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General Intuition, a New York and Geneva-based AI startup has raised approximately €114 million in a Seed funding round – making it one of 2025’s largest early-stage investments in AI.
The round was led by Khosla Ventures and General Catalyst, with participation from Raine.
“This next frontier in AI requires large scale interaction data, but is severely data constrained. Meanwhile, nearly 1 billion videos are posted to Medal each year. Each of them represents the conclusion of a series of actions and events that players find unique – across tens of thousands of environments. The only other platform of comparable upload scale is YouTube,” said Pim de Witte, CEO and Co-founder.
By comparison, most European startups working in embodied AI, agentic systems, or robotics have raised significantly smaller amounts.
For instance, Energy Robotics (Germany) secured €11.5 million in a Series A round to advance its autonomous robot and drone inspection software. Similarly, Unchained Robotics (Germany) raised €8.5 million in an extended Series A to make industrial automation more accessible.
In Southern Europe, Cyberwave (Italy) closed a €7 million early-stage round to build a connective operating layer linking AI agents with real-world machines and sensors. Meanwhile, Omnia (Spain) raised €3.5 million in pre-Seed funding for its agentic AI platform aimed at helping brands interact with AI systems.
Against this backdrop, General Intuition’s Seed funding far exceeds typical European deal sizes in adjacent sectors.
While most 2025 AI and robotics rounds reported by EU-Startups have ranged between €3 million and €12 million, General Intuition’s raise underscores a sharp contrast in both scale and ambition – particularly notable given its early stage and cross-continental structure spanning New York and Geneva.
“When you play video games, you essentially transfer your perception, usually through a first-person view of the camera, to different environments,” added de Witte. “You get this selection bias towards precisely the kind of data you actually want to use for training work.”
Founded in 2025 as a spin-off from the Dutch video platform Medal, General Intuition emerged from Medal’s extensive user base and content pool, which includes over 2 billion gameplay clips annually from 10 million monthly active users. Unlike typical AI startups that rely on curated training data, the company leverages organically uploaded content featuring dramatic successes and failures – ideal edge cases for training systems with spatial and temporal awareness.
It’s able to do this purely through visual input; agents only see what a human player would see, and they move through space by following controller inputs. This approach, the company says, can transfer naturally to physical systems like robotic arms, drones, and autonomous vehicles, which are often manipulated by humans using video game controllers.
The startup will use the funding to scale its research team and advance development of AI agents designed to perform in both virtual and real-world environments.
The company’s research targets include agentic systems capable of learning from unstructured video, world models that simulate dynamic environments for training, and video understanding that applies beyond gaming.
The company is structured as a public-benefit corporation and aims to enhance, not replace, creative roles in the gaming industry.
Commercially, it plans to launch AI-powered non-player characters (NPCs) and simulation tools by the first half of 2026. These NPCs are expected to offer a level of interactivity and adaptability that exceeds the capabilities of deterministic, rule-based bots.
General Intuition’s emphasis on embodied AI also has real-world applications, including search-and-rescue drones that can interpret and navigate unfamiliar terrains without relying on GPS.
This versatility stems from the startup’s belief that LLMs alone are insufficient for achieving artificial general intelligence (AGI), due to their lack of understanding of physical and spatial dynamics
The UK government is launching a “concierge” service designed to make the UK more appealing to overseas financial services investors.
The UK Treasury said its “one-stop shop” service will help global financial services firms pick locations, navigate regulation and “get to grips with Britain’s business environment”.
The service, which is free of charge, is a partnership between the Treasury, regulators and the City of London.
The move comes amid international investors bemoaning the absence of a dedicated UK resource, unlike in other countries, to help speed up investment in the UK.
Chancellor Rachel Reeves said: “We said we would make it easier to create jobs and grow a business in our country and we’re delivering. This service will drive investment across our United Kingdom, making sure that the world’s most innovative businesses can access the talent found in every corner of our country and that working people feel better off.”
Financial services employ 1.2 million people across the UK, with more than half of those jobs outside London.
The “concierge” service will draw on the strengths of the UK’s financial services clusters, such as Leeds, Liverpool, Belfast and Bristol, to promote investment opportunities and help deliver the infrastructure, the government said.
Chris Hayward, policy chairman of the City of London Corporation, said: "This marks a defining moment in the United Kingdom’s approach to foreign direct investment. Co-located in Westminster and the City of London, this important step moves us from ambition to action in less than six months.
"The service embodies the strength of public–private partnership, harnessing industry, government, and regulatory expertise to create a streamlined and fully integrated offer. It will make the UK the most attractive destination in the world for financial services.
"For investors worldwide, this represents an unparalleled opportunity to engage with a world-class ecosystem built for growth, innovation, and long-term success."
You know when you talk to an interviewee about transcribing interviewees and they admit they use AI to summarise notes from a meeting in archaic English, it's going to be a fun interview.
Dave Colwell, is VP of AI & ML at Tricentis. He also admits that some people he talks to at meetings “are very boring people. They always want an interview, and I’m like: “What are you going to talk about? Same thing as the last call.”
"So once, before anyone else joined, I set the transcript to be written in Shakespearean English. Everyone’s lines came out like “thou so-and-so.” It was hilarious. Prompt injection at its finest.”
He also recommends doing the same in gangster rap.
But speaking of AI, Tricentis provides a continuous testing platform designed to help large organisations automate and accelerate software testing as part of their DevOps and CI/CD pipelines. Its main goal is to help companies deliver software faster, with fewer defects, by replacing slow, manual testing with AI-powered, model-based, and low-code automation tools.
From testing software to testing AI itself
This week Tricentis unveiled its vision for the future of AI-powered quality engineering at Tricentis Transform, its flagship global event in London, marking a defining moment in how enterprises will build, test and deliver software in the AI era.
This announcement introduces a unified AI workspace and agentic ecosystem that brings together Tricentis’ portfolio of AI agents, Model Context Protocol (MCP) servers and AI platform services, creating a centralised hub for managing quality at the speed and scale of modern innovation.
Testing at the speed (and chaos) of AI
As software creation accelerates through generative AI, organisations face an exponential rise in both code volume and complexity. Traditional testing models can no longer keep pace. Tricentis’ vision reframes quality engineering as a strategic discipline powered by intelligent, autonomous systems where agents work alongside skilled professionals to ensure every release is faster, safer and more reliable. “We give enterprises the ability to test everything."
According to Dave Colwell, VP of AI & ML at Tricentis, the company began with automated testing, performance testing, and test management — essentially making testing easier to create and maintain.
“Today, we work with companies that run on incredibly complex technology stacks. Some of their systems were built in the 1970s, others were rolled out yesterday.
If any piece of that stack fails, customers feel the pain immediately. That’s where Tricentis comes in: we give enterprises the ability to test everything, across old and new technologies alike.”
Colwell likes to joke that “I’m an ‘AI hipster’ — I joined before large language models were even on the scene. “
His background is in computer vision and natural language processing, and he recounts that early on, Tricentis used computer vision models to analyse user interfaces and figure out how to test them organically, rather than mechanically.
“That was our first foray into applying AI to testing.
Over the past eight years, we’ve invested heavily in AI, with the main goal of reducing the human effort needed to build and maintain tests. Ideally, the tests build and maintain themselves. That’s the future we’re working toward.
The AI testing paradox: when ‘wrong’ isn’t a bug
I was curious, what makes testing AI solutions so difficult?
According to the 2025 Tricentis Quality Transformation Report, nearly two-thirds (63 per cent) of organisikju65ations deploy code without fully testing it, and over 8 in 10 (81 per cent) report financial impacts from software defects exceeding $500k annually.
As AI accelerates development and delivery, the need for adaptive, autonomous testing becomes critical.
Tricentis’ agentic AI technologies address this challenge directly, enabling systems that not only generate and execute tests but learn continuously from outcomes to enhance reliability and reduce risk over time.
Colwell detailed that the biggest challenge in AI is that a “wrong” response isn’t necessarily a bug — it’s just another data point. With traditional software, you fix a bug and it won’t reappear if fixed correctly. With AI, you can’t guarantee that:
“Take a customer-support chatbot as an example,” shared Colwell.
“During testing, someone might ask a question and the bot answers incorrectly. In a traditional workflow, testers would raise a bug. Suddenly you have thousands of “bugs” — but they’re not fixable in the usual sense because AI is probabilistic. It’s a big ball of math making guesses.”
When not to use AI
The first filter Tricentis teaches customers is: should you use AI at all? According to Colwell, if your use case can’t tolerate persistent error, then AI isn’t the right tool.
“In drug discovery or hiring, even a single mistake can have catastrophic consequences. By contrast, AI-generated code is a safer use case because humans review it, pipelines catch errors, and the system is designed with verification in mind.”
AI turns startups into giants
Tricentis’ customer base is primarily large enterprises with sprawling, complicated tech stacks and the most to lose when things go wrong.
They’re also the ones most anxious about being disrupted by nimble AI startups. Colwell argues that many large enterprises are intimidated by three-person startups.
“AI makes it possible for a tiny team to look like a big company almost overnight. We’ve seen billion-dollar organisations losing customers to these newcomers because the speed and polish of what they deliver is suddenly competitive.”
The problem for enterprises is that they’re weighed down by technical debt and legacy systems. They’ve never seen customers churn so quickly to younger competitors. Even though most AI startups won’t survive long-term, the disruption they cause is real.
“Vibe coding”: good idea, terrible name
And, of course, I wanted to get Colwell’s stake on vibe coding. He laughs that while it's a terrible name, the concept is real:
“We’ve run AI coding programs internally, and we’ve seen two very different outcomes. One engineer handed almost everything to the AI. He looked highly productive — shipping massive amounts of code.
But when we reviewed it, much of the code was low-quality, because he had surrendered too much control.
On the other hand, teams that built processes around AI coding — with feedback loops, documentation, and review — saw far better results.
They made the AI explain its reasoning, documented acceptance criteria, and looped back to check whether the outputs matched the original plan. That produced reliable outcomes.”
So the lesson is this: AI coding is about changing how you work — focusing on process, documentation, and validation. Colwell asserts:
“Done this way, it’s powerful, but done badly, it’s a disaster.”
The “stolen generation” of developers
I’m always interested in what AI means for young developers entering the workforce, especially in many cities in Europe where there are high unemployment rates for early-career roles.
According to Colwell, right now, we have a delicate balance.
"Younger engineers adapt quickly to new tools, but they don’t always recognize what “good” code looks like. Experienced engineers know quality, but can struggle to adapt to the new paradigm. Pairing the two creates strong outcomes.”
He believes that looking further ahead, we’ll flip the traditional learning path:
“Today, junior developers spend years learning by fixing bugs and writing small features before they’re trusted with design.
In the future, people may learn design patterns and architecture first, because AI will handle much of the low-level coding.
However, Colwell also raised concern about what he calls a “stolen generation” — developers trained on coding skills that AI makes less relevant, but who haven’t learned higher-level design thinking.
“They’ll need to re-skill, which won’t be easy. At Tricentis, we’ve realised that defensibility no longer lies in code — AI makes code almost disposable.
The moat is data, delivery, and customer trust. Code can be reproduced quickly, but real-world data and trusted customer relationships cannot. That’s why enterprises are incredibly protective of their data and why we focus heavily on transparency.”
From ERP overhauls to agentic AI workflows
In terms of AI-first evolution, Tricentis has three main focuses:
Autonomous testing — essentially, letting users guide the process while AI handles the execution. “We want 'hands on the keyboard' testing to disappear.”
ERP replacement and validation: “Many enterprises are moving to cloud ERP systems while grappling with massive technical debt and vendor lock-in. We see a huge opportunity in helping them test and validate those transitions,” shared Colwell.
Agentic coding and validation — Colwell asserts that the gap in the market is not just in AI coding but in AI validation.
“You can’t let the same AI that writes code also test it, because it will inherit the same false assumptions. We’ve developed approaches using separate AIs — one to write code, another to test it — communicating through protocols like Model Context Protocol. That separation creates the same dynamic you get in human teams, where developers and testers think differently.”
Tricentis AI workspace offers an enterprise-grade environment for managing AI agents, workflows and governance across the entire software lifecycle.
Coming in 2026, this intelligent workspace allows organisations to:
Onboard and orchestrate AI agents from Tricentis, partners or third parties;
Define governance and security policies for responsible AI operations;
Integrate directly into SDLC workflows using tools like Jira, GitHub and ServiceNow;
Monitor agent performance and compliance through unified dashboards; and
Scale quality engineering autonomously, empowering teams to manage agentic AI “workforces” while focusing on higher value initiatives.
The AI workspace unites Tricentis’ agentic portfolio, including Agentic Test Automation (Tosca), Quality Intelligence (SeaLights), Test Management (qTest) and Performance Engineering (NeoLoad), all connected through Model Context Protocol (MCP) servers that enable secure, flexible interoperability across AI systems and enterprise toolchains.
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Allye Energy raises $2.5M to scale smart battery systems and expand into Europe
London-based energytech Allye Energy has raised $2.5 million in a seed funding round to accelerate the deployment of its smart battery systems.
The funding round was anchored by Elbow Beach, alongside Alpha Future Funds.
Benedikt Sobotka, General Partner at Alpha Future Funds, said: “Allye's innovative approach to repurposing EV batteries - including those prematurely retired from accidents or early replacements - represents a circular economy breakthrough."
The round combines equity and debt financing and will support scaling up manufacturing and delivery of its technology for both grid-connected and off-grid use cases.
The company plans to expand into Europe within the next 12 to 18 months, having already established sales in the UK and Ireland.
Allye’s technology combines repurposed electric vehicle (EV) batteries with advanced control systems to provide flexible energy storage. Its systems are used in sectors ranging from construction and transport to energy utilities and media production. Customers including Horizon Plant and OnBio have ordered additional units following successful trials, while Roadchef has renewed its subscription contract.
The new funding will enable the further commercialisation of Allye’s MAX range of battery energy storage systems, including the MegaMAX models with capacities of 1 MWh and 1.5 MWh. It will also support the expansion of Allye’s engineering team to develop new power control innovations and battery technologies.
Jonathan Carrier, Founder and CEO of Allye Energy, said: “This funding represents validation of our vision to eliminate energy constraints through intelligent battery storage.
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From rare to resilient: Why exceptional cancer survivors signal a white space for startups
In oncology, progress is often described in cautious terms: a few months’ extra survival, a slightly improved quality of life, a percentage-point increase in remission. These steps matter, but they also reflect an industry built around averages. Clinical trials, treatment guidelines and approval frameworks all optimise for the “median” patient outcome.
Yet hidden inside every dataset are extraordinary outliers: cancer patients who, against all statistical odds, live far longer, and far better, than predicted. These “exceptional survivors” have traditionally been dismissed as anomalies. But what if, instead of treating them as medical curiosities, we saw them as the prototypes of a new standard? That is where I believe the opportunity lies, not just for science, but for startups, investors and healthtech pioneers.
From medical curiosities to a startup opportunity
The stories of exceptional survivors are not just inspirational; they are a largely untapped data source. Their biology, immune responses, genetic variants, lifestyles and psychosocial environments may hold clues to survival mechanisms that medicine has not yet translated into treatments.
This opens a massive white space for innovation. Startups are uniquely positioned to explore it because they can move faster than incumbents, cross traditional silos and experiment with technologies that scale. Agile startups can start from this observation and ask the question: what is right in the biology of survivors, and how can we replicate it?
For founders, this is a frontier market. For investors, it represents an underexploited therapeutic category with the potential for cross-cancer applications, lower toxicity profiles and reduced costs compared with late-stage interventions.
The tech enablers are already here
Until recently, resilience research was not feasible. Today, technology has rewritten the rules, and many of the leaders and drivers of this change are based in Europe.
Exceptional survivors are rare by definition and geographically scattered, making a large-scale study nearly impossible. But technology has changed the game overnight. AI and big data can now analyse billions of biomedical data points to spot survival patterns invisible to the human eye. Biobanking and sequencing provide high-resolution biological samples from patients worldwide. Digital twins allow researchers to model patient responses and simulate resilience mechanisms. Global data platforms can pool survivor cases across borders, creating the statistical power needed to extract actionable insights.
A nascent ecosystem and room to grow
Resilience-focused oncology today is where precision medicine was 15 years ago: rich in promise but still underfunded and under-recognised. Dedicated funding streams are needed, both public and private, to support early-stage ventures in this space. Regulatory pathways must also adapt to encourage resilience-driven endpoints, not only median survival metrics.
At the same time, cross-disciplinary collaboration is key.
Startups that can unite oncologists, immunologists, geneticists, data scientists and behavioural researchers will have an edge. Building resilience profiles requires a true 360° view of patients, not just tumours. That means integrating lifestyle, psychosocial and environmental data alongside biological samples. This is not a trivial challenge. But it is precisely the kind of complex, boundary-crossing problem where startups thrive and have a clear advantage over traditional health organisations, which tend to be siloed.
What is next for founders and investors
If you are a founder, resilience research is not just about biology; it is about data ownership, patient engagement and platform design. How can you create spaces where survivors contribute their stories and samples in exchange for transparency, support and real-world impact? How do you make data collection longitudinal, global and scalable? These are product and business model questions as much as scientific ones.
If you are an investor, resilience-focused oncology may be the next big therapeutic category. The potential for multi-cancer treatments, faster clinical trial recruitment and lower systemic costs is enormous. Just as rare disease startups reshaped biotech over the past decade, resilience startups could define the next one.
If you are a policymaker or ecosystem builder, the priority should be enabling global data collaboration. Exceptional survival cases are few; without international pooling, the statistical power is too weak. Europe has an opportunity to lead here by fostering data-sharing frameworks that respect privacy but allow startups to innovate on top of shared knowledge.
From outliers to new standards
The shift from focusing on “median patients” to learning from “exceptional survivors” will not replace oncology as we know it, but it could enrich it and accelerate transformative breakthroughs. Imagine clinical trial endpoints that do not just ask, “How long did the average patient live?” but also, “How many crossed into the realm of exceptional survival?”
The vision is clear: if startups and investors lean into this space, if regulators and funders support it, and if global data networks scale it, then what we currently call “exceptional” could one day become normal. The future of oncology will not be built on averages. It will be built on resilience. And startups have a once-in-a-generation chance to lead the way.
Lithuanian AI startup Supernaut AI has raised a €530,000 pre-seed investment from Helsinki- and Vilnius-based venture capital fund Superhero Capital.
Supernaut AI is building an “AI-native” tool for engineering teams, designed to accelerate software development by automating repetitive, time-consuming tasks and turning them into tested, documented code within minutes. The solution integrates with commonly used work platforms such as Jira and GitHub, acting as a proactive team member that helps resolve stalled tickets that often lack time or motivation to be addressed.
Supernaut AI stands out from competitors (such as individual developer tools like Vibe Coding) by focusing on team-based workflows. The solution helps not only with code generation but also with reducing technical debt.
Supernaut AI was founded by Mantas Konstantinavičius and Olga Maslova.
Mantas has years of experience leading engineering teams across five startups and applying AI-driven automation solutions in workflows. Olga Maslova, who holds a PhD in physics, brings deep technical expertise and experience in leading machine learning and data science projects as well as building complex systems.
“We’re building Supernaut to eliminate the biggest productivity barriers engineers face gradually,” shared Mantas Konstantinavičius, co-founder of Supernaut AI.
“Our first version solves a problem every developer knows – when Sentry floods you with errors, the whole team suddenly ends up fixing bugs instead of building the product.
Supernaut automatically investigates, documents, and fixes these issues with full transparency.
Our long-term vision is simple: an AI team member that reliably handles monotonous work so humans can focus on what truly creates value.”
The investment was led by Gytenis Galkis, Partner at Superhero Capital, responsible for expansion in the Baltic region.
"Mantas and Olga’s team has a unique market understanding and the technical competence needed to bring this solution to life. We see strong potential for both the product and the team to scale globally — their tool gives engineering teams back the time to innovate instead of dealing with backlogged tickets,” says Gytenis Galkis.
The product is currently being tested in a closed environment, and the startup plans soon to launch an open beta program with its first customers.
The funds raised will be used to expand the team and develop the product toward its first commercially viable version. Supernaut AI is targeting the global market, and investors see significant potential in proactive AI tools that enhance team productivity.
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Dutch energy innovator Return raises €300 million in growth capital to scale battery storage capacity
Amsterdam-based energy scale-up Return has entered a long-term partnership with APG, on behalf of pension fund ABP – the former of which is investing €300 million in new growth equity for a minority stake to support the platform.
“Partnering with APG marks an important step toward a more connected and resilient European energy system,” said Willem-Jan Schutte, Founder and CEO of Return. “Together, we can turn today’s fragmented energy landscape into one that truly works for customers, communities and the climate.”
Return’s growth equity investment from APG places it among the largest European storage and flexibility financings of 2025.
The deal surpasses most peer rounds, with only Terra One (€150 million) showing a comparable scale in grid-scale battery deployment. Within the Netherlands, Sympower and iwell also secured new capital this year, highlighting sustained investor confidence in Dutch energy flexibility platforms.
On a broader European level, green flexibility and Voltfang demonstrate continued institutional interest in scalable battery infrastructure.
Against this backdrop, Return’s partnership with APG reinforces the trend of large, long-term investors supporting capital-intensive, grid-balancing storage networks across Europe.
“The energy transition requires shared responsibility,” added Sjoerd Bazen, Managing Director at Return. “With APG we align interests, improve performance and create opportunities that benefit markets and society.”
Founded in 2021, Return is an energy scale-up specialising in grid-scale battery energy storage systems (BESS) and flexibility services. The company connects storage sites across countries through a data-driven platform that balances renewable generation, alleviates grid congestion, and enhances system reliability.
Active in the Netherlands, Germany, Belgium, and Spain, Return operates 70 MW of storage capacity with an additional 450 MW under construction.
With over €2 billion in long-term customer contracts, Return is on track to meet future demand with a pan-European storage network of around 5 GW by 2030, supporting flexible, reliable access to clean energy.
The transaction was signed in October 2025 and, subject to regulatory approval, is expected to close by year-end.
“APG’s investment aligns with its client’s strategy of supporting clean, connected infrastructure that delivers stable, long-term returns while advancing net-zero goals, in the interest of ABP and its participants. Grid-scale battery storage is key to reliably integrate renewables and to ease grid congestion,” said Bart Saenen, Senior Investment Director at APG. “Return’s integrated platform, long term vision on relations, and de-risked pipeline make it a strong partner for building grid resilience across Europe.”
Across Europe, the increasing share of renewables is creating fluctuations in electricity supply and demand. Energy customers need flexibility to balance portfolios and use renewable power more effectively. Return’s high-tech battery energy storage system (“BESS”) platform aims to tackle this challenge by connecting storage sites across countries, showing real-time insight where energy is available and needed to ease congestion and strengthen the grid.
The partnership reinforces Return’s role as an independent player in Europe’s energy system, connecting stakeholders through data-driven storage.
APG’s long-term involvement adds financial stability and supports continued system-focused delivery.
Amid record funding and growth, Britain is shaping itself as a top innovation powerhouse – and it’s doing so by reinvesting in an age-old advantage: its universities. This time, however, it’s not just academia leading the charge.
A three-pronged alliance between researchers, investors, and AI infrastructure is shaping a new wave of tech commercialisation that could reshape the UK economy for decades.
Record-breaking year for university spinouts
According to data received by EU-Startups this week, UK university spinouts raised a record €3.8 billion in equity investment during 2024, beating the previous high of €3.1 billion recorded in 2021. The findings, published by Parkwalk Advisors – a notably active investor in UK spinouts – and analytics platform Beauhurst, show a strong rebound from 2023 and renewed investor confidence.
This resurgence stems from several converging forces: a reawakened venture capital market, the return of ‘megarounds’, and stronger government focus on AI and digital infrastructure. Together, these trends are not only helping more companies spin out of academic institutions, but also laying down a path – albeit an uneven one – towards scale-up and global impact.
Challenges and disparities remain
Why uneven? Well, despite the impressive overall growth in UK innovation and investment, there are still significant imbalances and challenges within the ecosystem:
Regional Disparity: Nearly 78% of spinout investment still goes to the South East, London, and the East of England. Regions like the North, Scotland, and Wales receive comparatively little, although initiatives like the Northern Universities Venture (as covered by EU-Startups) Fund aim to change that.
Scale-Up Gap: While hundreds of spinouts are raising early rounds, few surpass the €22 million mark, stalling before commercial maturity.
Foreign Capital Dependence: The biggest rounds increasingly rely on US investors – valuable, but a sign of weak domestic risk appetite for late-stage venture.
Life sciences and DeepTech lead the way
Equity investment into UK spinouts in 2024 rose 44.3% compared to the previous year, with average deal size climbing from €5.6 million to €8.5 million. Life sciences led with 182 deals between H2 2024 and H1 2025, followed by DeepTech sectors like AI and data infrastructure with 152 deals.
Moray Wright, CEO of Parkwalk, said: “Spinouts are the future of this economy […] The companies raising record sums of investment in 2024 are tackling the biggest challenges of our time – from climate change to AI and healthcare.
They added that long-term support for the Enterprise Investment Scheme and full implementation of the Mansion House reforms could help the UK fully leverage its potential in frontier innovation.
The scale-up bottleneck
And yet, the findings illuminate difficult truths.
While early-stage investment is flourishing, scale-up funding remains limited. Of the hundreds of spinouts launched in recent years, only 57 raised between €20 million and €29.9 million, and just 42 reached €30 million to €39.9 million. Many are more than a decade old, suggesting even strong IP-based startups struggle to access growth capital for international expansion.
Greg Smith, CEO of IP Group, said: “The UK has nurtured one of the world’s leading ecosystems for academic innovation – but without scale-up capital, we risk missing a once-in-a-generation opportunity.”
Foreign capital, particularly from the United States, is filling part of this gap. US-based funds participated in 113 UK spinout deals in 2024, with average co-investment deal size rising from €15.4 million to €26.1 million year-on-year. Foreign-only rounds also grew, from €11.4 million to €18.4 million.
Five of the eight largest transactions in 2024 involved international investors.
Regional rebalancing takes shape
While the South East (€6.3 billion), London (€4.8 billion), and the East of England (€4.8 billion) still dominate, signs of rebalancing are emerging.
Manchester-based spinouts raised €64 million in 2024, a new record, while universities in Edinburgh, Sheffield, and Leeds are gaining momentum. Initiatives like The Northern Universities Venture Fund aims to unlock the research potential across the ‘Northern Arc’ – home to underfunded yet high-potential institutions.
Beyond spinouts, wider signs suggest Britain’s innovation economy is regaining its footing.
A Q3 2025 report by HSBC Innovation Banking and Dealroom shows UK startups and scaleups secured €7.6 billion in venture capital funding that quarter – the second-highest Q3 total on record and the strongest since 2021. With €14.7 billion raised so far in 2025, the UK has already matched its entire 2024 total and is on track to reach about €19.7 billion.
To put these numbers into perspective, the amount invested so far this year is reportedly greater than the combined totals of the top 2-4 countries: France (€5.3 billion), Germany (€5.1 billion) and Switzerland (€2.3 billion).
FinTech once again led, raising €4.5 billion across the first three quarters, including Revolut’s €1.7 billion round and Xelix’s €136 million Series B. Series A activity hit a seven-quarter high with 46 deals, signalling strong early-stage interest.
“UK venture capital has rebounded with strength across all stages,” said Simon Bumfrey, Head of Banking at HSBC Innovation Banking UK. “The return of billion-dollar megarounds, alongside record early-stage activity, signals renewed investor confidence […] FinTech remains the UK’s flagship sector, while the strength of HealthTech and other high-growth areas demonstrates the breadth of our ecosystem.”
He added that regional hubs are attracting a growing share of capital, positioning the UK as “a global centre where innovative ideas scale into successful, impactful businesses.”
AI infrastructure and the rise of UKAIFA
Nowhere is this convergence of research, capital, and policy clearer than in Edinburgh, where the EPCC (the UK’s first National Supercomputing Centre) is spearheading the €10 million UK AI Factory Antenna (UKAIFA). Supported by the UK Government and the European High Performance Computing Joint Undertaking, the project aims to mainstream AI across British industry and academia.
Set to employ 20 full-time staff and operate from early 2026, UKAIFA will support sectors such as health, FinTech, energy, creative industries, and robotics. It is part of a wider EuroHPC strategy placing supercomputing centres at the core of Europe’s digital transformation.
“This significant investment underlines Edinburgh’s world-leading capabilities in supercomputing and AI. It also shows the important role universities have in deepening our understanding of cutting-edge technologies,” said Professor Sir Peter Mathieson, Principal and Vice Chancellor of the University of Edinburgh.
The Antenna will work with Germany’s HammerHAI AI Factory to share best practices and provide scalable, secure infrastructure for businesses and researchers.
“By working with our neighbours, we’re giving our best and brightest access to the processing power, data and training needed to develop new breakthroughs in everything from healthcare to climate change,” said Kanishka Narayan, UK Government AI Minister.
A balanced innovation economy in the making
Britain’s strength in science hasn’t yet translated into scaled commercial success at the pace of the US or China. But as more spinouts raise larger rounds, regional universities gain access to capital, and AI infrastructure expands, the pieces of a more balanced and future-proofed innovation economy are falling into place.
Whether this becomes a launch pad for the UK – or just another spike in a notoriously cyclical tech sector – depends on the support of European investors and the innovation of their academic institutions.
For now, however, the message is clear: the UK is playing to its strengths.
Right now, one of the most common threads in innovation is the use of AI. Whether it’s designed for rapid drug discovery or drug repurposing, medical diagnosis, digital therapeutics, or fine-tuning a service delivery model, AI is everywhere and increasingly baked into the process of inventing.
But it’s not simply the adoption of AI that matters; it’s how it’s being used. When you’re a startup trying to secure investment, claiming you’re using AI is no longer enough. We’ve moved on from the days when buzzwords like AI or blockchain were sufficient to open funding doors. Investors are now more discerning, and importantly, so are patent offices.
Not all AI innovation is equal, and what makes AI patentable
Just because something uses AI doesn’t mean it’s patentable. Take, for example, a dating app versus an app that recommends whether you need to return to the hospital for an eye check-up based on analysis of longitudinal data from retinal scans. Both rely on AI and pattern recognition in the data, but one is viewed as a technical solution to a medical problem and associated healthcare risks, while the other might be dismissed as an obvious, non-technical business method that merely automates what has been done for many years, albeit with some additional sophistication. The AI itself doesn’t intrinsically know the difference, but the patent office certainly does. The real value often lies not only in the final trained model, but also in how you got there, especially your selection of training data.
The general position of most patent offices is that using AI to solve a big data problem, or spot a pattern, is often seen as obvious to try. So, when companies say they’ve innovated using AI, figuring out which side of the patentability line they are on is essential. Are you solving a genuinely technical problem or providing a new technical effect, or are you merely automating something that has been done manually for years?
Take financial risk profiling. AI can help maintain a client’s investment risk below a certain threshold in real time. That’s mathematically complex, involving data analysis, real-time inputs, and automation. Yet it’s still often viewed as non-technical. Why? Because the use case is finance, and that can then drag it to the wrong side of the line for patentability, a line drawn several decades ago.
Patenting AI vs keeping it secret
There’s another layer: even if something is patentable, should you file a patent application, or instead keep it as a trade secret? If your competitive edge lies in the trained model or the training data, secrecy might be the better strategy.
AI-based inventions in areas like healthcare, diagnostics, or engineering tend to get more traction from the patent office. But shift the focus to finance or admin, even if the technology is equally sophisticated, and it is often dismissed out of hand as an unpatentable business or mathematical method.
Startups should consider what exactly the inventive step is. Is it the technical problem solved, the selection or curation of training data, or the insights revealed? The answer will guide whether to patent or protect through secrecy. If the edge lies in the trained model or unique training data, secrecy may be the right approach, but you will need a trade secrets policy for this.
If, on the other hand, your innovation lies in the novel insight AI helped discover, and that insight can be articulated clearly, a patent for that will likely add real value. This is particularly true for drug discovery and drug repurposing, as well as novel dosage regimens.
AI is just a tool, but the human inventor is still key
Startups should also be cautious about saying their AI invented something. Instead, the focus should be on highlighting the ingenuity in how the team selected data, trained the model, and interpreted the outputs. That’s where the innovation lies, and that’s what patent law currently rewards.
Attributing the innovation to an AI platform may have PR value, but it carries real dangers, as only human inventors can be named on a patent application. You might be setting up a case for challenging the validity of the patent, either because there is no real human innovation or because you misrepresented it.
If a startup is using AI, the key question is whether it is implementing AI to deliver a technical solution or using AI to discover something new. In both cases, there’s real value, but the approach to IP protection will differ. And as policy slowly catches up with the pace of AI, navigating this grey area successfully will be a vital part of the innovation journey.
How ByteDance Made China’s Most Popular AI Chatbot
how-bytedance-made-chinas-most-popular-ai-chatbot
16/10/2025
An AI chatbot developed by TikTok's parent company, ByteDance, is now more popular than DeepSeek. The feat proves that user-friendly design often matters more than having the most advanced AI model.
16/10/2025 05:10 PM
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Deel hits $17.3B valuation after raising $300M from big-name VCs
Encube, a Stockholm-based DeepTech startup, is emerging from stealth with €19 million in funding to transform how hardware products are designed and manufactured, helping teams avoid costly design complexity, speed up development and lower production costs.
The round was backed by Kinnevik, Promus Ventures, and Inventure.
“Hardware development is a balancing act between how a product looks, functions and what it costs to produce. In Europe, we excel at the first two, but our manufacturing know-how is disappearing. At Sandvik and Aker, I saw firsthand how quickly production costs ballooned and competitive edge eroded, when early design decisions weren’t made with manufacturing in mind. We built Encube to change that,” says Hugo Nordell, CEO and Co-founder of Encube.
Encube’s launch funding arrives amid a surge of European investment in AI applied to industrial and manufacturing processes.
In 2025, Resourcly (Germany) raised €2.7 million for an AI-driven inventory platform, while 36ZERO Vision (Germany) secured €3.6 million to scale its data-efficient inspection software. Larger growth rounds, such as PhysicsX (UK) with €117 million and Pelico (France) with €34.7 million, show increasing investor appetite for AI-native engineering infrastructure. At an earlier stage, Bonx (France) and CloEE (Finland) attracted €7.3 million and €520k respectively for factory-focused software.
Within this funding landscape, Encube’s raise sits in the upper mid-range and reflects growing confidence in AI platforms that integrate design and manufacturing intelligence rather than focusing on narrow production tasks. Headquartered in Sweden, Encube also stands out within the Nordic deep-tech ecosystem, where few 2025 industrial AI startups have raised at comparable scale.
“Encube is one of the most promising innovations I’ve seen in hardware engineering in the last 30 years. The software’s ease of use and the speed of its simulations represent a major leap forward,” says Ralf Usinger, Global Head of Engineering Applications at Beyond Gravity.
Founded in 2021 by former Sandvik and Aker executive Hugo Nordell, together with Skype and Klarna veteran Johnny Bigert,, Encube is a European DeepTech startup developing AI-powered tools and workflows for hardware development. The company also conducts research in AI for hardware design, aiming to address complex challenges in the development process.
Validated by companies such as Volvo Group, Beyond Gravity and Scania, Encube develops an AI-powered platform that makes it faster and easier for hardware teams to understand which product design choices drive manufacturing complexity and how to avoid them.
This allegedly results in shorter time to market, lower cost of production and allows teams to explore exponentially more design directions than otherwise possible.
“Securing competence in our engineering and industrialisation functions is very challenging. Many of our key people are approaching retirement. Encube really helps us navigate the risk this creates for us,” says Jonas Hellman Peterson, Head of Sales Engineering at Birn Group.
Adding to industry pressures, tightening European sustainability regulations are requiring manufacturers to rethink how products are designed and built. Smarter product development and digital workflows at the design stage are becoming essential to improve both economic performance and environmental impact.
In hardware development, up to 80% of a product’s cost is determined once the design is locked. However, the company says many design decisions have an impact on manufacturing costs and the carbon footprint in ways that are not immediately obvious until they enter the production phase.
As a result, businesses are left with a difficult choice: either accept decreased profitability or redo the designs and delay market launch.
“We rely entirely on third parties to manufacture our robots. Encube makes it much easier for us to uncover and mitigate product risk early in development together with our suppliers and customers,” says Mattias Vanberg, Director of Development at Cognibotics.
Encube says they solve this challenge in two ways.
First, with a collaborative software platform that helps entire organisations align and make faster, better product decisions, all directly in the browser on any device.
Second, with AI-powered capabilities embedded inside the platform. These capabilities enable teams to eliminate common bottlenecks in hardware development projects.
One example of such a bottleneck is the need to manually identify design changes over time so that the team can determine if a change causes problems later. Another is to analyse how complex a design will be to manufacture, including what design choices drive this complexity.
“AI is fundamentally transforming how products are designed, enabling engineering teams to simulate, iterate and collaborate at unprecedented speed. Encube is pioneering this shift by embedding manufacturing intelligence directly into the engineering workflow, shaping the future of product development. We’re excited to partner with Hugo and the team on this journey,” says Tatiana Shalalvand, Investment Director at Kinnevik.
With a long-term ambition to help rebuild, secure and strengthen European industrial competitiveness, Encube will use its new financing to expand its commercial footprint across Europe, deepen existing partnerships and accelerate investments in hardware-focused AI, positioning the company to ride the current AI wave more aggressively.
“We’re incredibly proud to have been the first investors in Encube and our growing conviction in this stellar team has only been outpaced by the speed of their progress. We’re convinced that Encube is going to accomplish for industrial manufacturing what Figma did for web design and redefine how physical products are made,” says Adrian Arnsvik Bjurefalk, Principal at Inventure.
Barcelona-based Cooltra, a leading name in two-wheeled sustainable mobility across Europe, has officially acquired the business operations of fellow Barcelona-born urban cycling startup Kleta Mobility.
The move is part of Cooltra’s strategy to strengthen its service portfolio and deepen its market footprint across Spain, particularly in key cities like Barcelona and Valencia.
“For Cooltra, the integration of Kleta Mobility is a step forward in our growth strategy. This operation reaffirms our commitment to more sustainable, inclusive, and efficient urban mobility while enhancing our value proposition, diversifying our services, and providing real alternatives to private vehicle ownership,” said Timo Buetefisch, Co-founder and CEO of Cooltra. (Translated)
While many startups are securing fresh capital to scale operations, others – like Cooltra – are opting for strategic acquisitions to strengthen their position in competitive urban mobility markets.
Recent funding in the sector includes:
In Sweden, Standab raised €3.6 million to expand its charging infrastructure network for micromobility vehicles across Europe.
Belgium’s LIZY secured €75 million in equity and debt to scale its circular electric leasing model, highlighting investor confidence in sustainable fleet management.
In Spain, TRIBBU attracted €2 million in funding to grow its shared-mobility platform, signalling an active domestic investment landscape that also benefits established players such as Cooltra.
The Netherlands-based umob raised €3.5 million for its all-in-one mobility booking app.
The UK’s Forest secured €15.3 million to expand its e-bike fleet
Italy’s Maxi Mobility raised €1.2 million for its electric fleet-as-a-service platform.
Against this backdrop, Cooltra’s move represents a non-funding strategic consolidation, absorbing Kleta’s user base, assets, and employees to reinforce its market presence in Spain.
Overall, the deal reflects a European micromobility market in which scale, integration, and service diversification are becoming essential for sustainability – especially in urban transport ecosystems increasingly defined by electric, shared, and subscription-based models.
Buetefisch added: “At a critical moment for cities and the planet, we’re doubling down on the bicycle as the transport of the future. I want to thank everyone who made this possible. Their effort, passion, and commitment allow us to keep pedalling toward a cleaner, more human and connected future.” (Translated)
Founded in 2020 by Falk Siegel and Diego Casabe during the height of the pandemic, Kleta aimed to reduce barriers to city cycling with flexible, accessible mobility solutions.
Kleta’s roots in Barcelona mirror those of Cooltra, underscoring a shared commitment to local innovation in sustainable mobility. What began as a consumer-focused service has since expanded into B2B solutions, making the acquisition a strategic match for Cooltra’s multisector growth.
Founded in 2006, Cooltra has evolved into a dominant player in European micromobility, operating across multiple countries and offering electric scooters, bikes, and fleet services to both governments and private enterprises.
By folding Kleta’s assets and expertise into its broader operations, Cooltra gains not only scale but also a stronger foothold in the increasingly competitive bicycle-as-a-service market.
“The integration of Kleta’s production unit goes far beyond a business operation: it represents our firm commitment to bicycles as a driver of change towards more sustainable, inclusive, and efficient mobility. It is also a natural step in our growth strategy, adding talent, experience, and a community that shares our vision: we firmly believe that the future of cities moves on two wheels,” added Buetefisch in a public statement.
The integration will see Cooltra absorb Kleta’s fleet of over 2,000 urban bicycles- more than half of which are electric – alongside its existing customer base of 2,000 active users and a team of 13 employees.
All Kleta staff will retain their positions, seniority, and pay conditions.
Kleta’s offering was built around a subscription-based model for urban bicycles, tailored for both individual users and corporate clients. Subscribers could access quarterly or annual plans with perks like home repairs, theft protection, and accessory customisation.
The acquisition follows a difficult period for Kleta, which declared insolvency in September 2024 due to accumulated losses of €1.6 million and debts of €1.2 million with financial institutions.
Despite financial setbacks, the startup had managed to attract high-profile backers, including FC Barcelona goalkeeper Marc-André ter Stegen and NBA veteran Marc Gasol. The duo led two financing rounds worth €400k and €2 million respectively, demonstrating belief in the startup’s mission and potential.
With judicial approval now secured, the transition is expected to be completed in the coming days.
While Cooltra did not disclose the financial details of the acquisition, the company’s ongoing investment in expanding access to sustainable transport reinforces its ambitions to lead the urban mobility revolution – one pedal at a time.
UK-based
cybersecurity startup Theodosian has raised $1.3 million in a pre-seed round
led by Fuel Ventures, with participation from D11Z Ventures, 1818 Venture
Capital, Heartfelt, Startup Wise Guys, and several angel investors.
Theodosian provides
enterprise-grade, file-level encryption and access control, delivering a
persistent layer of protection that travels with data, supports compliance
across multiple regulatory frameworks, and helps mitigate both human error and
cyberattacks. Founded by cybersecurity practitioners with over a decade of
experience across defence, intelligence, banking, and healthcare, the company
focuses on a “second layer” of defence that embeds controls directly at the
file level.
The platform enables
per-file permissions and conducts 20–30 compliance-aligned checks per document.
It is designed to help organisations prepare for emerging standards, including
the UK’s Defence Cyber Certification (DCC) and the US Cybersecurity Maturity
Model Certification (CMMC), strengthening both compliance and overall security
posture.
According to Andy
Johnson, co-founder of Theodosian, the company was founded to close a major gap
in enterprise security by ensuring that each file remains protected wherever it
is shared or stored.
Our platform goes
beyond traditional encryption, offering persistent, per-file dynamic access
controls, detailed permission management, and continuous verification to ensure
only the right people can access sensitive data. With Fuel Ventures’ support,
we can bring these capabilities to market quickly, helping companies comply
with regulations, including new DCC standards, and significantly reduce the
risk of data breaches.
The funding
will support completion of v1 of the product and the start of commercial
scaling.
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Irish FinTech lender Teybridge Capital Europe secures €50 million funding line to expand working-capital solutions
Dublin’s FinTech startup Teybridge Capital Europe has raised an initial funding line of approximately €50 million from the Madrid-based family office Baghdadi Capital, with plans to gradually increase this to around €500 million as the business grows.
Teybridge Capital Europe, a trade finance and working capital platform, is projected to reach a valuation of over €100 million.
Dylan Martin, CEO of Teybridge Capital Europe, says: “The investment from Baghdadi Capital supercharges our ability to serve SMEs and corporates across multiple regions. It expands our reach, strengthens our offering, and brings our BRIDGE platform to more businesses in need of fast, reliable access to working capital.
“With this funding, we can support a broader client base while preserving the agility and rigor that have always defined us. It’s a powerful step forward for our company.”
This strategic investment aligns with a broader 2025 trend in Europe, where FinTech and specialty finance companies are scaling working capital and trade finance solutions through large credit lines and structured capital facilities.
Several comparable developments were reported by EU-Startups this year:
London-based Zvilo secured an expanded €75 million credit facility to support MSME trade finance operations.
Amsterdam’s Factris obtained €100 million from Brand New Day Bank to grow its SME invoice-financing portfolio across Europe.
Prague-based Flowpay raised €30 million from Fasanara Capital to enhance its embedded finance offering for SMEs.
Berlin’s re:cap secured a €125 million credit facility to expand its “Capital OS” platform into the UK market.
Brussels startup Husk raised €1 million in pre-seed funding to develop cashflow optimisation tools for early-stage businesses.
“At Baghdadi Capital we are not simply investing in companies; we are shaping a global network of autonomous platforms – connected by shared standards and strengthened with capital. Our investment in Teybridge Capital Europe reflects this vision: building resilience, empowering local teams, and delivering truly complementary financing solutions that support cross border growth,” adds Baihas Baghdadi, Founder & Executive Chairman of Baghdadi Capital.
Founded in 2022 by Dylan Martin and Colm Devine, Teybridge Capital Europe delivers working capital and trade finance solutions to SMEs and corporates through its proprietary platform, BRIDGE.
In two and a half years, Teybridge has deployed approximaely €500 million to over 250 SMEs across Ireland, the UK, and the U.S.
This investment forms part of Baghdadi Capital’s broader diversification strategy, which is designed to strengthen the Group’s position beyond Spain – its core market – where it already holds the largest book through its subsidiary, Trade & Working Capital.
All acquisitions are structured as cash-in only participations, with management teams retaining full autonomy over daily operations and risk assessment.
The UK market now represents 60% of Teybridge Capital Europe’s lending portfolio, providing lending facilities to UK SMEs and corporate clients in the food & beverage, technology, and manufacturing sectors.
Baghdadi Capital’s clients will now gain access to BRIDGE , Teybridge’s proprietary platform, for digital onboarding, operational management and near real-time funding.
Over the past two and a half years, the platform has processed more than 12,500 transactions and funded approximately more than £400 million in trade finance and working capital loans, to more than 250 clients based in the UK, Ireland and the US.
In this context, Teybridge Capital Europe brings nearly 1,000 debtors across 19 countries over the past two and a half years, while Baghdadi Capital through its different companies in the US and Spain managed almost 500 debtors only in the last fiscal year.
Together, the platforms look to achieve greater granularity and resilience, reducing concentration risk and creating synergies to negotiate more efficient funding terms which opens the door to new securitisation-like structures.
As part of the funding, Baghdadi Capital will join Teybridge Capital Europe’s board.
Encube builds an AI-driven platform
that helps hardware teams identify which design choices create manufacturing
complexity and how to avoid them. The result is faster development, lower
production costs, and the ability to explore far more design options.
Founded
by former Sandvik executive Hugo Nordell (CEO) and Skype/Klarna veteran Johnny Bigert, Encube is rethinking how engineering teams collaborate on hardware
product design.
European manufacturing is being
reshaped by geopolitics, a tightening talent pipeline, and the shift to
sustainable production. Supply-chain fragmentation and economic nationalism are
driving efforts to re-shore capabilities and secure industrial autonomy.
Meanwhile, an ageing workforce and past offshoring have widened skill gaps.
Stricter sustainability rules are pushing for earlier, smarter design and digital
workflows. Because most product costs are locked at design, late-stage impacts
on manufacturing expense and carbon footprint often force firms to choose
between lower margins or redesigns and delays.
Encube addresses these
challenges through two approaches. First, it offers a browser-based
collaborative platform that helps organisations align and make faster,
higher-quality product decisions across devices. Second, it embeds AI
capabilities that remove common hardware-development bottlenecks. These
workflows are essential yet typically manual and time-consuming. Encube aims to
make them faster, more accurate, and scalable.
The
platform has been tested in R&D programs with partners ranging from large
industrial firms to specialised space companies. Reported outcomes include
reduced time to market (up to 50 per cent), lower production costs (20–30 per
cent), and higher engineering productivity (up to 2×).
Hardware development is a
balancing act between how a product looks, functions and what it costs to
produce. In Europe, we excel at the first two, but our manufacturing know-how
is disappearing. At Sandvik and Aker, I saw firsthand how quickly production
costs ballooned and competitive edge eroded, when early design decisions
weren’t made with manufacturing in mind. We built Encube to change that,
shared Hugo Nordell.
The
new funding will support expansion across European markets, growth of existing
partnerships, and increased investment in hardware-focused AI, positioning the
company to accelerate its participation in the ongoing AI transformation.
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Dwarf Engineering is building the universal infrastructure layer for Ukraine’s defence sector
The defencetech sector has boomed since Russia’s full-scale invasion of Ukraine. Many companies have now completed product development and beta testing, but they face a critical next hurdle: scaling up production. Large-scale manufacturing of new technologies demands robust, well-planned infrastructure.
Currently, individual teams are building their own production infrastructure from scratch, a process that wastes six to twelve months and $ 200,000 to $ 500,000 per tech solution.
Dwarf Engineering is the first company in Ukraine to launch ready-made infrastructure for B2B integrations in the defence tech sector, that allows software from different manufacturers to be deployed and updated across all types of unmanned systems and precision-guided munitions. I recently saw the company in the startup pitch final at IT Arena, where it won first place in the startup competition in defencetech category.
I spoke to Oleksandr Bakhmach, co-founder and CTO at Dwarf Engineering, to learn more.
A new standard for defence collaboration
According to Bakhmach, the company’s mission is to “build a bridge for quality assurance and technical support between tech teams and manufacturers.”
He adds,
“I haven’t seen anything like this globally. Most companies, such as drone maker DJI, are closed ecosystems. They don’t connect different companies or cover the full chain from software to hardware.”
The platform takes the opposite approach. “We’re building an open but secure protocol that allows different companies to collaborate without compromising sensitive data,” Bakhmach explains.
“Standardisation is crucial here. It might sound simple, but it’s actually the hardest and most innovative part of our platform.
We give manufacturers and tech teams a native, secure way to cooperate with each other — something that hasn’t existed before.”
A pivot to build Ukraine’s defence infrastructure layer
Bakhmach comes from a background in software engineering — mostly machine learning, data science, and computer vision. He shared: “I was always passionate about designing software architectures. From an early age, I was interested in robotics and wanted to find the right time to get involved in building robotic systems. I have a pretty broad background: from computer vision to Web3. I’ve worked with a lot of concepts, businesses, and ideas. So starting something new wasn’t too complicated for me.”
But he stressed, its not just about him — everyone at Dwarf Engineering wanted to build something new from scratch.
“In modern software development, everything is so automated and standardised that it’s hard to innovate. We wanted a new challenge and a “new breath.”
When it comes to defence, the whole domain is new.
According to Bakhmach, “the challenges in defence today are ones we’ve never had to deal with before. People are using tools intended for different purposes, and no existing platform addresses all of the domains.
Dwarf Engineering applies abstraction to defence infrastructure
To achieve its goal, Dwarf Engineering took principles from software development — particularly object-oriented programming — and applied them to the engineering domain.
At the core of this approach is abstraction, which allows complex systems to be broken down into modular, interoperable components.
According to Bakhmach, “every engineer, when facing a new challenge, tries to abstract the domain, find patterns and hidden relationships, and automate them. We did the same: we tackled autonomy systems, found recurring patterns and interfaces, and realised we needed a tool to do this better.”
The team realised this was a problem faced by all of the engineers in Ukraine.
“So we built a solution based on experience, data, and analytics. Our platform lets manufacturers and engineering companies focus on what they’re passionate about, while we solve the common problems they’d otherwise face again and again.”
Bakhmach outlined two key user groups: tech teams and manufacturers. For engineering teams, the main challenge has been secure collaboration.
“In traditional engineering, people collaborate openly and trust each other. In defence, it’s the opposite — zero trust, a lot of sensitivity, and no existing tools for collaboration,” he says.
“There wasn’t a platform to handle this before. We’re the first to develop a strategy that enables engineers to collaborate while maintaining zero-trust security. It was complicated, but I’m proud to say we’ve achieved it.
Now teams can collaborate, share data, and combine software without compromising security, intellectual property, or sensitive information.”
For manufacturers, the platform tackles standardisation — a critical but missing element in the defence sector. “In manufacturing, standardisation impacts everything — logistics, production, interoperability,” Bakhmach notes. “Defence lacked this standardisation. So our platform solves two problems at once: engineering security and manufacturing standardisation. That’s why we believe it’s a game-changer and why we received the IT Arena award — our vision aligns with the market.”
Turning shared struggles into a scalable platform
Bakhmach shared that most engineers they reached out to already knew they were missing something like this.
“When we showed them we knew the exact pain points they were facing — sometimes issues they’d never shared publicly — they were amazed. “How do you know that?” they’d ask. It’s because we went through the same challenges ourselves. That credibility made it easy to demonstrate why using our platform made sense.”
“Startups need to prove their concepts quickly to investors. We remove friction and side problems that distract them from their core ideas. You can think of our platform as a “hardware Docker”: a standardised, secure environment that lets them focus on building, not on infrastructure.”
Getting underneath the hood of the platform
The first major feature is Continuous Integration and Deployment (CI/CD), adapted for defence hardware. This isn’t new in software, but the defence domain needed a new vision for using hardware.
“We’ve adopted DevOps ideas so teams can use familiar development patterns. That reduces friction and speeds up delivery,” shared Bakhmach.
The second feature is zero-trust environments. This enables multiple teams to work on the same device, each in isolated, secure environments that never interact.
“It’s like having a mini cloud on the device — SSH access, secure logging, everything — but fully isolated.”
For manufacturers, Dwarf Engineering provides strict versioning and standard interfaces for clear communication. These are crucial for collaboration between manufacturers and engineering teams. The platform is subscription-based.
Akin to the PlayStation Store: Dwarf Engineering provides the “console” — the platform — and users pick the “games,” i.e., modules and features, to run on it. All within a secure, zero-trust environment. Bakmach contends, “before our launch, it was the "first generation of video game consoles' era for the Ukrainian defence sector, and we started 'the second.” “Manufacturers integrate the system once, then can subscribe to different modules, combine them, or switch them out as needed.”
All of Dwarf Engineering’s software currently runs on Raspberry Pi with a customised Linux distribution.
“We modified drivers and a lot of system elements to make it efficient,” shared Bakhmach.
“We also provide a standard SDK and defined interfaces for communicating with UAVs and other unmanned systems — aerial, ground, or underwater.
Every device has its own control interface, and that’s a big headache for development teams. We remove that burden.”
Dwarf Engineering steps into hardware with Narsil
Now Dwarf Engineering is developing its own custom hardware, optimised for security and performance, to address gaps in off-the-shelf systems.
Narsil is a copilot system for combat FPV drones built around an autonomous target-guidance module that the team extends with frontline-driven features. Those enhancements can include maintaining flight under electronic-warfare conditions or navigating to targets in GPS-denied environments.
A key advantage for military users is Narsil’s semi-autonomous design: it preserves the control and experience of a professional operator while lowering the skill barrier for less experienced users. Among its distinctive capabilities is an integrated cruise-mode with targeting that simplifies long-distance aiming — a feature the team haven’t encountered elsewhere in this field. It is also, to its knowledge, the first smart guidance module that integrates directly with the payload.
Crucially, Narsil works offline in extreme environments, a critical challenge according to Bakhmach:
“Most systems assume access to sensors, GPS, or cloud compute. In reality, you may have none of that on the battlefield. So we rewrote algorithms to lower their requirements, rather than increasing hardware power.
We design as if there’s no connection, no data, and no sensors — then build from there. It’s challenging, but it’s the only way to ensure reliability in real conditions."
Further, each of the devices can form part of a peer-to-peer swarm. Devices can collaborate securely between each other, out of the box.
“It’s a huge benefit for collective autonomy missions,” shared Bakhmach.
Dwarf Engineering goes global with strategic partnerships and major milestones
Dwarf Engineering has achieved rapid growth and success. Its CEO, Vladyslav Piotrovskyi,was selected for the first batch at the DTSA accelerator at the prestigious Stanford Research Institute and secured first place at Defence Tech Valley, highlighting its innovation in the defence sector. It became the first to deliver payload-agnostic terminal guidance technology and successfully integrated three tech teams to accelerate development.
In terms of customers, Dwarf Engineering has signed agreements with seven factories and welcomed its first international client in Japan. With more than 1,500 hours of testing completed and its first factory application set to launch, the company has already sold 10,000 licences.
According to Bakhmach, the focus now is onboarding as many teams and manufacturers as possible to the Dwarf Engineering platform, speeding up delivery, improving security and optimisation, and reducing costs.
Winning at IT Arena validates “that we’re solving the right problems — problems the market truly cares about.”
