matters beyond fashion is the pattern underneath it: AI that finally scales past the demo stage, tied directly to a P&L. That pattern is showing up across every vertical Tech.eu covers. In fintech, AI-driven underwriting and fraud detection are moving from add-on features to default infrastructure. In healthtech, diagnostic and triage models are clearing the trust threshold that kept them in pilot purgatory for years. Deeptech ventures are proving that foundational research—in robotics, materials, or computer vision—can be productized on realistic timelines. SaaS vendors are being judged less on their AI features list and more on measurable retention and margin. And sustainability has stopped being a compliance checkbox, becoming a genuine efficiency lever as AI helps reduce waste, from fewer fashion returns to leaner data center loads. This is precisely the shift DMEXCO has chosen as its 2026 theme: "Scaling Intelligence"—the pivot from AI experimentation to real value creation. It's a fitting frame for where the market actually is. The easy wins from bolting a chatbot onto an existing product are gone. The harder, more interesting work now is building AI that holds up at scale, earns trust from real users, and shows up in the numbers investors and operators actually track. DMEXCO 2026 takes place September 23–24 in Cologne, and brings together decision-makers across agencies, commerce, tech and media to work through exactly these questions. For founders, operators, and investors tracking where AI is actually converting into revenue and retention rather than headlines, the agenda spans World of Commerce, World of Tech, and dedicated summits addressing the same scaling challenge across sectors—from fintech and healthtech to deeptech and sustainable innovation. It's a chance to see, case by case, which parts of the AI hype cycle have turned into working infrastructure, and which are still stuck in pilot mode. That mix of formats is deliberate. The Expo floor puts scaled products from established players next to early-stage tech in the Start-up Area, so visitors can compare a live enterprise deployment against the pitch that might become one in eighteen months. The Conference stages pair that with the strategic view: operators explaining what actually broke when they moved a model from pilot to production, and where the ROI showed up first. For a European tech audience in particular, that combination matters. Much of the AI scaling conversation is still dominated by US platforms and Chinese manufacturing; DMEXCO's floor and agenda are unusually dense with European builders—in fintech, healthtech, deeptech and SaaS—solving the same problem under different regulatory and capital constraints. Virtual try-on took ten years to go from novelty to necessity. The vertical-specific AI applications now underway in fintech, healthtech, deeptech, and SaaS are unlikely to take that long—but they will face the same test: does it work at scale, for real users, with numbers that hold up. That is the conversation DMEXCO 2026 is built around.

A UK healthtech startup which has built AI-powered tech that it says reduces the test time for a lung disease that impacts nearly two million people in the UK from an hour to under five minutes has raised $19m in a funding round. Called TidalSense, the startup is looking to transform respiratory diagnosis, starting with COPD (chronic obstructive pulmonary disease). COPD is a chronic lung disease affecting nearly two million people in the UK. The disease, which causes breathing difficulties, is the UK's third biggest cause of death, killing around 30,000 people a year and costing the NHS £1.9 billion annually. The funding round in the startup includes investment from new investor Cross-Border Impact Ventures, the Canadian healthtech impact fund, and returning investors BGF, Airstream Capital and Foresight Group. In total, TidalSense, founded in 2013, has raised $40m, including $11m of grant funding. It says it will use the funding to speed up the rollout of the test across the NHS, where it launched last year, and across Europe, as well as look to enter the US market. The test, called N-Tidal Diagnose, requires patients to breathe normally into a handheld device for 75 seconds, capturing a CO₂ waveform — a capnogram — of the kind traditionally used in critical care, which a set of AI models then analyses to detect COPD.  TidalSense says its AI models have been trained on more than 2.5m patient breaths. The Cambridge-based startup says any healthcare professional can be trained to use the device in 10 minutes, with no specialist qualifications required. Tests, it says, can be carried out on average in under five minutes. It claims that by using its device, clinicians can see four to six patients an hour, compared to roughly one an hour with traditional spirometry, the most common breathing test. The startup is led by doctor Ameera Patel, CEO, whose own struggles and long wait to obtain an asthma diagnosis drove her to build the tech. Patel, CEO of TidalSense, said: "We're still diagnosing in the 21st century with a test invented in the 1800s, and one that needs specialist equipment and training most of the world doesn't have access to. Lower-income and minority communities pay the price for that first. That's the gap we want to close at TidalSense, and the NHS is the first place we're doing it.” IMAGE: Pixabay

More than one billion professionals spend most of their workday in email: an interface that hasn't changed in 25 years. Scape, founded by two 23-year-old Swedes, today emerges from stealth and launches an intelligent email inbox.  Scape has raised $3.2 million from Y Combinator, General Catalyst, and FundersClub.  Angel investors include:  Max Junestrand (co-founder of Legora),   Sebastian Knutsson (co-founder of King),  Jacob Wallenberg jr. (Ramp and EQT),  Sophia Bendz (previously CMO, Spotify),  and operators from OpenAI, Google, Meta and Ramp.  Using Gmail can make email feel more like work about work, than actual work. Simply answering an email from a client can mean reading through old threads to find context, checking meeting notes for what was agreed, filling out attached forms in a separate tool, uploading them, writing the email and sending it, and then watching for their reply among all other ongoing threads. Deciding how to respond is only a fraction of that time.  With Scape, this can all be done in a single click.  Scape was founded by Melvin Hagberg while participating in Y Combinator's summer batch in 2024 as a 21-year-old solo founder. While the company originally started as a customer support tool for email, Melvin pivoted it into Scape after realising the email support tool he had built could help solve his own frustration with email. Elis Hodzic, 23, joined as a co-founder in 2025 after originally backing the company as an investor.  On the surface, the product looks familiar to a traditional email inbox, but is designed to prepare work proactively.  When opening a thread, Scape has already drafted responses that are ready to review and send. The drafts can even include attachments that Scape has created or edited.  It can do so because it learns continuously from the entire email inbox and meetings via its built-in, local meeting notetaker. At the core of Scape is the inbox view, which surfaces only the emails that require attention. It’s organised around custom labels such as Customers and Hiring, to enable prioritisation accordingly. Lower-priority emails like notifications and newsletters are hidden by default. “Our bet is simple: email is where most professionals get their work done. They don’t need another chatbot or Gmail plugin; they need an interface purpose-built for work that happens in email,” said Melvin Hagberg. “Our mission is to enable these professionals to do more impactful work, and to make email fun and fast to use.”  Early investor Gustaf Alströmer, General Partner at Y Combinator, said: “It’s painfully obvious that AI will transform email. While I’ve seen hundreds of startups try to innovate in the space over the years, I’ve seen nothing like the team behind Scape. Once people start using the product, they just don't go back to Gmail.”  Today, the team is five people based in Stockholm. Next, the company is planning to grow the team with additional roles across engineering and product.  Scape is now available for early access at scape.app. 

Spanish AI startup PageMind has raised €1.2 million in funding to accelerate the development of its e-commerce optimisation platform, expand its team and support international growth, with the United States identified as its primary target market. The round was led by 4Founders Capital, with participation from David Martín, CEO of Tradeinn, and Javier Pérez-Tenessa, co-founder of 4Founders Capital and eDreams. Founded by Jaume Portell, PageMind develops an AI platform that helps e-commerce businesses optimise product content to improve how products are discovered, understood and recommended across digital channels and AI-powered search engines. The platform analyses consumer behaviour and search intent to generate product descriptions, buying guides, comparison pages and FAQs, while deploying conversational AI assistants and optimising product visibility for AI search platforms. The company is addressing changes in online product discovery as consumers increasingly rely on AI systems such as ChatGPT, Gemini and Perplexity to research and compare products. As AI-generated search becomes more widely adopted, retailers face growing pressure to ensure product information is structured and optimised for AI-driven recommendations and search results. PageMind's platform also provides analytics on product content and sales performance, enabling businesses to identify the factors influencing product discovery and conversion across digital channels. Traffic no longer depends exclusively on traditional search engines or performance marketing campaigns, but increasingly on AI systems that interpret, recommend and synthesise information from multiple sources. PageMind was created to help e-commerce businesses adapt to this new paradigm and turn it into a competitive advantage, said Jaume Portell, founder and CEO of PageMind. The funding will support further platform development, team expansion and the company's international expansion as it scales its AI-powered product discovery technology.

AI systems need constant, costly retraining. European AI startup kausable raises €12 million in a seed funding round to solve this problem by developing reasoning-first frontier AI that adapts efficiently to changing context without further retraining. The European frontier lab kausable has ties to Heidelberg University and Black Forest Labs (BFL), one of Germany’s most prominent AI companies. The round is led by the German and Belgian investors UVC Partners and Entourage, with follow-on from the German investors HTGF and Mätch VC. kausable is also backed by various private angel investors from the AI industry and academia working at Black Forest Labs, OpenAI, Google DeepMind, Noxtua, and the European Laboratory for Learning and Intelligent Systems (ELLIS), including: Robin Rombach & An­dre­as Blatt­mann (Co-Founder, BFL), Sandro Gia­nel­la (International Strategy & Operations, OpenAI), Dorothy Chou (Strategic Advisor, DeepMind), Dr Michael Bolle (Ex-Board Member, Robert Bosch), Dr An­dre­as Nau­erz (CPO IONOS), Dr Jens Buchner (Lead, Neura Robotics), Jo­han­na Claus­sen & Cor­ne­li­us Claus­sen & Dr Marco Möller (Co-Founder Pionix), Prof Dr Mat­thi­as Bethge (Uni Tübingen, Co-Founder ELLIS), Prof Dr. Marco Aiello (Uni Stuttgart), Georg Schwarz­kopf (Campione Venture), Alexander Schlen­sog (Ex Secunet), Dr Clara Herdeanu (Chief Communications Officer, Noxtua), Juliette Ast (Deeptech VC), Hans Ramsl (Weights & Biases), Jeroen Van Hautte (CTO, TechWolf), Christopher Craig (Google Cloud), Sebastian Stark (TUM Venture Labs), and Sebastian Spitzer (HPE), The financing round comes at a time of increased momentum for strategic digital sovereignty, as current geopolitical instability demonstrates the need for AI frontier models and sovereign systems developed in Europe. From Heidelberg University to frontier AI Johannes Haux (CEO), Dr Benjamin Herdeanu (CTO), and Gregor Ramien (COO) founded the European frontier AI lab kausable in 2025 based on their research at Heidelberg University and their working experience at start-ups as well as in highly regulated industries such as cybersecurity and the banking sector. kausable began developing its idea in 2024, incorporated in early 2025, and worked with the Startup BW Pre-Seed programme before raising approximately €1.5 million in pre-seed funding. Teaching AI to reason, not retrain A reasoning-first model is designed to learn and adapt more like humans. At the heart of kausable's approach is what it calls a 'world model' — a robust set of causal intuitions that allows the AI to adapt quickly to changes in its environment using very little new information. Haux explained: "Humans don't need to repeat the same task a million times to learn it. If you show someone how to open a door once or twice, they can usually figure out how to open a different door without starting from scratch. Today's AI doesn't work that way. It often requires huge amounts of data and constant retraining whenever conditions change." Instead of continually updating a model's internal weights, kausable trains a foundation model once and enables it to learn new tasks from just a handful of examples. This allows it to adapt quickly to new situations without requiring another costly training cycle. Ramien detailed: "Large language models build an understanding of the world from language. Our models instead learn directly from causal relationships. Rather than inferring how the world works from billions of text examples, we train on abstract cause-and-effect structures. That gives us a much more direct representation of how systems behave, allowing the model to transfer what it has learned across many different domains." The team recently also co-authored a research paper with experts from Columbia University , validating the causal reasoning architecture underlying its frontier model. Synthetic data, real-world intelligence One of kausable's biggest departures from conventional AI development is how it trains its models. Rather than relying on vast quantities of customer data, the company teaches its models using synthetic causal data, enabling them to learn how systems behave before being adapted to real-world applications. Haux argues that while additional data can improve model performance, it is not the determining factor. "More data certainly helps," he said. "Our approach is based on Bayesian learning, so the model continually improves as it receives additional evidence." However, he says the key advantage is that the system requires far fewer examples than conventional AI models to achieve useful performance, making it significantly more data-efficient than today's foundation models. Further, beyond the privacy benefits, he said this approach gives the company "much greater control over the kinds of systems our models can understand," creating what he believes is "a very defensible" commercial advantage. ​ Predicting black swans before they happen One of the first demonstrations of the technology is TipPFN , a zero-shot forecasting model for complex dynamic systems that predicts tipping points and other "black swan" events across domains including medicine and energy before they happen. Herdeanu explained: “We tested the model across 15 different domains, including ecological systems, biomedical data and energy infrastructure. For example, it can predict epileptic seizures from EEG data or anticipate power grid blackouts before they occur. The important point is that it learns these behaviours from only a handful of examples.” Ramien thinks of kausable’s models as learning instincts about how the world works. "They're trained entirely on synthetic causal systems rather than real-world data, but they can transfer that understanding to real applications. For example, our blackout prediction model had never seen an electrical grid during training. It simply received frequency data from the grid and was able to predict how close the system was to a critical transition.” That ability to personalise quickly is especially interesting for areas like healthcare, where every patient is different. From research lab to commercial AI The same rapid adaptation that makes the technology useful in healthcare also opens opportunities across robotics, forecasting and industrial systems. kausable has published research, submitted additional papers and demonstrated the first proof points. The next phase is working closely with early customers and testing the technology in real-world applications. Physical AI is one of the company’s biggest priorities because collecting enough training data is difficult, and robots constantly encounter situations they've never seen before. “Our technology is particularly valuable in environments where models need to adapt quickly without retraining. We're also interested in areas such as demand forecasting, where the problems are lower dimensional and can be commercialised earlier while we continue developing the broader platform,” shared Herdeanu. While the company is still primarily a research company, it plans to become more product-focused over the next year through customer pilot projects. Herdeanu credits kausable's rapid progress to its research team: "We have exceptional people who can quickly absorb new ideas and continually push the boundaries of what's possible," he said. While increased competition helps advance the field, he believes the company's edge comes from its ability to produce genuinely novel research. He also highlights the role of kausable's investors and angel backers, describing them as "extremely engaged" partners who contribute far more than capital and have become an important extension of the nine-person team. Many deep-tech founders struggle with the transition from academia into entrepreneurship. According to Haux, having three founders with complementary strengths has made a huge difference. “Herdeanu leads the research, Ramien brings extensive experience managing engineering teams, and I focus more on communicating the vision to investors, partners and customers. That balance allows us to keep advancing the technology while simultaneously building the company around it.” ​ According to Andreas Unseld, Partner at UVC Partners: “Nearly every industrial company runs on complex systems it struggles to predict and control – and today, applying AI to each one is slow and expensive. kausable makes that effort collapse. That turns AI from a series of costly one-off projects into something that can be rolled out across an entire industrial landscape – which is why we led this round.” “Most AI models are trained to remember the past. kausable is building AI that can reason about the future. Instead of relying on ever-larger datasets and constant retraining, they’re developing a fundamentally different approach: systems that adapt, infer causality and solve problems they have never seen before. It’s an ambitious scientific bet, and exactly the kind of foundational AI company we’re excited to back,” emphasised Pieterjan Bouten, Co-Founder, Entourage. According to Haux, the company offers a fundamentally different way to build AI. "Today's systems often require continuous retraining whenever sensors change, environments shift, or new data appears. We're building technology that can adapt to those changes almost immediately from only a handful of examples. Ultimately, we see this becoming a foundational intelligence layer that other AI systems can build upon." Ramien predicts that future AI systems will consist of specialised models working together. “Language models, vision models and other components will provide interfaces to the world, while this causal reasoning layer becomes the core intelligence making decisions and predictions. Because our approach is much more efficient, we also believe it offers a path towards dramatically reducing the computational cost of AI, making future systems both more sustainable and more economically viable.” kausable will use the new funding to expand its current nine-person team and to advance its rapid-learning frontier model. Lead image: kausable co-founder: Johannes Haux, Gregor Ramien, and Dr Benjamin Herdeanu.

AI systems need constant, costly retraining. European AI startup kausable raises €12 million in a seed funding round to solve this problem by developing reasoning-first frontier AI that adapts efficiently to changing context without further retraining. The European frontier lab kausable has ties to Heidelberg University and Black Forest Labs (BFL), one of Germany’s most prominent AI companies. The round is led by the German and Belgian investors UVC Partners and Entourage, with follow-on from the German investors HTGF and Mätch VC. kausable is also backed by various private angel investors from the AI industry and academia working at Black Forest Labs, OpenAI, Google DeepMind, Noxtua, and the European Laboratory for Learning and Intelligent Systems (ELLIS), including: Robin Rombach & An­dre­as Blatt­mann (Co-Founder, BFL), Sandro Gia­nel­la (International Strategy & Operations, OpenAI), Dorothy Chou (Strategic Advisor, DeepMind), Dr Michael Bolle (Ex-Board Member, Robert Bosch), Dr An­dre­as Nau­erz (CPO IONOS), Dr Jens Buchner (Lead, Neura Robotics), Jo­han­na Claus­sen & Cor­ne­li­us Claus­sen & Dr Marco Möller (Co-Founder Pionix), Prof Dr Mat­thi­as Bethge (Uni Tübingen, Co-Founder ELLIS), Prof Dr. Marco Aiello (Uni Stuttgart), Georg Schwarz­kopf (Campione Venture), Alexander Schlen­sog (Ex Secunet), Dr Clara Herdeanu (Chief Communications Officer, Noxtua), Juliette Ast (Deeptech VC), Hans Ramsl (Weights & Biases), Jeroen Van Hautte (CTO, TechWolf), Christopher Craig (Google Cloud), Sebastian Stark (TUM Venture Labs), and Sebastian Spitzer (HPE), The financing round comes at a time of increased momentum for strategic digital sovereignty, as current geopolitical instability demonstrates the need for AI frontier models and sovereign systems developed in Europe. From Heidelberg University to frontier AI Johannes Haux (CEO), Dr Benjamin Herdeanu (CTO), and Gregor Ramien (COO) founded the European frontier AI lab kausable in 2025 based on their research at Heidelberg University and their working experience at start-ups as well as in highly regulated industries such as cybersecurity and the banking sector. kausable began developing its idea in 2024, incorporated in early 2025, and worked with the Startup BW Pre-Seed programme before raising approximately €1.5 million in pre-seed funding. Teaching AI to reason, not retrain A reasoning-first model is designed to learn and adapt more like humans. At the heart of kausable's approach is what it calls a 'world model' — a robust set of causal intuitions that allows the AI to adapt quickly to changes in its environment using very little new information. Haux explained: "Humans don't need to repeat the same task a million times to learn it. If you show someone how to open a door once or twice, they can usually figure out how to open a different door without starting from scratch. Today's AI doesn't work that way. It often requires huge amounts of data and constant retraining whenever conditions change." Instead of continually updating a model's internal weights, kausable trains a foundation model once and enables it to learn new tasks from just a handful of examples. This allows it to adapt quickly to new situations without requiring another costly training cycle. Ramien detailed: "Large language models build an understanding of the world from language. Our models instead learn directly from causal relationships. Rather than inferring how the world works from billions of text examples, we train on abstract cause-and-effect structures. That gives us a much more direct representation of how systems behave, allowing the model to transfer what it has learned across many different domains." The team recently also co-authored a research paper with experts from Columbia University , validating the causal reasoning architecture underlying its frontier model. Synthetic data, real-world intelligence One of kausable's biggest departures from conventional AI development is how it trains its models. Rather than relying on vast quantities of customer data, the company teaches its models using synthetic causal data, enabling them to learn how systems behave before being adapted to real-world applications. Haux argues that while additional data can improve model performance, it is not the determining factor. "More data certainly helps," he said. "Our approach is based on Bayesian learning, so the model continually improves as it receives additional evidence." However, he says the key advantage is that the system requires far fewer examples than conventional AI models to achieve useful performance, making it significantly more data-efficient than today's foundation models. Further, beyond the privacy benefits, he said this approach gives the company "much greater control over the kinds of systems our models can understand," creating what he believes is "a very defensible" commercial advantage. ​ Predicting black swans before they happen One of the first demonstrations of the technology is TipPFN , a zero-shot forecasting model for complex dynamic systems that predicts tipping points and other "black swan" events across domains including medicine and energy before they happen. Herdeanu explained: “We tested the model across 15 different domains, including ecological systems, biomedical data and energy infrastructure. For example, it can predict epileptic seizures from EEG data or anticipate power grid blackouts before they occur. The important point is that it learns these behaviours from only a handful of examples.” Ramien thinks of kausable’s models as learning instincts about how the world works. "They're trained entirely on synthetic causal systems rather than real-world data, but they can transfer that understanding to real applications. For example, our blackout prediction model had never seen an electrical grid during training. It simply received frequency data from the grid and was able to predict how close the system was to a critical transition.” That ability to personalise quickly is especially interesting for areas like healthcare, where every patient is different. From research lab to commercial AI The same rapid adaptation that makes the technology useful in healthcare also opens opportunities across robotics, forecasting and industrial systems. kausable has published research, submitted additional papers and demonstrated the first proof points. The next phase is working closely with early customers and testing the technology in real-world applications. Physical AI is one of the company’s biggest priorities because collecting enough training data is difficult, and robots constantly encounter situations they've never seen before. “Our technology is particularly valuable in environments where models need to adapt quickly without retraining. We're also interested in areas such as demand forecasting, where the problems are lower dimensional and can be commercialised earlier while we continue developing the broader platform,” shared Herdeanu. While the company is still primarily a research company, it plans to become more product-focused over the next year through customer pilot projects. Herdeanu credits kausable's rapid progress to its research team: "We have exceptional people who can quickly absorb new ideas and continually push the boundaries of what's possible," he said. While increased competition helps advance the field, he believes the company's edge comes from its ability to produce genuinely novel research. He also highlights the role of kausable's investors and angel backers, describing them as "extremely engaged" partners who contribute far more than capital and have become an important extension of the nine-person team. Many deep-tech founders struggle with the transition from academia into entrepreneurship. According to Haux, having three founders with complementary strengths has made a huge difference. “Herdeanu leads the research, Ramien brings extensive experience managing engineering teams, and I focus more on communicating the vision to investors, partners and customers. That balance allows us to keep advancing the technology while simultaneously building the company around it.” ​ According to Andreas Unseld, Partner at UVC Partners: “Nearly every industrial company runs on complex systems it struggles to predict and control – and today, applying AI to each one is slow and expensive. kausable makes that effort collapse. That turns AI from a series of costly one-off projects into something that can be rolled out across an entire industrial landscape – which is why we led this round.” “Most AI models are trained to remember the past. kausable is building AI that can reason about the future. Instead of relying on ever-larger datasets and constant retraining, they’re developing a fundamentally different approach: systems that adapt, infer causality and solve problems they have never seen before. It’s an ambitious scientific bet, and exactly the kind of foundational AI company we’re excited to back,” emphasised Pieterjan Bouten, Co-Founder, Entourage. According to Haux, the company offers a fundamentally different way to build AI. "Today's systems often require continuous retraining whenever sensors change, environments shift, or new data appears. We're building technology that can adapt to those changes almost immediately from only a handful of examples. Ultimately, we see this becoming a foundational intelligence layer that other AI systems can build upon." Ramien predicts that future AI systems will consist of specialised models working together. “Language models, vision models and other components will provide interfaces to the world, while this causal reasoning layer becomes the core intelligence making decisions and predictions. Because our approach is much more efficient, we also believe it offers a path towards dramatically reducing the computational cost of AI, making future systems both more sustainable and more economically viable.” kausable will use the new funding to expand its current nine-person team and to advance its rapid-learning frontier model. Lead image: kausable co-founder: Johannes Haux, Gregor Ramien, and Dr Benjamin Herdeanu.

Berlin-based AI startup telli has raised $15 million in a seed funding round to expand its AI platform for customer-facing operations. The round was led by redalpine, with participation from Mutschler, Cherry Ventures, Y Combinator and several angel investors, bringing the company's total funding to more than $18.5 million. Founded in 2024 by Seb Hapte-Selassie, Philipp Baumanns and Finn zur Muehlen, telli develops AI agents that help B2C companies automate customer-facing operations across voice, chat, SMS, WhatsApp and email. Its platform enables businesses to deploy AI agents, manage customer conversations, analyse interactions and automate workflows across sales, service and support functions. At the core of the platform is Charlie, an AI coworker designed to help customer operations teams build and optimise AI agents, connect internal systems, analyse conversations, identify operational issues and improve customer communications. The company is addressing a shift in how consumers interact with businesses as AI assistants increasingly handle tasks such as customer support, appointment booking, contract management and product comparisons. As communication expands across multiple channels and AI agents become more widely adopted, businesses face growing operational complexity in delivering consistent customer experiences while maintaining efficient operations. telli says its AI agents already handle millions of customer conversations for businesses ranging from SMEs to large enterprises, by answering customer enquiries, qualifying leads, booking appointments and resolving service requests. Customer-facing operations are becoming too complex to run with the current tools alone. The next generation of consumer companies will need AI that can talk to customers, work across channels, and help teams improve the operation behind every interaction. That's what we're building with telli, said Finn zur Muehlen, co-founder and CEO of telli. The funding will be used to expand the company's engineering and go-to-market teams, further develop Charlie, enhance its voice and multi-channel AI agent platform, and support more B2C companies in adopting AI-powered customer operations.

Revolut has confirmed that it has started a fresh secondary share sale, valuing the digital bank at a reported $115bn.   The sale will allow some Revolut employees to cash in on their shares, which, according to Bloomberg, are valued at $2,017 each.   Revolut said: "We can confirm that a secondary share sale process is underway. As is standard, we won't comment on the details while the process is ongoing, and we'll provide an update once it has completed."   According to an internal message from Revolut CEO and co-founder Nik Storonsky sent to Revolut staff, reported by Bloomberg, Storonsky said: “I’m glad that you now have another opportunity to realise liquidity on your shares.   “Revolut’s momentum over the past twelve months, underpinned by the strong fundamentals of the business and our continued expansion into new markets, has attracted significant demand from new and existing investors." Last year, Revolut carried out secondary transactions that priced the company at $75bn, up from $45bn in 2024.    Revolut has over 75m retail customers globally.   Earlier this year it won a UK banking licence, and it has applied for a banking licence in the US and France.   Employee share sales have become popular in recent years with startups, as they look to offer liquidity options for employees and a way of bringing on new investors, amid a drying up of the IPO market.

London-based AI deployment startup Arrakis has emerged from stealth, having raised nearly $40m in just over three months. Arrakis was founded by former Accel investor Rafael Quintanilla, along with former Palantir executive Haroun Beltaifa, Romain Fouilland, also previously of Palantir, and Mikhail Galkov, a former Delivery Hero engineer. It has raised $38m in over three months, including a $30m Series A co-led by Blossom Capital with participation from Accel, which invested at seed in March. Others contributing to the funding include Olivier Pomel, founder and chief executive of Datadog, Olivier Godement, OpenAI’s head of business products, and Junaid Hussein, founder of Cambridge Aerospace. Arrakis, founded in January this year, helps industrial companies design, build and scale AI agents. It helps companies deploy AI agents into key operations across aerospace, energy, logistics, manufacturing, construction and telecommunications. Its pitch is that companies are experimenting with AI chatbots but struggle to deploy AI that can carry out business tasks effectively. Arrakis says it has a model-agnostic approach and uses forward-deployed AI engineers. It says its approach allows companies to leverage their data to train, deploy, and scale AI agents in weeks. Arrakis will use the funding to open offices in New York and the Middle East, platform development and AI deployment. It says it has secured customers including NYSE-listed enterprises across the energy, logistics, and industrial sectors. Quintanilla, co-founder and CEO of Arrakis, said: “The West is under growing pressure to reindustrialise, but that renaissance won't be powered by net new companies alone. It requires equipping our industrial champions with the tools to harness their data, navigate the AI transition and compete on a global stage.”

London-based AI deployment startup Arrakis has emerged from stealth, having raised nearly $40m in just over three months. Arrakis was founded by former Accel investor Rafael Quintanilla, along with former Palantir executive Haroun Beltaifa, Romain Fouilland, also previously of Palantir, and Mikhail Galkov, a former Delivery Hero engineer. It has raised $38m in over three months, including a $30m Series A co-led by Blossom Capital with participation from Accel, which invested at seed in March. Others contributing to the funding include Olivier Pomel, founder and chief executive of Datadog, Olivier Godement, OpenAI’s head of business products, and Junaid Hussein, founder of Cambridge Aerospace. Arrakis, founded in January this year, helps industrial companies design, build and scale AI agents. It helps companies deploy AI agents into key operations across aerospace, energy, logistics, manufacturing, construction and telecommunications. Its pitch is that companies are experimenting with AI chatbots but struggle to deploy AI that can carry out business tasks effectively. Arrakis says it has a model-agnostic approach and uses forward-deployed AI engineers. It says its approach allows companies to leverage their data to train, deploy, and scale AI agents in weeks. Arrakis will use the funding to open offices in New York and the Middle East, platform development and AI deployment. It says it has secured customers including NYSE-listed enterprises across the energy, logistics, and industrial sectors. Quintanilla, co-founder and CEO of Arrakis, said: “The West is under growing pressure to reindustrialise, but that renaissance won't be powered by net new companies alone. It requires equipping our industrial champions with the tools to harness their data, navigate the AI transition and compete on a global stage.”

Fintech-for-good platform Lightning Reach has been acquired by European Technology Group (ETG), a mission-aligned govtech group and long-term investor. Despite over 20 million people living in financially vulnerable circumstances, over £24 billion in financial support goes unclaimed each year. This is because support is spread across different organisations and remains highly fragmented, application processes are often manual, and awareness of available schemes is low. At the same time, local authorities, charities and other organisations face the challenge of rising demand, constrained budgets and complex administrative and reporting requirements. Founded during the Covid-19 pandemic, Lightning Reach was created to bridge this gap, making it easier for people to access the financial support available to them through a single, simple platform. It provides the infrastructure for organisations to deliver support more effectively, reach more people and create greater impact.  The company now partners with over 100 organisations across the UK, including some of the largest utility providers, local authorities, charities, housing associations and banks.  It was initially backed by nearly 30 investors including the Joseph Rowntree Foundation, Big Issue Invest and Techstars, and was recently named Fintech for Good of the Year at the Fintech Awards London. Since launch, more than 300,000 people have unlocked over £25 million in financial support through Lightning Reach. ETG acquires and scales software businesses serving the public sector and other regulated industries in Europe. Built and backed by entrepreneurs for entrepreneurs, ETG provides a strategic platform for founders and their teams, offering resources to support growth in areas such as sales, international expansion, and product development. ETG currently has over 400 public sector clients serving a combined population of over 14 million citizens across six countries. The acquisition marks the next stage of Lightning Reach’s expansion following a period of strong growth, having reached more than 300,000 people and facilitated over £25 million in financial assistance since its platform was launched in December 2021. The company quadrupled its annual recurring revenue over the past year while remaining cash positive. As part of ETG, Lightning Reach will benefit from long-term backing, public sector technology expertise and additional resources to accelerate its goal of helping over 1 million people access the financial support available to them by 2028. This will enable the company to broaden its market access, enhance public sector procurement and further invest in product innovation to unlock faster, more efficient delivery of a wider range of support. Under the new ownership structure, Lightning Reach will continue operating independently with its existing team and stay focused on its mission, with no changes to the platform or services anticipated for partners or clients.  As part of the transition, COO Rhiannon Sheridan has become CEO of Lightning Reach, leading the next phase of growth. Founder and former CEO Ren Yi Hooi will remain involved as a Director on the Board.  The acquisition represents ETG's third investment and reflects its strategy of supporting technology businesses that improve the delivery of public services and social outcomes. According to Ren Hooi, Founder of Lightning Reach: “I’ve always wanted to make sure our impact as a company can outlast my role as the founder, and it’s clear we’ve reached this point. Rhiannon has been an exceptional leader since she joined our early team nearly five years ago and is the ideal person to lead our next phase, with ETG providing the dream long-term home that will allow us to stay laser-focused on our mission.” Rhiannon Sheridan, CEO of Lightning Reach, added: “When I joined Lightning Reach, we were a tiny team with a big goal, to make it easier for people to access support while removing the manual work that slows organisations down.  With ETG’s long-term backing, sector expertise and clear alignment with our mission, we have the right partner to help us scale sustainably, deepen our partnerships and keep investing in the platform as we work towards helping one million people access financial support by 2028.” Lars Becker, CEO and Co-Founder of ETG, added: “Lightning Reach is tackling one of the most important challenges out there: making sure people in financial hardship can actually access the help they are entitled to.  The team has built something genuinely special, with a brilliant product and real proof of impact. We see a significant opportunity to grow its reach across the UK and beyond, and we could not be more excited to support Rhiannon and the team as they scale.”

Fintech-for-good platform Lightning Reach has been acquired by European Technology Group (ETG), a mission-aligned govtech group and long-term investor. Despite over 20 million people living in financially vulnerable circumstances, over £24 billion in financial support goes unclaimed each year. This is because support is spread across different organisations and remains highly fragmented, application processes are often manual, and awareness of available schemes is low. At the same time, local authorities, charities and other organisations face the challenge of rising demand, constrained budgets and complex administrative and reporting requirements. Founded during the Covid-19 pandemic, Lightning Reach was created to bridge this gap, making it easier for people to access the financial support available to them through a single, simple platform. It provides the infrastructure for organisations to deliver support more effectively, reach more people and create greater impact.  The company now partners with over 100 organisations across the UK, including some of the largest utility providers, local authorities, charities, housing associations and banks.  It was initially backed by nearly 30 investors including the Joseph Rowntree Foundation, Big Issue Invest and Techstars, and was recently named Fintech for Good of the Year at the Fintech Awards London. Since launch, more than 300,000 people have unlocked over £25 million in financial support through Lightning Reach. ETG acquires and scales software businesses serving the public sector and other regulated industries in Europe. Built and backed by entrepreneurs for entrepreneurs, ETG provides a strategic platform for founders and their teams, offering resources to support growth in areas such as sales, international expansion, and product development. ETG currently has over 400 public sector clients serving a combined population of over 14 million citizens across six countries. The acquisition marks the next stage of Lightning Reach’s expansion following a period of strong growth, having reached more than 300,000 people and facilitated over £25 million in financial assistance since its platform was launched in December 2021. The company quadrupled its annual recurring revenue over the past year while remaining cash positive. As part of ETG, Lightning Reach will benefit from long-term backing, public sector technology expertise and additional resources to accelerate its goal of helping over 1 million people access the financial support available to them by 2028. This will enable the company to broaden its market access, enhance public sector procurement and further invest in product innovation to unlock faster, more efficient delivery of a wider range of support. Under the new ownership structure, Lightning Reach will continue operating independently with its existing team and stay focused on its mission, with no changes to the platform or services anticipated for partners or clients.  As part of the transition, COO Rhiannon Sheridan has become CEO of Lightning Reach, leading the next phase of growth. Founder and former CEO Ren Yi Hooi will remain involved as a Director on the Board.  The acquisition represents ETG's third investment and reflects its strategy of supporting technology businesses that improve the delivery of public services and social outcomes. According to Ren Hooi, Founder of Lightning Reach: “I’ve always wanted to make sure our impact as a company can outlast my role as the founder, and it’s clear we’ve reached this point. Rhiannon has been an exceptional leader since she joined our early team nearly five years ago and is the ideal person to lead our next phase, with ETG providing the dream long-term home that will allow us to stay laser-focused on our mission.” Rhiannon Sheridan, CEO of Lightning Reach, added: “When I joined Lightning Reach, we were a tiny team with a big goal, to make it easier for people to access support while removing the manual work that slows organisations down.  With ETG’s long-term backing, sector expertise and clear alignment with our mission, we have the right partner to help us scale sustainably, deepen our partnerships and keep investing in the platform as we work towards helping one million people access financial support by 2028.” Lars Becker, CEO and Co-Founder of ETG, added: “Lightning Reach is tackling one of the most important challenges out there: making sure people in financial hardship can actually access the help they are entitled to.  The team has built something genuinely special, with a brilliant product and real proof of impact. We see a significant opportunity to grow its reach across the UK and beyond, and we could not be more excited to support Rhiannon and the team as they scale.”

UK software supply chain security startup Ossprey has raised $2.65 million in an oversubscribed pre-seed funding round to accelerate product development, expand its engineering and commercial teams, and support international growth. The round was led by Episode 1 Ventures, with participation from Osney Capital and Octopus Ventures. Founded by Nate Dunning and David Read, Ossprey develops software supply chain security technology that helps organisations detect malicious code hidden within open-source software packages before it reaches production environments. The platform continuously scans open-source packages for malware, enabling development teams to secure their software without slowing engineering workflows. The company was founded in response to growing software supply chain security risks as AI accelerates modern software development. Around 90 per cent of enterprise software relies on open-source components, while attackers are increasingly embedding malicious code within trusted packages to infiltrate organisations through legitimate development workflows. As AI coding assistants accelerate software development and increase the volume of code entering production, securing the software supply chain has become increasingly important. We founded Ossprey because existing approaches weren't designed for the pace modern engineering teams now operate at. Organisations shouldn't have to choose between shipping software quickly and building it securely. This investment allows us to continue developing technology that helps organisations build safely at AI speed while expanding our reach internationally, said Nate Dunning, CEO of Ossprey. The company plans to continue expanding across the UK, Europe and North America, focusing on enterprise organisations building software at scale, while preparing for a larger funding round to support its next stage of growth.

UK software supply chain security startup Ossprey has raised $2.65 million in an oversubscribed pre-seed funding round to accelerate product development, expand its engineering and commercial teams, and support international growth. The round was led by Episode 1 Ventures, with participation from Osney Capital and Octopus Ventures. Founded by Nate Dunning and David Read, Ossprey develops software supply chain security technology that helps organisations detect malicious code hidden within open-source software packages before it reaches production environments. The platform continuously scans open-source packages for malware, enabling development teams to secure their software without slowing engineering workflows. The company was founded in response to growing software supply chain security risks as AI accelerates modern software development. Around 90 per cent of enterprise software relies on open-source components, while attackers are increasingly embedding malicious code within trusted packages to infiltrate organisations through legitimate development workflows. As AI coding assistants accelerate software development and increase the volume of code entering production, securing the software supply chain has become increasingly important. We founded Ossprey because existing approaches weren't designed for the pace modern engineering teams now operate at. Organisations shouldn't have to choose between shipping software quickly and building it securely. This investment allows us to continue developing technology that helps organisations build safely at AI speed while expanding our reach internationally, said Nate Dunning, CEO of Ossprey. The company plans to continue expanding across the UK, Europe and North America, focusing on enterprise organisations building software at scale, while preparing for a larger funding round to support its next stage of growth.

Robotics deployment company microagi today announced a collaboration with Google Cloud to accelerate the development of models and robotics capable of understanding and interacting with physical environments. As part of the collaboration, microagi will use Google Cloud’s advanced AI stack and the NVIDIA Blackwell platform to scale its model training workloads. microagi's Atlas platform fine-tunes AI models using each customer's operational data, creating robotics systems tailored to specific industrial tasks. The hardware- and model-agnostic platform sits between customers' infrastructure and frontier AI models, avoiding vendor lock-in. Founded in 2025, the company is headquartered in Munich, with a research hub in Zurich and offices in London and New York.  Its business model aims to accelerate robotics AI development by training task-specific models for individual robotic platforms. The company operates a unique business model designed to accelerate robotics AI development, including training task-specific models for robotic platforms. I spoke to Bercan Kilic, CEO and co-founder of Microagi to learn more. Five days of fundraising, months of investor interest The news comes a week after the company announced it had raised $55 million in seed funding, the largest seed round in German history. The round was led by Hummingbird, with participation from Northzone, LocalGlobe, Village Global and redalpine Unusually, the company says it has spent only five days fundraising — two days for the pre-seed and three for the seed round.  “That's unusual, but it reflects the fact that investors had been tracking our progress long before we formally opened a round,” said Kilic. “We were demonstrating our technology to research labs, customers and robotics partners, showing progress across data collection, compute infrastructure and robot training." Hummingbird Ventures had been tracking the company's progress for several months before reaching out and visiting the team. Following the visit, the firm moved quickly to invest. While other investors also expressed interest, Hummingbird was already providing strategic support and making introductions even before the fundraising round had officially begun. The parties signed a term sheet within just three days. Europe faces an embodied AI crossroads Kilic believes that if Europe doesn't act quickly, the technology gap with the US and China could become larger than Europe's current gap with developing economies.  "AI is advancing so rapidly that governments are increasingly likely to treat advanced models and compute as strategic national assets. If export restrictions become commonplace, countries without sufficient domestic compute infrastructure will struggle to compete. That's why we believe the next 18 months are critical. Europe needs to invest in energy, data centres and advanced compute now — not simply for startups like microagi, but for the entire European innovation ecosystem.” The former Formula 1 engineer from Red Bull Racing was inspired to build the company after concern for Europe’s future. He contends that every year, AI models were improving exponentially, while Europe wasn't making the same progress.  “The moment that really hit me was seeing open-source Vision-Language-Action (VLA) models emerge. As a mechanical engineer, robotics has always been close to my heart, and I realised the next frontier had arrived, yet almost nobody in Europe was building for it.” Initially, he didn't even plan to start a company. But the more he explored the space, the clearer it became that Europe was missing three essential ingredients: large-scale robotics data, massive compute capacity, and the infrastructure to train and deploy embodied AI systems. “Without all three, Europe risks becoming irrelevant over the next 20 to 30 years.” Building productivity, not replacing workers Long-term, the company’s ambition isn't simply to improve margins for individual companies. It's to increase productivity enough that European manufacturers can compete on both quality and price. “China offers an interesting example. Rather than replacing workers, successful manufacturers often expand capacity by opening new factories that produce more goods at lower cost. Greater productivity drives prices down while increasing competitiveness. Over time, that creates abundance. As robotics improves, costs should continue falling. Some robots can already operate 24 hours a day. They're currently slower than humans in many tasks, but we expect that to change.” Kilic shared that the partnership is important because both companies recognise that Europe needs strong leaders in embodied AI. “NVIDIA provides the compute platform, while Google Cloud provides the cloud infrastructure and engineering support. We'd already been working with Google Cloud, but this partnership significantly deepens that relationship.” One of the biggest benefits has been efficiency.  “Google's engineers have helped us optimise our clusters so we're effectively achieving roughly twice the computational efficiency while using substantially less energy per unit of work. That optimisation work is ongoing,” said Kilic. How Google Cloud and NVIDIA accelerate training The new partnership announced today will ensure microagi has access to highly optimised, NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs (G4 VMs) and NVIDIA GB300 NVL72 rack-scale systems (A4X Max instances) to power its model training and inference workloads.  This infrastructure will support microagi’s efforts to offer customisable software packages for enterprise robotics. For example, hospitality or industrial businesses will be able to procure robots pre-configured with microagi models tailored for specific operational roles. Working closely with both Google Cloud and NVIDIA engineering teams, microagi can streamline its workflows on Google Cloud's platform and bring new products to customers more quickly. “Robotics is becoming one of the most demanding frontiers for AI, requiring massive physical-world datasets, accelerated compute and a full-stack platform to turn models into intelligent machines,” said Tobias Halloran, Director of EMEAI Startups at NVIDIA. “By running on NVIDIA Blackwell-powered instances on Google Cloud, microagi can scale the training and deployment of embodied AI systems for commercial and industrial environments.” An end-to-end robotics AI platform In a sector where many companies are developing the software intelligence layer for physical AI, Kilic believes microagi's competitive advantage lies in offering an end-to-end ecosystem. “Robotics doesn't have an internet-scale dataset like language models do, so collecting high-quality data is one of the industry's biggest challenges. We collect diverse robotics data, train foundation models on large-scale compute infrastructure, and then fine-tune those models using each customer's own operational data. That process transforms a capable general model into one that's highly effective in a specific industrial environment.” Importantly, microagi customers always retain ownership of their data and models: “Unlike some approaches where customer data ultimately improves shared foundation models, we ensure each customer's intellectual property remains protected. Why European compute matters Equally important is microagi’s commitment to European compute infrastructure.  “Whenever possible, we want our workloads to run on European-based infrastructure,” asserts Kilic. “There are two reasons. First, our customers are European manufacturers with valuable intellectual property. Even if they trust us, they may not want sensitive production data processed outside Europe. Keeping workloads within Europe under GDPR provides additional confidence" Second, he believes Europe must build its own long-term AI infrastructure. “If advanced chips become subject to export restrictions or geopolitical tensions increase, the only compute Europe can rely on will be the infrastructure already located here. Creating demand today encourages companies to continue investing in European AI infrastructure.” From here on, the company’s focus is execution. “We have customers, data and compute. Now it's about scaling deployments. Alongside that, one of our biggest priorities is expanding European compute capacity. We believe Europe needs significantly more AI infrastructure if it wants to remain competitive over the next decade.