Edmund, a Czech startup developing an AI-powered debugging platform for industrial maintenance, has raised €2.5 million in funding led by FORWARD.one, with participation from University2Ventures and Tensor Ventures.  Check out an earlier Tech.eu interview with Jakub Szlaur,  CEO and founder of Edmund. Manufacturing is entering a period of structural strain. As production systems become more complex and data-intensive, the availability of skilled engineers is moving in the opposite direction. In Europe alone, tens of thousands of engineering roles remain unfilled, while around 20 per cent of the current workforce is expected to retire within the next decade. This combination of rising complexity and shrinking expertise is leaving companies increasingly dependent on fragmented documentation, legacy systems, and institutional knowledge to keep operations running, driving costly downtime, slow diagnostics, and growing operational risk across global supply chains. Edmund addresses this gap by deploying AI agents that connect technical documentation, PLC projects, maintenance logs, and real-time machine data into a single system. Rather than acting as a generic chatbot, the platform functions as an operational layer inside the factory, enabling technicians to identify faults, understand root causes, and receive step-by-step guidance within minutes. In practice, this approach significantly reduces the time required to diagnose issues, cutting troubleshooting from hours or days to minutes. In manufacturing, the majority of downtime is spent diagnosing faults rather than fixing them, often up to 80 per cent of the total time. Edmund cuts this analysis phase by up to 90 per cent, dramatically reducing overall downtime and accelerating recovery. At Amcor Flexibles, for example, Edmund’s system reduced average repair times by 26 per cent in total, saving approximately 440 man-hours annually, per factory. Founded in 2023, Edmund is designed to be hardware-agnostic and compatible with a wide range of industrial systems.  “The real challenge is not a lack of data, but a lack of context,” said Jakub Szlaur, co-founder and CEO of Edmund. “We’re building AI agents that understand how machines actually work, down to the PLC project level, so instead of searching through documentation or waiting for experts, engineers can act immediately.” “Edmund is solving one of the most overlooked challenges in industrial maintenance: how knowledge is transferred and applied under pressure,” said Beau Anne-Chilla, Partner at FORWARD.one. “Their approach has the potential to become a foundational layer for modern manufacturing.” According to Dr Johannes Triebs, Founding Partner at U2V (ex-Earlybird-X), Edmund is turning the factory floor into an intelligent, self-diagnosing system that gives manufacturers real-time answers instead of costly downtime.  “Our corporate network spans exactly the industrial players Edmund needs to accelerate its expansion, and we look forward to helping Edmund expand across Europe." The company will use the new funding to grow its team, expand across European and US markets, and further develop its platform toward fully contextual, AI-driven troubleshooting and diagnostics for industrial operations.

London-based Qoro Quantum has secured $750,000 in a pre-seed funding round to develop software infrastructure for hybrid quantum-classical computing. The round includes backing from Ada Ventures, Superangels Venture Fund, and the Polsky Center for Entrepreneurship and Innovation. Founded in 2024, Qoro Quantum is a deeptech company building software infrastructure for distributed quantum computing. Its platform provides a unified orchestration layer that connects classical systems, such as CPUs and GPUs, with emerging quantum processors, enabling hybrid applications to run across heterogeneous environments. As the industry continues to develop fully functional quantum computers, enterprises are already combining classical processors with early-stage quantum hardware to address complex challenges. However, integrating these systems remains resource-intensive, often requiring specialised expertise, significant time, and extensive custom code. Qoro’s software stack simplifies this process by reducing integration complexity and enabling diverse computing systems to operate as a unified environment. While the broader industry is racing to build physical quantum hardware, we are focused on the immediate software bottleneck required to actually use those machines, said Dan Holme, CEO of Qoro Quantum. The company’s platform includes a network stack and cloud-based control system that automates the execution of quantum algorithms, manages resource allocation, and synchronises multi-vendor computing clusters. By abstracting hardware complexity, it allows applications to be built once and deployed across high-performance and quantum computing environments. The funding will support the development of its hybrid quantum-classical software layer, as well as key engineering hires, grant co-funding, and accelerated product rollout ahead of its next funding round.

Italian-based TeiaCare has raised €7 million in a funding round led by P101 SGR. The round also included participation from existing shareholders and new healthcare-focused investors, including Spanish family offices Namarel and Inderhabs. Founded in 2018 by Guido Magrin and Luca Iozzia, TeiaCare develops care-monitoring solutions for residential healthcare facilities such as nursing homes, rehabilitation centres, and dementia care units. Its proprietary platform, Ancelia, combines optical sensors and artificial intelligence to monitor care environments and convert the data into actionable insights, supporting care staff in decision-making, risk prevention, and daily operations. Guido Magrin said that as structural weaknesses in the residential healthcare sector become more apparent, technology is no longer optional but essential: Today, we have a unique opportunity to help define a new category of care solutions: practical tools that support care professionals, improve the quality of life for vulnerable individuals, and structurally address one of the major challenges of our time - population aging. The company currently serves more than 150 clients across over 200 facilities, covering around 75,000 residents. It operates in a sector under increasing pressure, driven by rising demand for long-term and home care services, as well as ongoing workforce shortages. TeiaCare will use the new funding to scale its business model, expand into new geographic markets, and further develop its Data, Spatial, and Care Intelligence capabilities. The company also plans to extend its solutions beyond residential care into broader healthcare and home care settings, while initiating its international expansion with an initial focus on France and Spain.

OpenAI’s plans to bring its flagship $500bn AI data centre project to the UK have been put on hold, with the ChatGPT developer citing energy costs and regulatory issues as factors which have halted its plans. OpenAI announced plans to bring its giant Stargate AI project to the UK in September last year, marking what it said was ”a major step forward in the US-UK technology partnership” helping the UK government build its sovereign AI capabilities. The UK government said the project would “help boost AI infrastructure and adoption in the UK – transforming public services and growing the economy”. The scheme was run in partnership with Nscale and Nvidia, with plans to run around 8,000 Nvidia AI processors at a data centre in Cobalt Park, Tyneside, during the first quarter of this year. Commenting on pausing Stargate UK, OpenAI said: “We see huge potential for the UK's AI future. London is home to our largest international research hub, and we support the Government's ambition to be an AI leader. "AI compute is foundational to that goal - we continue to explore Stargate UK and will move forward when the right conditions such as regulation and the cost of energy enable long-term infrastructure investment." The news that OpenAI’s Stargate plans in the UK had stalled was first reported by the Daily Telegraph. OpenAI announced plans for its $500bn Stargate project in January 2025. It was announced at the White House by President Donald Trump who billed it "the largest AI infrastructure project by far in history" and said it would help keep "the future of technology" in the US.

Spanish startup Sybol, which focuses on corporate digital identity and verifiable credentials, has raised over €1 million in a funding round that combines public and private investment. The round is backed by the Spanish Society for Technological Transformation (SETT), alongside investors including Repsol, Grupo Synaptia, Bolboreta Innova Group, Tritemius, Venturade, and Chromata Invest. The company is operating within the evolving European regulatory landscape, particularly eIDAS2, which establishes a unified framework that allows citizens and businesses to identify themselves and share verified information across the European Union via digital wallets. In response to this, Sybol is developing a corporate wallet aligned with the emerging European Business Wallet model, designed to integrate with existing enterprise systems. The progress of eIDAS2 and the European Business Wallet opens a new chapter for corporate digital identity. Sybol enables companies to start preparing with a corporate wallet designed for this new framework. said Raúl López, CEO of Sybol. Sybol’s platform allows organisations to issue, manage, and verify digital certificates linked to their own identity as well as to that of clients or third parties. These certificates are created in a standardised, reusable format, enabling seamless exchange between organisations and functioning as verifiable digital evidence. By replacing traditional document-based workflows, the platform reduces manual processes, improves traceability, and enhances data reliability without requiring significant changes to operations Initial deployments are focused on sustainability-related certifications, where data is often shared through static documents that lack traceability and automated validation. Sybol’s approach links certificates directly to the verified identities of issuers and recipients, enabling ESG, auditing, and reporting platforms to use the data as structured, reliable digital evidence. This transforms certificates from static files into traceable digital assets, improving efficiency and reducing reliance on manual validation processes. The funding will be used to accelerate the rollout of Sybol’s enterprise verification platform and its corporate wallet based on digital identity principles.

Vinted, the second-hand marketplace unicorn, today said its revenues surpassed €1bn last year, but profits dipped nearly 20 per cent, as it took a financial hit from its investments. Financial figures for Vinted Group, which includes its core second-hand marketplace Vinted, shipping service Vinted Go, and Vinted Pay, its payment platform, show revenues came in at €1.1bn in 2025, up 38 per cent on the year, while profits fell 19 per cent on the year to €62m. Profits fell at Lithuania’s first unicorn due to its investment in a number of areas, the 2008-founded company said. These included investment in the German market, expansion of Vinted Marketplace categories, expansion of Vinted Go’s carrier services to Portugal and Spain, and the introduction of the Vinted Pay wallet. Vinted, which is headquartered in Vilnius, first reported a profit in 2024. Gross Merchandise Value (GMV), which is a key metric for retailers and measures the total value of goods sold, rose 47 per cent to €10.8bn. Vinted has benefited from rising inflation, which has led shoppers to turn to cheaper, second-hand products. 2025 highlights, according to Vinted, include turning around its performance in Germany, along with a “strong performance” in women’s and children’s clothing, while Vinted continued its expansion into more consumer-goods categories, including sports and collectables, it said. In 2025, Vinted, which is available in 26 countries and was valued at around €5 billion in 2024, launched in the new markets of Latvia, Estonia and Slovenia. Vinted is reportedly discussing a share sale that would value it at around €8 billion. Thomas Plantenga, CEO of Vinted, said: “To make second-hand first choice, we know what we need to do: we need to be the most cost-efficient, be the most reliable and easy to use. Therefore we need to build an ecosystem for C2C second-hand trade, that maximises value to members at the lowest possible cost. We do this by investing in technology to have long-term scalable impact. That’s why you see us improving our product, investing in safety and member support, while strengthening the rails that power the marketplace: shipping and payments.”

Plume, a Franco-American startup specialising in geospatial AI for renewable energies, has raised a €3.3M funding round led by AENU, with participation from Y Combinator, Kima Ventures, Raise Phiture, Better Angle and Collab Fund.  Founded by Edouard Labarthe (ex-Palantir) and Marc Watine (ex-Harvard researcher in geospatial and AI), the startup was incubated by Y Combinator- Plume has developed a platform that centralises more than 150 geographical datasets updated continuously and deploys AI agents that reason on thousands of unstructured documents to accelerate prospecting, permit processing and grid connection.  Developing a renewable energy project (solar, wind, or battery storage) requires cross-referencing zoning data, grid capacity, protected areas, and land parcels, while analysing municipal deliberations, permit histories, environmental studies, and grid development plans. In France, this work mobilises nearly a hundred layers of geographical data, to which are added urban planning documents, agricultural chamber records and permit archives.  Most of this work remains manual, entrusted to large teams for months: many projects are thus abandoned after years of work, and delays are measured in years when the climate transition demands months.  According to Edouard Labarthe, co-founder and CEO of Plume, renewable energy development is a reasoning problem hidden in maps and documents: “Uncertainty regarding risks and timelines remains one of the main obstacles to the deployment of renewables in Europe. We are building the intelligence layer that allows teams to move faster and increase the share of projects that actually succeed. Our AI agents synthesise structured geospatial data and unstructured regulatory information to produce clear territorial intelligence, helping project developers go faster while selecting projects with the highest probability of reaching construction.”  Plume aggregates more than 150 sources: natural areas, electrical grids, PPRi (flood risk prevention plans), building permits, local authority deliberations and deploys AI agents that reason over all of this information in natural language.  A project manager can query the platform without any technical skills and obtain a site analysis in seconds, where previously several weeks of manual work were required. By enabling better site selection and earlier risk detection, Plume improves the efficiency of capital investment and reduces unforeseen setbacks at the end of development. According to its clients, Plume agents enable site analyses to be conducted up to 20 times faster and three times more accurately. In France, nearly 500 companies developing renewable infrastructure could benefit from the platform.  Robert Stoecker, partner at AENU, shared: “Plume tackles the most critical bottleneck in the energy transition: the years of friction accumulated from manual site selection and permit processing. By transforming fragmented geospatial layers and unstructured data into an agentic intelligence platform, they allow developers to go 20 times faster. We are delighted to support a team that is not just building a tool, but a new standard for the deployment of global energy infrastructure.”  Already deployed in France, Spain, Romania, and the Czech Republic, Plume aims to enter Italy and the United States in 2026.  This first round of funding will finance team expansion, the launch into new European markets, and the next phases of platform stakeholder mapping, AI-based competitive intelligence, and automated drafting of permit applications. The company is recruiting in the fields of AI systems, geospatial engineering and energy analysis. 

Revolut is today rolling out its first AI-powered financial assistant to its 13 million-plus UK customers, claiming it is more sophisticated than a traditional chatbot, saying it represents a fundamental shift in how customers can interact with their finances. Revolut, valued at $75bn, is the latest challenger bank to leverage AI, hoping to simplify the financial lives of its customers. Revolut said the free-to-use AI assistant within the Revolut app will “end the era of multi-step navigation” and act as a co-pilot, helping customers navigate their financial life through simple prompts, be it giving them spending insights, managing subscriptions, or planning holidays. Julia Ponomareva, director and general manager of CX and AI product, Revolut, said, "We believe the era of navigating through endless tabs and menus is over. With AIR, we’re delivering a new level of money intelligence that’s both powerful and effortless. It’s not just an assistant; it’s a co-pilot that elevates everyday life, making financial management as easy and natural as sending a text. Crucially, Revolut customers also remain firmly in the driver’s seat, ensuring that money intelligence never comes at the cost of privacy." The AI assistant's key highlights, according to Revolut, are customers gaining instant spending insights, tracking investments or freezing a lost card through a simple prompt; making travel easier, such as helping with trip budgets; and strong privacy controls, which means personal information is never stored by third-party AI partners or used for training external AI models. Many fintechs and neobanks are using or experimenting with generative AI tech.  Across Europe, Klarna uses it for customer service purposes, while Bunq launched its AI assistant in 2024. Danish challenger Lunar says its GenAI-powered voice assistant will handle around 75 per cent of customer calls over time. Last month, rival UK challenger bank Starling launched what it said is the “UK’s first agentic AI financial assistant”, as it looks to leverage the new technology to help improve day-to-day banking.

Ukraine’s tech ecosystem in 2025 appears top-heavy and driven by a single outlier, rather than broad-based capital inflows. Total funding reached €945 million, largely driven by a single deal, Grammarly’s $1 billion financing, which pushed the country into the top 10 by total capital raised. However, this headline figure masks a much smaller underlying funding base. Beyond this outlier, the ecosystem is characterised by numerous small, early-stage rounds, typically below €10 million. Funding activity is concentrated in pre-seed, seed, and Series A stages, with occasional alternative structures such as debt financing, indicating a developing ecosystem with limited late-stage depth. From an industry perspective, there is a strong presence of defence, security, and robotics, alongside software, AI, and healthtech, highlighting a dual focus on deeptech and scalable digital products. Overall, the data points to a resilient but uneven ecosystem - a broad and active early-stage pipeline, increasing specialisation in defence and security, but continued reliance on a small number of large, globally scaled companies to drive total funding volumes (for more detailed analyses of the European technology ecosystem, check out Tech.eu’s annual report: European Tech 2025 - The Big Picture). Here are the 10 companies that raised the most in 2025. Amount raised in 2025: $1B Founded in 2009 in Ukraine, Grammarly offers an AI-powered writing assistant that helps users improve clarity, correctness, and tone across documents, emails, and messages, with tools for grammar, spelling, style, and communication enhancement used by individuals and teams. Grammarly has raised $1 billion in financing to scale sales and marketing and for strategic acquisitions to grow its customer base and extend the reach of its AI productivity platform. Amount raised in 2025: €15.2M Reface is a Ukrainian AI company developing consumer applications for content creation, using generative AI to enable users to create and transform images and videos through features such as face swapping, animation, and style transfer. Its platform powers a portfolio of mobile and web apps used by millions globally, designed to make advanced creative tools accessible for entertainment, social media, and digital expression. In 2025, Reface secured €15.2 million in non-dilutive funding to support user acquisition and drive growth of its AI-powered consumer apps. Amount raised in 2025: €13.1M Swarmer is a defence technology company developing AI-powered software that enables large numbers of drones and unmanned systems to operate autonomously and coordinate as a single swarm. Its platform allows a single operator to control and manage complex multi-drone missions in real time, using collaborative autonomy and advanced navigation to operate effectively even in contested or GPS-denied environments. Swarmer raised €13.1 million over two rounds in 2025, to scale operations and enhance coordination capabilities for autonomous unmanned systems across Ukraine and NATO markets. Amount raised in 2025: $9M Liki24 is a Ukraine-founded health and wellness marketplace that connects consumers with pharmacies, drugstores, and health product suppliers across Europe through a single platform. Its AI-driven logistics system aggregates products from multiple sellers, allowing users to compare prices, access cross-border offers, and receive consolidated deliveries of medicines, supplements, and personal care products. In 2025, Liki24 raised $9 million in a Series A round to support its expansion across Europe and scale its health marketplace and delivery solutions. Amount raised in 2025: $5.4M PeopleForce is a cloud-based HR software platform that helps companies manage the entire employee lifecycle, including recruitment, onboarding, performance, and engagement, through a single, integrated system. Its modular SaaS solution automates workflows, centralises HR data, and enables organisations to streamline operations and scale people management more efficiently. In 2025, PeopleForce raised $5.4 million in a pre-Series A funding round to further expand in Poland. Amount raised in 2025: €2.5M Himera is a Ukrainian defence technology company developing secure, electronic warfare-resistant communication systems for military and emergency use, designed to operate reliably in complex combat environments. Its products include tactical radios and networked communication platforms that enable encrypted voice and data transmission, supporting coordination and situational awareness for frontline units and critical infrastructure operations. In 2025, Himera raised around €2.5 million over two rounds for the development of secure communications. Amount raised in 2025: €2.4M Dropla Tech is a Danish-Ukrainian defence and robotics company developing AI-powered systems for detecting landmines, unexploded ordnance, and other battlefield threats using drones, sensor fusion, and autonomous platforms. Its technology combines real-time data analysis, multi-sensor mapping, and autonomous vehicles to support military operations and humanitarian demining, aiming to improve safety, speed, and efficiency in clearing hazardous areas. In 2025, Dropla Tech raised €2.4 million in a pre-seed round to accelerate production and deployment of its edge AI systems for detecting explosive threats and enhancing force protection. Amount raised in 2025: €2.4M M-FLY is a Ukrainian defence and aerospace technology company developing advanced electro-optical systems and laser guidance solutions for unmanned aerial and robotic platforms. Its products enable accurate imaging, tracking, and navigation in contested environments, supporting both military operations and dual-use applications such as surveillance and geospatial analysis. In 2025, M-Fly secured €2.4 million across two funding rounds to support the development of defence technologies. Amount raised in 2025: $1.6M LetsData is a Ukrainian-founded cybersecurity company that develops AI-powered tools to detect and counter information operations, including disinformation and coordinated influence campaigns, across media and social platforms in real time. Its platform scans millions of data sources to identify early signals of manipulation, providing actionable intelligence to governments and enterprises to protect against reputational, operational, and security risks. In 2025, LetsData raised $1.6 million in a pre-seed round to enhance its AI-driven platforms and expand tools for detecting and countering disinformation. Amount raised in 2025: $1.5M Teletactica is a defence technology company developing advanced, electronic warfare-resistant communication systems for unmanned and autonomous platforms. Its hardware (including video and telemetry modems and ruggedised antennas) is designed to maintain secure, reliable connectivity in GPS-denied and high-interference environments, supporting military, industrial, and government operations. Teletactica secured $1.5 million investment for jamming-resistant communication systems for contested environments.

European tech activity in March 2026 eased slightly compared to February, while overall market conditions remained stable. The ecosystem recorded 292 funding deals and €7.5 billion raised, down marginally from 296 deals and €7.8 billion in February, reflecting declines of 1.4 per cent and 3.8 per cent respectively. At the country level, a more significant shift was observed. UK funding fell to €2.6 billion from €3.8 billion in February, a 31.6 per cent decrease, indicating lower capital concentration month-on-month. Sector trends also evolved, with AI leading in March at €1.8 billion, compared to transportation in February at €1.5 billion, signalling a rotation of capital toward artificial intelligence and related technologies. Tech.eu’s Cate Lawrence commented on the March numbers within the European tech investment landscape in our March Tech.eu Pulse, a compact version of the monthly report: European tech in March 2026 looked less like a market pulling back and more like one settling into a new rhythm. AI (albeit ubiquitous across sectors) attracted €1.8 billion and is overtaking other sectors as the primary destination for capital. At the same time, large rounds continue to account for a disproportionate share of total funding, pointing to sustained conviction in companies building core infrastructure, from compute to platforms that underpin entire industries. There are also some notable geographic shifts. The UK remains the dominant market despite a sharp drop in funding, while France, Sweden, Germany, and the Netherlands continue to form the backbone of European dealmaking. Beyond these, a broader mix of countries is starting to appear more consistently, suggesting the ecosystem is widening rather than further concentrating. For her more detailed review and more in-depth analyses of the European tech ecosystem, including industry and country performance, exit activities, and more, check out our March report. Here are the 10 largest tech deals in Europe from March, accounting for 62.7 per cent of the month’s total funding. Amount raised: $2B Nscale is a London-based AI infrastructure company that builds and operates vertically integrated GPU cloud platforms, combining data centres, high-performance computing, and software to enable large-scale AI model development, training, and deployment. It provides enterprises and governments with scalable, energy-efficient compute capacity and end-to-end tools designed to support the growing demands of advanced AI systems. In March, Nscale raised $2 billion in a Series C funding round, valuing the company at $14.6 billion. Amount raised: $1B AMI (Advanced Machine Intelligence) is a frontier AI research lab developing a new class of systems that understand and interact with the real world. It focuses on building “world models”, AI that can reason, plan, and operate safely across complex physical environments, with applications in areas such as robotics, healthcare, and industrial systems. Founded by a global team of leading researchers and engineers, the company aims to advance reliable, controllable AI and enable real-world intelligence beyond traditional language-based models. AMI raised more than $1 billion in what it describes as Europe’s largest-ever seed funding round. Amount raised: $830M Mistral AI is a Paris-based AI company founded in 2023 that develops high-performance, open-weight large language models and enterprise AI systems, enabling organisations to build, customise, and deploy advanced generative AI and autonomous agents. The company focuses on combining strong model performance with openness and efficiency, offering scalable AI solutions for both developers and large enterprises. Mistral secured $830 million in debt financing to acquire Nvidia chips for its initial data centre. Amount raised: $550M Legora is a Sweden-based legal AI company developing a collaborative workspace that helps lawyers automate tasks such as document review, research, and drafting, integrating both public and proprietary data to streamline legal workflows and improve productivity. The platform is designed to support legal professionals across law firms and in-house teams, enhancing efficiency while maintaining accuracy and control over complex legal processes. Legora raised $550 million in Series D at a $5.55 billion valuation to accelerate US expansion. Amount raised: $225M Kandou is a fabless semiconductor company that develops high-speed, energy-efficient chip-to-chip connectivity solutions used in advanced computing and data infrastructure. Its technology focuses on enabling scalable, cost-efficient AI and data centre systems by improving how processors, memory, and networks communicate, helping reduce power consumption while increasing performance. Kandou AI closed a $225 million Series A round to break memory bottlenecks in AI. Amount raised: €180M PLD Space is an aerospace company that designs, manufactures, and operates reusable rockets to provide reliable and cost-effective launch services for small satellites. Founded in 2011, the company develops its MIURA family of launch vehicles to enable flexible access to space, positioning itself as a key player in Europe’s emerging commercial space sector. PLD Space raised €180 million in Series C equity funding to scale satellite launch infrastructure. Amount raised: $170M 9fin is a fintech company that provides an AI-powered data and analytics platform for debt capital markets, combining real-time news, financial data, and predictive insights to help credit professionals analyse deals and make faster, more informed decisions. The platform is used by investment banks, asset managers, and law firms to streamline workflows and improve transparency across leveraged finance and credit markets. 9fin raised $170 million, reaching a $1.3 billion valuation. Amount raised: $150M Wonderful is an enterprise AI agent platform that enables organisations to build, deploy, and manage AI agents across customer-facing and internal workflows, helping integrate AI directly into core business operations. The platform provides a unified infrastructure for creating, monitoring, and optimising agents at scale, supporting complex, multilingual, and compliance-driven environments across global markets. Wonderful received a $150 million in a Series B funding round, reaching a valuation of $2 billion. Amount raised: €113.8M Iron Fuel Technology (developed by RIFT) is a cleantech energy solution that uses iron powder as a circular, carbon-free fuel to generate high-temperature heat for industrial processes and district heating. The system works like a rechargeable energy carrier: iron powder is burned to produce heat without CO₂ emissions, leaving iron oxide that is then regenerated using hydrogen and reused, enabling a closed-loop, scalable alternative to fossil fuels. RIFT has secured €113.8 million in combined financing (Series B and EU grant) to advance its Iron Fuel Technology from pilot projects to commercial deployment and to develop its first commercial production facility. Amount raised: $125M Upvest is a fintech infrastructure company that provides banks, brokers, and fintechs with a unified, API-based platform to build and scale investment products, including trading, custody, and back-office services. Its technology enables businesses to offer seamless, cross-border investment experiences, such as stock and ETF trading, savings plans, and fractional investing, while handling the underlying regulatory and operational complexity. Upvest secured a $125 million financing round to support the modernisation of legacy banking systems across Europe and the UK.

Handhold, an AI-agent platform that turns visitors into customers without sales reps, has raised €3 million Seed funding led by Entourage Capital, with participation from Inovia Capital and e2vc. Angel investors include: Markus Villig (founder of Bolt), Ott Kaukver (former CTO of Twilio), Harsh Sinha (CTO of Wise), and  Janer Gorohhov (founder of Veriff). Software buyers are more informed than ever and expect instant, personalised support. However, in reality, they often face unnecessary demo calls, generic onboarding flows and multiple handovers. When selling software, companies choose between product-led and sales-led motions. The choice comes down to setup complexity, product depth and price point. But when the factors don't align, neither approach works cleanly: product-led growth leads to low activation and high churn, while giving a dedicated sales rep to every SMB account isn't economically viable. Handhold automates the inbound customer journey, from first interaction to renewal, using AI account managers that qualify leads, run demos, and activate users around the clock. I spoke to Georg Vooglaid, co-founder and CEO of Handhold, to learn more. Why high-touch account management doesn’t work for most customers Originally from Estonia, Handhold co-founder and CEO Georg Vooglaid started his career at TransferWise, then moved to London to study and later joined Seedcamp. ​ But while advising founders, he realised he wanted operating experience of his own. He found it at identity verification company Passbase, where he worked across the revenue organisation as the business scaled across New York and Berlin. There, he built close relationships with the company’s largest clients and supported them from validation through retention and upsell. The model proved effective, but only for the top few accounts where the economics justified that level of personal attention. ​ He explained: “With our biggest client, I was available on WhatsApp 24/7. If we could’ve, we would’ve liked to give that level of attention to every customer, but there was no way we could afford to staff it.” ​ After leaving Passbase, Vooglaid reunited with his now co-founder to build a compensation benchmarking side project, which they later sold. ​ In May 2023, they launched what would become Handhold, initially as a conversation intelligence tool used by companies including Superhuman, Moss, and Katana. But after running into the limits of long sales cycles and relatively low pricing, they pivoted in late 2024. ​ The result was Handhold’s current product, shaped by customer feedback and his earlier experience. Turning every prospect into a managed account According to Vooglaid: “With AI agents, we can now replicate that one-to-one experience at scale because the economics work. You can give a ten-person startup a personal account manager that works around the clock, in any language, without actually growing headcount.” Each prospect or customer is assigned an AI account manager who validates use cases, runs demos, supports onboarding, and manages the relationship over time. From funnel to full lifecycle Handhold aims to manage the full customer lifecycle — from first website visit through activation, retention, and expansion. With Handhold’s agents taking care of advancing the top of the funnel and closing smaller clients, sales teams can fully focus on building relationships with mid-market and enterprise accounts. The buyer feels like they’re dealing with the same account manager, but behind the scenes, three agents actually split the work: ​ One handles text Q&A and lead qualification, Another runs voice demos tailored to the prospect, A third sits inside the product to tailor activation paths for new users. While you don’t have to use all three agents, context carries between them, and each following agent adapts to what the previous one has already discovered. Vooglaid explained: “We approach it from the customer journey. What does the user actually need at each step? If you have a quick question, text works best. If you want a deeper understanding, a demo agent works better. During onboarding, the agent might sit inside the product and guide you directly in the UI. From the user’s perspective, it’s always the same agent — in our case, “Holly” — but the form adapts to the context. The agent is there when needed and invisible when not.” Vooglaid contends, “If we can price based on the number of customers we manage end-to-end, that’s a strong signal that we’re delivering real value. It means we’re not just improving one part of the funnel, but actually driving outcomes across the entire journey.” This experience shaped his view on a broader problem: What human–AI interaction really looks like in practice I was interested in learning how people interact with AI agents. Vooglaid notes that people are initially very direct with agents — almost testing them. “Only once the agent proves itself does the interaction become more conversational.” Second, attention is critical. “You have five to ten seconds to engage someone — there are no social norms keeping them in the interaction. Third, active listening matters more than we expected. Giving users space to process and respond significantly improves the experience.” And finally, personalisation is powerful, but risky. He contends that good personalisation can close a deal, but if you get it wrong and make incorrect assumptions, it can completely break trust. Vooglaid explained that Handhold started at the top of the funnel — pre-sales, which enables the team to gather context early. “For example, if a user interacts with a Q&A agent first, that context carries into the demo. The demo is then tailored to what they’ve already asked. As we expand deeper into the journey, that context compounds. At the same time, users become familiar with the agent, which builds trust. So when the agent appears later inside the product, it doesn’t feel intrusive.” More agents, but one winner: the account manager layer ​ Agentic sales agents and tools are likely to become more commonplace, even with large players like Salesforce, which acquired Qualified. Vooglaid sees the real competitive battleground in building a persistent AI account manager that supports customers across the entire journey. “We’re particularly focused on SMB segments, where traditional sales models are harder to scale economically. That’s where this approach delivers the most value.” The core benefit for customers is conversion and efficiency. Vooglaid explained: “Some companies use us to handle inbound volume they can’t manage manually. Others use us for lower-priced segments where it doesn’t make sense to allocate a salesperson.” Handhold also sees strong demand from companies operating across time zones — the agent can handle traffic outside working hours. Ultimately, the goal is to convert more visitors into customers without compromising the experience. Where AI agents work today and gain the most traction Handhold soft-launched in September 2025 and grew to a strong six-figure ARR run rate by year-end. The platform is working with more than 15 customers, who are seeing strong early results. For instance, workforce management company Parim reported a 60 per cent reduction in bad-fit demos alongside double-digit month-over-month growth in sales-qualified leads since deploying Handhold. Vooglaid admits much of this is still trial and error. One advantage, however, is access to large volumes of sales call recordings and transcripts. “From those, we can extract best practices — how to handle objections, how to structure demos — and use that to improve the agent’s performance.” In terms of customer response, while people are already familiar with agentic Q&A and onboarding, the demo agent is more novel. Vooglaid admits that early on, there was concern around quality and whether the experience would feel polished enough. “We’re now seeing more success with 'reverse demos,' where customers experience the agent themselves first. Once they see it working well, they’re much more open to deploying it.” As for the hardest parts of the customer journey to get right, Vooglaid points to qualification and routing, detailing: “If companies position the agent as a core part of their brand experience, the quality bar is much higher." "They need it to perform really well. If the alternative is to enter new markets or cover gaps in availability, companies are more flexible. So a lot of this comes down to brand risk and how central the agent is to the customer experience.” From human sellers to hybrid sales models As for job displacement, Vooglaid asserts that Handhold is not directly replacing roles today. Instead, he sees that companies want their sales teams focused on mid-market and enterprise customers. “We help handle the lower-value segment more efficiently. For example, one UK customer reduced low-quality demo bookings by 60 per cent. That didn’t reduce headcount — it allowed their team to focus on higher-value opportunities.” Looking ahead, Vooglaid believes tools like his are fundamentally changing how software is bought and sold. AI enables more personalised, scalable interactions, which opens up new business models. It also shortens the sales cycle. “We may even move toward a world where agents are buying software on behalf of users, or where some purchases become nearly instant. Exactly how this evolves is still unclear, but the direction is toward faster, more efficient buying.” Handhold is already exploring use cases beyond SaaS, with clear applications across many industries. For example, the startup is piloting with a telecom company the use of agents to guide users through installing a Wi-Fi router. You scan a QR code, and the agent walks you through the setup step by step. According to Pieterjan Bouten, Partner at Entourage Capital, AI agents are fundamentally changing how we buy software. “From enabling new motions to becoming buyers themselves, Georg and Uku are building a system that opens up completely new business models and helps companies validate what’s working about their sales motion and what their customers need. The early traction is a sign that they're on to something, and we’re excited to help them redefine how software gets sold in the future.” The funding will accelerate go-to-market efforts and expand Handhold’s ability to move from converting leads to managing entire customer bases.

Verne today announced the launch of Europe’s first commercial robotaxi service, starting in Zagreb, Croatia. Beginning today, members of the public can now book and pay for a Pony.ai-powered autonomous ride through the Verne app. The service will soon also be available through the Uber app, following a recently announced strategic partnership between the three companies. The commercial service is the result of several years of development and close collaboration with regulators, positioning Verne among the leaders of autonomous mobility in Europe. “For the first time in Europe, there is a real commercial robotaxi service. People can use it and take real autonomous rides,” said Marko Pejković, co-founder and CEO of Verne. “We said we would launch in Zagreb in 2026. Today, we did. This is just the start.” Start of service in Zagreb The initial commercial deployment will use electric vehicles equipped with Pony.ai’s seventh-generation autonomous driving system. These vehicles ​will ​operate autonomously, with trained autonomous vehicle operators onboard during the early phase of the rollout. The initial service zone covers key districts of the Croatian capital, with plans to expand coverage across the city. The companies aim to transition to fully driverless operations as soon as possible, subject to regulatory approvals and the service meeting the required safety and reliability standards. From Zagreb and beyond Verne has begun permitting discussions with 11 cities across the EU, UK, and the Middle East, with more than 30 additional cities currently under consideration. Verne​​ ​​ will also eventually deploy the company’s purpose-built autonomous vehicle, a two-seat robotaxi designed specifically for driverless ride-hailing. From EasyMile to Einride, and now Verne: Europe’s autonomy stack evolves Image: EasyMile. Verne marks a shift from earlier paths to vehicle autonomy in Europe. Until now, one of the region’s most prominent players has been the French company EasyMile, which was the first to offer a fully driverless L4 autonomous shuttle, the 12-seater EZ10, across locations such as business parks, campuses, and commercial roads. EasyMile operates throughout Europe, including autonomous shuttles operational on public roads in Bad Birnbach, Monheim am Rhein, and Munich in Germany, as well as Toulouse, France. Earlier this year, the company announced a strategic pivot to heavy-duty applications for airports and industrial sites. The company is focusing on software licences for these markets, where it considers autonomy is commercially viable today, with growing deployments and a clear path to scale for heavy-duty vehicles that transport parts, goods, baggage, cargo etc. on airports and industrial sites. In parallel, German autonomous trucking company Fernride develops human-supervised autonomous trucking systems used in container terminals, industrial yards and defence logistics, retrofitting existing vehicles with AI, sensors and software to automate repetitive transport tasks. Its technology has already been deployed in real-world operations and, in 2025, it became the first company to receive TÜV approval for autonomous trucks in Europe. The company was acquired by Quantum Systems in late 2025 as part of a broader push to build a multi-domain autonomy stack spanning air and ground systems. Image: Einride. Meanwhile, Swedish-founded Einride deploys electric fleets and its driverless “Pod” vehicles, which can operate autonomously or be remotely controlled by human operators when needed. Alongside its hardware, the company runs a digital platform that plans routes, manages charging, and optimises deliveries, positioning itself less as a truck manufacturer and more as a software-driven freight operator. Already working with companies like Maersk and Oatly, Einride is part of a broader shift toward cleaner, more automated, and data-driven supply chains. In September last year, Einride completed the first successful European cross-border operation of a cableless electric autonomous vehicle without a human driver onboard. Against these efforts, in January, US company Waymo announced its intention to launch a fully driverless ride-hailing service in London by the fourth quarter of 2026. The company will soon begin conducting extensive trials of Waymo’s technology as part of our mapping and safety validation work across select boroughs in London. Testing hours typically run 24 hours a day, 7 days a week, to ensure its technology can safely handle all of London’s road conditions. Teledriving as an alternative path In commercial passenger transport, Estonia’s Elmo and Germany-founded Vay pioneered a different approach to vehicle automation, using teledriving to bring vehicles to users before switching to manual control for the trip itself. Using an app, users can request the delivery of an electric vehicle to their location. After the car arrives, the user takes over and drives it like a regular car.  At the end of the trip, the user ends the rental in the app, exits the car, and a remote driver takes over, eliminating the time-consuming search for parking.  Combined, these approaches highlight a fragmented but interconnected approach to vehicle automation in European mobility, which straddles controlled environments and industrial use cases against complex urban settings.

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Eilla AI has completed Europe’s first M&A deal executed by an AI-native advisory firm, advising on the acquisition of two Central and Eastern European digital marketing agencies, CreateX and Native Digital, by Swedish listed company White Pearl Technology Group. Its proprietary technology, built in-house over three years, combines AI infrastructure with experienced M&A advisors who oversee AI-generated work, manage transaction processes, and coordinate communication between both sides. I spoke to Petar Petrov, Chief Commercial Officer and co-founder of Eilla AI, to learn more. A shift driven by a lagging industry and an underserved market Eilla AI was founded in 2022. Initially, it was selling AI tools to the M&A industry. Over the past year its spoken to more than a thousand M&A firms and private equity funds. According to Petrov, two things became clear. First, the M&A industry is quite behind in terms of AI adoption — “even large boutiques were only just integrating tools like ChatGPT internally,” he shared. Second, the SMB segment is underserved. The team decided to combine the AI it has built with the expertise of experienced advisors. According to Petrov: “We partnered with our Head of M&A, Dmitry, a senior investment banker with over 13 years of experience at firms like Jefferies and Citibank.” Eilla AI’s customer is typically the founder or owner of an SMB business looking to sell.  What “AI-native advisory” means in practice Eilla AI’s technology enables it to reach hundreds of high-fit buyers across multiple countries within days, each with messaging built on in-depth research into what makes the acquisition compelling for that specific buyer.  Eilla AI runs a structured process similar to what top-tier investment banks use, but applied to the SMB market. The AI handles large parts of the workflow, but humans step in where full automation isn’t yet reliable — especially for customisation and judgement. First is preparation. It identifies a broad universe of potential buyers — often larger in SMB deals, where smaller companies attract a wider range of acquirers. “We use AI to identify these buyers. Eilla has built a large proprietary database with detailed information on companies, and uses AI to identify the right buyers from that database based on similar deals and synergies,” explained Petrov. Eilla uses its AI automations to build key materials, including the confidential information memorandum (CIM), the core document used to present the business to potential buyers.  “Traditionally, this process can take one to two months. We can do it in a few days.” Next is outreach. While the company utilises its existing relationships, it also deploys highly personalised outreach to new buyers. It built a database of around nine million companies, tracking their products, tech, and other signals. This enables it to send highly tailored messages at scale, resulting in higher response rates. “The goal is to create competitive tension — ideally by arranging five to ten meetings,” explained Petrov. Buyers then submit non-binding offers, which are reviewed with the client before moving into due diligence. Due diligence is usually the longest stage — one to two months — and depends on multiple parties. Where AI stops, and judgment begins Petrov emphasised that humans remain in the loop, particularly in judgment-heavy tasks such as responding to buyers. While AI drafts outputs based on available data, all materials are reviewed by humans and given final approval. “These are judgment calls — what to include, what to emphasise. AI can assist, but humans make the final decision.” Eilla AI is already seeing early traction in both deal speed and buyer reach. One recent transaction moved from outreach to non-binding offers in around 15 days, with the full process completing within a few months — despite involving multiple companies, shareholders, and a non-obvious buyer. According to Petrov:  “It was a complex deal — multiple companies, multiple shareholders, and a buyer that wouldn’t normally be identified through traditional relationships.” Rather than relying on existing networks, the firm identified the buyer through pattern matching at speed against previous acquisitions, surfacing a publicly listed Swedish company that would likely have been missed in a traditional process. Nikola Lazarov, CEO and co-founder, contends that this pace and depth would be impossible to replicate without the infrastructure it has built.  “Our work with CreateX and Native Digital is not just proof of concept. It is a completed deal.” The founders of both acquired companies credited Eilla AI with making the transactions possible. “Honestly, without Eilla, this deal would not have happened,” said Aleksandar, founder and CEO of CreateX. The reaction from Native Digital was similar. Early traction across deal speed and buyer reach Adoption of AI in M&A is still in its early stages, particularly in a sector long defined by relationships and traditional processes. For Eilla AI, client response tends to fall into two distinct categories, according to Petrov. The majority of its clients come through its automated sourcing using AI rather than referral.  “They typically need to see the technology — once they do, the reaction is generally very positive.” Some clients come through referrals and already understand the process.  “For them, we demonstrate how we’re different.“ While M&A remains relationship-driven, Petrov argues that this model has clear limitations, particularly in the lower and mid-market segments. “Relationships only take you so far. A typical advisor might know 10–20 relevant buyers. In SMB deals, the real buyer universe is much larger.” Instead of relying on a narrow pool of known acquirers, Eilla AI’s approach is designed to expand buyer discovery and increase competitive pressure within deals. “We focus on creating competitive tension, rather than running bilateral processes with just one buyer. That’s a key advantage.”  Eilla AI’s models are probabilistic, and the system does not rely on generic model outputs or training data alone. Instead, it works with structured context provided by the client, combined with data extracted from proprietary databases and licensed external sources — including a dataset built from tens of millions of scraped pages covering around nine million companies. Petrov explained: “Importantly, everything is reviewed by humans, and critical information is validated with the client. The goal is not to replace people, but to make one person as effective as a much larger team.” When software becomes the service Eilla AI’s model reflects a broader shift already underway in the US. Firms including General Catalyst, Founders Fund, Sequoia, a16z, YC, Blackstone and others have converged on a shared thesis: the next generation of category-defining companies won’t sell software to professional services firms — they will become them. Across legal, accounting, insurance and consulting, over a billion dollars has been deployed into companies that own the outcome rather than sell the tool. General Catalyst committed $1.5 billion to acquiring traditional service businesses and rebuilding them with AI. Sequoia and a16z co-led $108 million into Rillet, an AI-native accounting firm. Emergence Capital led a $47 million round into Harper, an AI-native insurance brokerage. Lawhive, an AI-native law firm, raised $60 million on the back of 7x year-on-year revenue growth.  Sequoia partner Julien Bek crystallised the thesis in a widely circulated essay earlier this month titled “Services: The New Software.” His core argument: for every dollar spent on software, six dollars are spent on services. He contends that the next trillion-dollar company, he wrote, will be a software company masquerading as a services firm. Scaling M&A for the long tail of businesses The deal executed by Eilla AI arrives at a moment of acute structural pressure on the European M&A market. The European Commission estimates that a third of EU entrepreneurs will exit their businesses over the coming decade, putting roughly seven million businesses and 30 million jobs at risk.  In Germany alone, 626,000 businesses plan to transfer ownership by 2027. Traditional boutique advisory firms cannot economically serve the vast majority of these transactions. A proper sell-side process requires hundreds of hours of work, and for deals below a certain size, the fees do not cover the cost of running that process properly. The result is a market where most business owners either cannot access quality advisory or receive a diminished version of it. Eilla AI’s cost structure is fundamentally different. Because AI handles the volume-intensive work, buyer sourcing, outreach and document creation, the firm operates on a success-fee-only basis with no retainers.  A model already proving out globally The pattern has a precedent. In Japan, Shunsaku Sagami built M&A Research Institute to address a similar succession crisis, using AI to compress deal timelines from over 12 months to an average of 6.2 months. The company is now publicly listed, and Sagami, at 33, became Japan’s youngest billionaire. In the United States, OffDeal raised $17 million to build an AI-native investment bank.  Eilla AI launched its advisory practice at the end of last year and now has around 20 active mandates, with a fee pipeline of approximately €20 million — up more than 15-fold from roughly €1.6 million at the start of the year. M&A advisory is inherently transactional, raising questions about how firms build sustainable businesses without recurring revenue. For Petrov, the answer lies in deal size, volume, and execution. Rather than relying on repeat subscriptions, the model is driven by the economics of individual transactions. “In our segment, average deal sizes are around €10–20 million, and we charge about a 5 per cent success fee. So a single deal might generate around €500,000.” Petrov argues that long-term strength comes not from recurring revenue, but from consistently generating and closing deals. “You don’t need recurring revenue to build a strong business — you need deal flow and execution.” AI plays a role not only in deal execution, but also in sourcing opportunities, while brand becomes increasingly important over time. Across its processes so far, Eilla AI reports that around 80 per cent of companies reach the stage of presenting to buyers, suggesting a higher level of early-stage engagement. “In one case, a company that previously secured one NDA with a traditional advisor reached nine NDAs using our process.” Although the M&A practice only launched at the end of last year, the company says momentum is building quickly as more deals move through the pipeline.  "We’re still early, but we’re already seeing strong momentum.”

A London-based startup which helps mitigate risks and vulnerabilities of businesses deploying so-called AI agents or AI tools that can complete specific tasks has emerged from stealth with a $13m seed round. The funding round in Trent AI was led by LocalGlobe and Cambridge Innovation Capital, with participation from leaders at OpenAI, Spotify, Databricks, and Amazon Web Services. The startup, founded in 2025, is tapping into the current trend of AI agent deployment, claiming its product is the first multi-agent security solution designed to secure agents as they evolve. AI agents and autonomous workflows introduce new security risks that traditional security tools were not designed to address, it says. Trent AI says its product secures AI agents with specialised AI security agents that continuously scan environments, judge risk, mitigate vulnerabilities, and evaluate overall security. The startup was founded by Eno Thereska (CEO), Neil Lawrence (chief scientist), and Zhenwen Dai (CTO), who are former Amazon/AWS and Spotify engineering leaders hailing from academia and research. Thereska said: “Organisations are deploying AI agents and autonomous workflows faster than their security can adapt, and most development teams using these agents and workflows have no security framework designed for their systems. “This is not an easy problem to solve. Trent AI is tackling these difficult and important problems, while building the necessary security foundations and frameworks for agentic systems now and through the next decade.” The startup pointed to Deloitte research showing nearly three in four (74 per cent) companies plan to deploy agentic AI within two years, but that only one in five (21 per cent) report having a mature model for governance of autonomous agents. Its product is built for developers and security teams that want to develop and ship agents fast without compromising security, it says. Companies with early access to its product include Canopy and Weblogic. Trent AI said: “These partners have reported: immediate visibility into their security posture, a security audit report, fast response time identifying and presenting vulnerabilities, a clean and well laid out remediation scope and adaptive feedback.” The seed funding will support continued development of Trent AI’s security agents, expansion of the engineering team and growth of the company’s design partner and customer bases, it said.

UK-based analytics startup WholeSum has brought its total Pre-Seed funding to $1.3 million, with an additional $335,000 new investment from Love Ventures, Beamline, and strategic angels, following its initial $965k raise led by Twin Path Ventures announced earlier this year. The round comes amid growing demand from enterprises in high-trust sectors, where organisations are increasingly finding that existing AI tools fail to deliver reliable, auditable insight from large volumes of text data. While most organisational data is unstructured, teams continue to struggle to analyse it at scale. In practice, many have turned to LLMs, only to encounter hallucinations, inconsistencies, and outputs that cannot be reproduced or defended – particularly in regulated environments such as healthcare, financial services, and defence. Founded by Emily Kucharski and Dr Adam Kucharski, WholeSum was born out of the founders’ frustration with existing AI tools while analysing large-scale qualitative datasets in a previous venture. The experience highlighted a systemic problem: organisations want to extract meaningful insight from qualitative data, but lack tools that are both scalable and scientifically defensible. “From talking to dozens of large organisations making high-stakes decisions, we’ve seen a clear pattern: teams are experimenting with AI for text analysis, but quickly hit a wall when outputs can’t be trusted or reproduced,” said Emily Kucharski, cofounder and CEO of WholeSum. “This funding allows us to move faster in building infrastructure for robust analysis at scale.” WholeSum addresses this gap with a hybrid AI and statistical inference platform that converts free-text data into uncertainty-aware, reproducible, and auditable insight. Designed as an API-first infrastructure layer, it integrates directly into existing analytics workflows, enabling organisations to extract nuanced signals and underlying drivers with the same rigour as numerical data. Since its initial raise, WholeSum has seen strong traction across enterprise organisations in high-trust sectors. Early work with universities, financial institutions and pharmaceutical companies has demonstrated that the most valuable early signals are often buried in unstructured text data rather than in lagged quantitative metrics. “Generic LLMs can’t deliver the consistent, reliable signals that high-trust industries need from unstructured data,” said Bill Corfield, Principal at Love Ventures.  “Emily and Adam are uniquely positioned to solve this, and we're delighted to be backing them as they scale across Pharmaceuticals, Financial Services and beyond.” The company is now rolling out pilots and enterprise integration for increasingly complex, large-scale datasets. The additional funding will be used for R&D, expanding the company’s world-class scientific and engineering teams, and scale enterprise deployments in sectors where methodological rigour is critical.

“All of us live in the dark most of the year, and we don’t have anything better to do than build,” says an organiser of one of a new wave of hacker houses which have cropped up in recent months across Scandinavia and the Baltics. This resurgence in hacker houses can be seen all across Europe. But across Scandinavia and the Baltics, the hacker house mentality, the esprit de corps, is particularly acute, given the relative smallness of the markets. Amid waning deal flow, particularly across the Baltics, investors see them as a quick-fire win to turbo-charge investment, while builders view them as a chance to showcase their talents. Latvia-based Shipyard, Estonia’s ruum, Lithuania’s Basedspace and Denmark-based Bifrost House are examples of the new breed to emerge. Hacker houses became popular in the early 2000s, particularly in Silicon Valley and the San Francisco Bay Area startup ecosystem- in response to rising housing costs and the need for collaborative startup environments. They are now enjoying a resurgence, with a more explicit hacker house/ builder lab format. ruum Tallinn-based ruum is one of the new crop of hacker houses which launched last year. Helery Pops, ruum founder who is also a VC and angel investor, says ruum took inspiration from Basedspace, a neighbouring hacker space in Lithuania. Pops said: “When we started looking into it, it was like an avenue of green flags everywhere. There was really no reason not to do it.” The idea was to give free working space to builders just starting out in their careers, she says. Central to ruum's hacker house programme was a full-day hackathon, with 12 teams selected from 110 applicants, with the resulting progamme running for two and a half months. Pops said: “There have been many hackathons, there have been many accelerators, there are some that are still on-going in Estonia. But at this point, it seemed that the deal flow was not coming on as it had been maybe in the last five years. There was space for something new. People are seeing there is a problem with the early-stage companies. This just seems like a possibility to solve a little bit of it.” The programme was supported by €20,000 in funding, which came from Skaala, the family office of Skype alumni and Wise cofounder Taavet Hinrikus and his Skype colleague Sten Tamkiv, Startup Estonia, and a few angel investors.   The broader Estonian tech community helped out by offering their services for free. The winners, Bilt.me (a "Lovable" for mobile apps), a six-strong team with an average age of 21, were whisked off for a week in San Francisco. Pops says: “They work six days a week. If you are in the working space with them, and you start going home at 5pm, they are generally shocked. It is very cool to see how much energy and power they are putting into it.” Ruum might have started out as a hobby, but Pops said the future could see more programmes, with a slightly amended format. Shipyard Meanwhile, across the Baltics, in Latvia, another newish hacker house space is the AI-centred Shipyard. According to one of Shipyard’s founders, Marija Rucevska, who is also GP at a VC investing in the Baltics, Shipyard was created recognising the impact of AI on startups. Rucevska said: “This new movement is acknowledging that you can move a lot faster to market and understand if it’s worth building something longer term or maybe just something that you are building for yourself.” Like ruum, Shipyard’s admission programme was a 48-hour hackathon, with the programme then taking on 20 teams over three months, which is then whittled down further to a group of eight teams looking to get pre-seed funding. Part of the programme, designed to turn builders into founders who are building AI-native teams, demanded builders deliver weekly shipping cycles. “If you don’t deliver, you are out,” she says. She adds: “We want to cherish and nurture the building, energy and spirit and also witness some of those of new AI native founders.” Shipyard also helps Rucevska tap into her VC pipeline efforts, she said. She says: “We have really technically brilliant people here, a lot of very AI-savvy teams applying different types of tools.” On the broader emergence of hacker houses across the Baltics, she said: “That kind of comes from the fact that all of us live in the dark most of the year and we don’t have anything better to do than build.” She says the Baltics are also “very ecosystem driven” given the relative smallness of the countries, which means that individual countries are always rooting for each other. Bifrost House In Scandinavia, there is Copenhagen-based Bifrost House, which bills itself as “Copenhagen’s most ambitious startup community and co-working space”. It is a venture studio that builds startups from the ground up, with a hacker house mentality. Bifrost House raises capital, forms founding teams, and operates businesses across sectors, including defence technology, consumer goods, B2B SaaS, and financial data.  It is currently raising a €30m fund and has hitherto built 25 startups, with a mission to build 100 companies a year. Sophus Blom-Hanssen, who runs the operation, said there is nothing like Bifrost House in Europe, given the scale of its ambitions. He says: “The reason we are doing it, and the reason a lot of these type of spaces will emerge is that the whole modus operandi of a startup, of getting a startup to market quickly, that timeframe is compressing super-quickly. Both to build a product and the timeframe you are relevant in the market is also compressing.” On its fund, he said: "We look at what does the business case we are scoping around require from a funding perspective? And work together with the founder and entrepreneur to structure a cap table that works to actually reach the first or second milestone so that the business can raise more money." IMAGE: Bifrost House

Xoople, the data infrastructure company building a global system of record for physical change on Earth, has closed a $130 million Series B round. The round included investors such as Nazca Capital, MCH, CDTI (Government of Spain), Buenavista Equity Partners, and Endeavor Catalyst, bringing the company’s total funding to $225 million. Founded in 2019, Xoople has spent the past seven years developing its end-to-end system in stealth while building global partnerships to integrate its data into enterprise tools. The investment positions the company as one of the most well-capitalised players in its category, supported by a proprietary satellite-based system capable of generating high-precision, scientific-grade datasets. Xoople is now entering its commercial phase, with rollout beginning this quarter. As AI systems increasingly shift toward autonomous, agent-driven workflows, demand for reliable real-world data is expected to grow. Xoople’s platform provides this “ground-truth” layer, enabling applications across supply chain optimisation, infrastructure monitoring, insurance risk modelling, disaster response, and geopolitical analysis. The company refers to this infrastructure as the “Earth’s System of Record,” designed to connect digital systems with real-time physical-world intelligence. Every major computing era creates a new system of record; those that define that system become the economic centers of that era. CRMs gave companies a system of record for customers. Cloud platforms create systems of record for software and data. We are building the system of record for the physical world in the AI era with Xoople. After seven years developing our system in stealth, we are incredibly excited to begin commercialisation in Q2 and start scaling up that capability in the market, said Fabrizio Pirondini, CEO of Xoople. Early users include government agencies and Fortune 500 companies applying the platform to areas such as agricultural forecasting, urban planning, and scenario modelling. Xoople’s mission is to provide organisations with access to real-time physical-world intelligence, supporting the next generation of AI systems.

nFuse, an AI-powered B2B ordering platform that enables retailers and HoReCa operators to place orders through WhatsApp, Viber, and SMS using text, voice, or images, has raised $2 million in funding from Eleven Ventures and LAUNCHub. For the past decade, every major FMCG company has had the same idea: build a B2B eCommerce platform, get retailers to download it, and watch orders roll in digitally. The results have been almost universally disappointing. Adoption rates for B2B ordering apps in fragmented trade hover around 15 per cent. Implementation timelines stretch to 18 months. And the retailers these platforms were built to serve — millions of small shops, kiosks, and independent stores across emerging markets — largely ignore them. The lived experience that led to nFuse Stoyan Ivanov and Stefan Radov watched this pattern repeat for nearly 30 years combined at Coca-Cola, working across distribution, sales, and go-to-market operations. They didn't learn about fragmented trade from market research - they lived it, visiting thousands of small retailers and watching firsthand as digital initiatives repeatedly failed to gain traction. "We were the people being asked to make these B2B platforms work," Radov explains. "We sat in the meetings where adoption targets kept getting missed. We saw the gap between what headquarters wanted and what actually happened in the field. Eventually, we decided to build what we wished had existed." The digital gap in fragmented trade Fragmented trade - the network of independent retailers, small shops, and kiosks that dominate commerce in emerging markets - represents over $5 trillion in global value. And in regions like CESEE, Latin America, Africa, and Southeast Asia, these outlets account for the majority of FMCG sales. They're not a niche. They're the market. Yet the industry's approach to digitising this channel has been remarkably consistent: build sophisticated B2B portals with product catalogues, order management, and analytics dashboards. Train sales reps to onboard retailers and wait for adoption. The waiting tends to last a while. "The fundamental assumption was wrong," says Stoyan Ivanov, nFuse co-founder and CEO. "The industry built and designed eB2B for headquarters - for the people who wanted dashboards and data. Not for the retailer standing behind a counter who just needs to reorder beer before the weekend rush." Industry analysts estimate 80–95 per cent of B2B eCommerce projects underperform or fail outright. The platforms work technically. They just don't work behaviourally. nFuse builds on how retailers actually communicate Ivanov and Radov’s insight came from watching what retailers actually did, not what platforms wanted them to do.  Across emerging markets, small retailers were already running their businesses through messaging apps — sending photos of empty shelves, handwritten notes on Viber or voice-messaging orders because typing was slower. nFuse is built on this observation. Retailers place orders via WhatsApp, Viber, or SMS using text, voice, or photos. No app to download, no login to remember, no interface to learn. A photo of an empty shelf becomes a confirmed order in seconds. “These retailers aren’t technology-averse,” says Stefan Radov, co-founder and COO.  "They're using technology constantly. Just not the technology we kept trying to give them. They don't want another app. They want to order the same way they message their family." nFuse hits 70 per cent where B2B platforms stall The numbers back the approach: while traditional B2B platforms struggle to reach 10–15 per cent adoption, nFuse reports 70 per cent+ adoption among enterprise clients. Revenue per outlet increases 15–30 per cent. Deployment takes eight weeks - not eighteen months. The economics shift too. Traditional B2B ordering - whether through sales reps, call centres, or underused portals - carries a high cost per transaction. nFuse drives cost per order targeting below $1, a 5x to 20x reduction that fundamentally changes the math on serving small, frequent-ordering retailers that were previously too expensive to reach efficiently. Early clients report ordering frequency jumping from monthly to weekly cycles. Retailers who previously waited for a sales rep visit now reorder whenever they need stock. For brands, this means increased volume, a direct channel to push more SKUs - including new launches - and faster feedback on what's moving. Outlets themselves are choosing nFuse as their primary ordering channel over portals, call centres, or waiting for a rep. The company is already working with category leaders across beverages, dairy, pet food, and wholesale distribution - validating the model across FMCG verticals, not just one category. According to Ivaylo Simov, Partner, Eleven Ventures, Stoyan and Stefan know the FMCG industry inside out and have set out an ambitious task to solve the broken model of B2B e-commerce solutions.  “Instead of asking retailers to change their behaviour, the advancements in AI have opened a new frontier of intelligent solutions that "speak" their language via the channels they usually use. This unlocks enormous opportunities for brands, as the tail of the market (i.e. all the fragmented hotels, small shops and restaurants) can now be served efficiently and at scale."   Rumen Iliev, Partner, LAUNCHub Ventures, shared that the B2B eCommerce graveyard is full of platforms that worked technically but failed commercially.  “Most portals force unnatural behaviour — buyers do not want to click through SKUs and quantities. nFuse makes ordering natural again via voice, text, or image, just like speaking or texting to a sales rep. With 30 years in distribution, the founders have seen exactly where adoption fails. We backed the insight as much as the product.”   The funding will accelerate nFuse's expansion across Europe, with plans to move into broader EMEA and American markets. But Ivanov sees the self-ordering flow as just the entry point. "Self-ordering is where we start because it's the most obvious pain point," he says. "But once you're the channel through which orders flow, you become the infrastructure for the entire relationship between brands and retailers. Trade marketing, promotions, inventory visibility, loyalty programs — it all runs through the same conversation." With the core model proven, nFuse sees payments and micro-lending as the next unlock: letting retailers pay through the same WhatsApp thread where they order, collapsing an entire workflow into one conversation. It's the same thesis applied to a bigger problem. Not "how do we build better apps?" but "how do we stop asking people to install them?" "The industry spent a decade trying to get retailers to come to us," says Ivanov. "We're just going to where they already are."