A federal judge in Oklahoma has ruled that a deputy’s warrantless search of Flock’s licence plate reader network broke the US Constitution. In an order dated 1 October, Judge Sara Hill called the system “a type of indiscriminate mass surveillance”. Jason Koebler of 404 Media first reported the ruling. “It is a tool that collects […]

Ask anyone who has worked in a security operations center what the job actually involves, and you’ll hear a lot about alerts. Thousands of them, most of which turn out to be nothing. For the past decade, AI’s role has been to help with that pile: spot something odd, flag it, and leave the decision […]

Collibra has acquired trail ML, a Munich startup whose agents work out which AI rules apply to a system, check whether its controls work, and block agent actions that break policy, with no price disclosed. The market exists because of the EU AI Act, whose enforcement powers arrived on 2 August and whose frontier model […]

OpenAI’s own AI models changed parts of its Jalapeño chip, and its engineers could not always say why. In one example, they saved more than 13% of die area, Richard Ho told Ian Cutress of More Than Moore. Ho leads OpenAI’s hardware team, and the interview was published on 30 September. “Well, I still don’t […]

Hans Anders, one of the largest Dutch eyewear chains, has stopped selling Meta’s Ray-Ban smart glasses in the Netherlands and Belgium. The chain told Reuters on Friday that privacy concerns were behind the move. Dutch online retailer Wehkamp has also paused sales, Business Insider reported. “This decision follows the ongoing public and political debate surrounding […]

Apple will add new controls to Full Disk Access on the Mac. Users will only be able to give an app that level of access “with very explicit user action”. The company announced the change on its developer news site on Friday and said AI agents were the reason. “As AI agents become increasingly capable […]

Zurich-based Namespace, a developer platform that offers fast coding, build, and test environments across Mac, Windows, and Linux, today announced its €37 million ($42 million) Series B to accelerate product development and expand its data centers

The round, closed only seven months after their Series A funding, was led by Scale Venture Partners, with participation from 20VC, NEA, Essence, Burst Capital, and angel investors including Olivier Pomel (CEO of Datadog) – bringing the total raised to €58 million ($65 million). The expansion comes as demand surges, with Namespace’s total revenue growing 8x over the past 12 months.

“I started Namespace because I believe developers deserve better. At Google, I saw how much great tools & infrastructure changes the way developers work. Outside of a handful of companies, that still doesn’t exist,” says Hugo Santos, Founder and CEO of Namespace. “My vision is to make that experience the default for every fast moving company. We’re starting where developers and their agents spend the entire day: coding and CI.”

Namespace’s Series B comes amid continued investment in European developer tooling and infrastructure in 2026.

EU-Startups has covered approximately €160 million in funding across ten comparable or adjacent companies this year, including €61.5 million for Belfast-based software supply-chain platform Cloudsmith, €31 million for Cambridge-based software engineering company Undo, €21 million for Paris-based orchestration platform Kestra, and €4 million for Helsinki-based AI-native CI/CD startup Avrea.

Switzerland has also contributed to this activity, with Zurich-based Rapidata raising €7.2 million for AI development infrastructure and Pfäffikon-based AI Infrastructure Capital AG launching with around €16 million for compute capacity.

“The use of agents in software development challenges the tradeoff assumptions made by prior generations of tooling,” adds Javier Redondo, Partner at Scale Venture Partners. “Namespace is​ the platform that can meet the demand for speed and scalability, while delivering the same reliability and security that engineers have grown accustomed to.”

Founded in 2022, Namespace offers fast coding, build, and test environments across Mac, Windows, and Linux. The company was founded by former Google Principal Engineer Hugo Santos.

While hyperscalers like AWS and GCP optimise for production workloads, Namespace says they optimises for coding, build, and test environments. It designs and deploys its own server racks worldwide, then builds their suite of products on that engineering foundation.

Namespace is already working with over 1000 organisations including SpaceXAI, Ramp, Framer, ElevenLabs, Vanta, Bilt. and Sierra.

“Namespace is the best dev infrastructure tool I’ve used in years. We run everything from our CI to Oz, our cloud agent platform, on Namespace, and I could not recommend it enough,” says Aloke Desai, Head of Product Engineering, Warp

According to the company, some of the most important interactions today happen on an iPhone or a Macbook. Yet almost every infrastructure provider skips Mac, which means a developer’s agent, trying to build an iOS or macOS app for the App Store, has nowhere to build or test it. Coding agents need a Mac at any scale with all the required iOS and macOS developer tooling. This has led to a demand for Namespace’s Mac environments.

With the new funding, Namespace will expand its data centre locations, including its fleet of Mac hardware, and open offices in San Francisco and New York City.

The post Namespace secures €37 million to scale coding, build and test infrastructure across Mac, Windows and Linux appeared first on EU-Startups.

PwC and Cohere have announced a global alliance to sell secure enterprise AI, beginning in Canada, with no client, value or timeline disclosed. Cohere markets itself as a sovereign AI company while completing a merger with Germany’s Aleph Alpha in which Cohere shareholders take roughly 90%, as Europe drafts rules defining the highest tier of […]

Slovenia’s domain registry recorded 20,276 new .si web addresses in the 24 hours to Monday afternoon, the live counter on Register.si shows. The .si country code matches the initials of “super intelligence”, the name President Donald Trump has told US agencies to use instead of AI. The registry counts 46,066 new .si domains in the […]

Google has said a small number of complex Android apps and games need developer tuning to run properly on the Intel versions of its new Googlebook laptops, which reached Britain, Ireland, France and Germany today. Three of the five models use Intel chips and run Android through a translation layer, while the Dell and HP […]

Anyone who has ever worked at a large enterprise knows the drill. You submit an IT ticket for a complex software issue, and then you wait. First-generation AI chatbots have successfully managed to automate the low-hanging fruit of Tier-1 support, like password resets and basic software approvals. But they historically hit a brick wall the […]

Reclinker, a startup that turns demolition waste back into cement, has raised £10m in a Series A round. It will use the money to move from trials to full commercial production in Cardiff. The company said on Monday that its process cuts cement’s emissions in half, at the same cost as conventional cement. Clean Growth […]

A Zurich-founded developer infrastructure startup has raised $42m in a Series B financing round, just seven months after completing its Series A. Namespace is a platform that increases the pace of software teams’ build and test workflows. Its tech is geared towards engineering teams that want faster software development without managing the infrastructure themselves.

Founded in 2022 by former Google principal engineer Hugo Santos, Namespace is aiming to be the infrastructure layer for AI coding agents, so developers and AI agents can build, test and run code faster.

Its funding round comes at a time when coding agents have sped up the time to write software.  

The Series B funding round was led by Scale Venture Partners, with participation from 20VC, NEA, Essence, Burst Capital, and angel investors including Olivier Pomel, the CEO of Datadog.  

Namespace will use the funds to speed up product development and expand its own compute and server operation.

Santos said: "I started Namespace because I believe developers deserve better. At Google, I saw how much great tools & infrastructure changes the way developers work. Outside of a handful of companies, that still doesn’t exist. My vision is to make that experience the default for every fast-moving company. We're starting where developers and their agents spend the entire day: coding and Continuous Integration."

Namespace works with organisations including SpaceXAI, Ramp, Framer, ElevenLabs and Vanta.

During the first episode of Decoded, Politico’s podcast, OpenAI chief executive Sam Altman says the money AI companies are pouring into US politics has failed to improve how people see the technology. “Something’s clearly not working,” he said on the first episode of Politico’s Decoded podcast. People often love using AI tools, Altman said, but they are […]

Deliveroo has partnered with the American firm Coco Robotics to run four-wheeled pavement robots in five UK locations, starting in Canary Wharf this month, and says most orders will still go to human riders. Milton Keynes, one of the five, has had robot deliveries since April 2018 through Starship, a company founded in Tallinn and […]

RobCo, a Munich-based robotics startup focused on industrial automation, today announced that it has surpassed an €892.4 million ($1 billion) valuation in a transaction that combines new investment with an employee secondary share sale. The company says its valuation has doubled in nine months. 

Existing investors, including Sequoia, Lightspeed, Greenfield, Kindred, Lingotto, and Promus Ventures, participated in this deal alongside new investors, including Cherry Ventures and European Tech Collective, a group of European technology founders. The announcement did not disclose the transaction’s size or the split between new capital and secondary share sales. Earlier this year, in January, the company raised €89.2 million ($100 million) in a Series C round co-led by Lightspeed Venture Partners and Lingotto Innovation. 

“This is an important moment for RobCo, and I cannot think of a better way to mark it than by giving some of the people who built this company the opportunity to realise part of the value they created. There was strong demand to invest in RobCo, so we used that moment to strengthen the company. A billion-dollar valuation is an incredible milestone, but we’re much more excited about what comes next: bringing the next generation of autonomous industrial robotics to factory floors,” said Roman Hölzl, co-founder and CEO of RobCo. 

Founded in 2020 out of the Technical University of Munich, RobCo is a physical AI-driven robotics company developing AI-driven robotic systems that bring learning and autonomy into industrial operations. 

By combining perception, motion planning, and self-learning methods, RobCo states that its platform reduces friction between today’s processes and end-to-end automation. 

At the core of RobCo’s offering is Alfie, a robot purpose-built for the autonomous industrial lifecycle. The company highlighted that Alfie combines perception, reasoning and execution to handle the tasks that have defeated traditional automation for decades: high-mix, unstructured, safety-critical work on real factory floors. Alfie will be commercially launched at RobCoN, its first annual summit, in Munich on March 4th, 2027.

Deployed through a robotics-as-a-service model with zero upfront investment, RobCo helps industrial companies automate manual tasks while minimising operational complexity and risk. The company supports a wide range of industrial workflows, including machine tending, palletising, dispensing, and welding.

RobCo expanded into the United States in 2025 and is doubling down on the country, which is already its fastest-growing market. Its customer operations now span more than a dozen states, which is supported by manufacturing and assembly operations in Austin, Texas, and a lab in San Francisco. The company also notes that its CEO has relocated to the US to personally drive the company’s expansion.

“RobCo is building for a future in which AI doesn’t just reason and generate, but acts in the physical world. The progress the company has made over the past few years is impressive, but we believe this is still the beginning. RobCo has the ambition and technology to fundamentally change how industrial work gets done, and we’re excited to see the company take that vision from Europe to factory floors around the world,” said Luciana Lixandru, Partner at Sequoia Capital.

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Ukrainian defencetech company Buntar Aerospace has closed a $16 million funding round. The round was led by Freedom Fund and an international growth equity investor, with participation from Gardar, Iron Wolf, and Autonomy Capital. It brings the company's total capital raised to $30 million.

Buntar Aerospace built its business on the Buntar-3 reconnaissance drone and Buntar Copilot, knowledge-based AI for drone warfare. Together they form a stable, fast-growing commercial base with front-line units across Ukraine.

With its new investment funding, Buntar Aerospace will accelerate product development, expand manufacturing capacity to meet growing demand from the Armed Forces of Ukraine, and recruit top engineering, management and operations talent while bringing proven teams and technologies into the Buntar platform.

 The company will also continue developing Buntar Copilot and enter new international markets with dual-use product lines beyond Intelligence, Surveillance and Reconnaissance systems — evolving Buntar into a multi-domain defence autonomy company with a growing footprint in the civilian sector, where demand for autonomous technology is rising fastest.

"Every Buntar system is built to fly, sense, and adapt on its own, so skilled people can focus on decisions. We're targeting the missions that depend most on highly trained operators: reconnaissance, counter-drone defence and precision strike assistance. That's what Ukraine needs today, and what Europe must be ready for tomorrow. Our experience shows us that what we design today for defence has a wide range of civil applications as well, enabling us to expand our dual-use offering as well," said Bohdan Sas, co-founder, Buntar Aerospace.

Some people might think there’s only one way to do an interview. While in-person conversations or Zoom calls are the norm, that format doesn’t suit everyone.

I believe that if someone has a compelling story to tell, they should have the opportunity to tell it in a way that works for them.

I’m also increasingly interviewing very young founders — some under 18 — who tell me that I’m their first-ever media interview, often conducted in a language that isn’t their first. I want to give people the opportunity to tell their story and shine, rather than make the format itself a barrier.

Bálint László is 19 and the founder of LB: Universal Scanner, a privacy-focused product and ingredient scanner.

Point your phone at a barcode — or photograph the ingredients if the barcode isn’t recognised — and the app helps explain what’s actually in the product. It covers everything from food and pet food to cosmetics, cleaning products, and household and art supplies.

Bálint is also neurodiverse and prefers written rather than verbal communication. So, instead of a conventional interview, I spoke with Bálint and his mother, Mónika, in writing to learn more about him, what he’s building, and why.

Bálint was born in Hungary and has lived in Germany since he was five. He shared:

“I’m autistic, and I’ve always processed information somewhat differently from the way traditional education expected me to. I tend to focus on how something actually works, whether there’s a logical solution, and whether there’s a more efficient way of doing it.”

LB is a consumer app, available on Android and iOS. It may have been built with limited resources, but it has a serious focus on usefulness, accessibility, privacy, and responsible information.

The idea behind LB: Universal Scanner

The idea for LB: Universal Scanner originated from his mother, Mónika, who has fructose and lactose intolerances/sensitivities, which caused her a lot of digestive problems.

She explained:

“The original idea came from a friend of ours, Tünde. I asked what kind of app she would want if someone could build exactly what she needed but couldn’t find anywhere.

She said she wanted an app that could tell her which ingredients in food might harm her. That immediately made sense to me because of my own allergies, so we started with food.”

One day, Mónika was standing in the shower looking at the ingredients on a shower gel. She realised she didn’t understand many of those either:

“I thought, why should this only work for food? We also have two cats, Bella and Teddy, and I wanted to understand what was actually in their food.”

One thing led to another. Food expanded into pet food, cosmetics, cleaning products, and eventually art and craft supplies. The same problem kept appearing: we’re surrounded by product information, but it isn’t always easy to understand or verify.

With LB, users can scan a product barcode or photograph an ingredient or safety label. Barcode scans search supported public product databases, while photo scans use text recognition. Users can review and correct the recognised text before the app analyses it.

Today, LB covers four broad categories: human food, pet food, cosmetics, and cleaning and art/craft products. The latter includes paints, glues, pigments, clay, dyes, solvents, and resins, where ingredient or safety information can be important. For food and personal health-related use, people can create profiles around allergies and sensitivities, including cross-allergies and medication allergies, as well as settings such as IBS/SIBO, FODMAP, Keto, Blue Zone, and healthy-longevity preferences.

The app can show ingredients, warning triggers, allergens or cautions, nutrition information where available, translations, and which parts of a label it could or couldn’t match. It also includes product comparisons, notes, scan history, and recall-related information.

To be clear, it stands as an informational aid, not a medical diagnosis, and it can’t guarantee that a product is safe from trace ingredients.

Bálint explained:

“I’m primarily building it for people with allergies or sensitivities, visually impaired users, families, caregivers, and anyone who wants clearer product information.”

Learning by building

Bálint started learning English quite young through YouTube. Around the age of 12:

“I taught myself to touch-type because I thought it would be useful in the future.”

Later, he found online Python and C++ courses, which eventually led him to platforms such as edX and courses from HarvardX, IBM, and others.

However, he asserts that while a course can teach you an algorithm or concept, building and shipping a real application forces you to deal with unreliable network responses, camera behaviour, corrupted data, accessibility, localisation, performance, device differences, and app-store requirements at the same time.

“The strongest learning happens when something you built has to work in the real world, something fails, and you have to understand why, fix it, and prevent it from happening again.”

Why scanning a barcode isn’t enough

While there are already numerous barcode and product-scanning apps, many treat finding a database record as the end of the process. Bálint saw it as only the beginning.

The company conducted its own small-sample test, scanning protein powders by barcode and comparing the database results with the ingredient lists printed on the packaging.

“One test really changed the way I thought about this. In roughly 90 per cent of the cases we tested, the barcode information didn’t fully match what was on the package.

That was a serious warning for us. A barcode can identify a product, but the database record behind it may be incomplete, outdated, or different from the formulation currently on the shelf. For someone with a serious allergy, relying solely on that information could be dangerous.”

That’s why LB uses a layered process. It validates the barcode, identifies what kind of information it contains, retrieves available data, and, when necessary, falls back to the physical label. Users can review OCR results before analysis, and the app shows what it matched and what it couldn’t.

“I don’t want the app to pretend it knows more than it actually does. Scanning is only the entry point.”

When there’s no barcode to scan

But reading a physical label creates a different set of problems. The print might be tiny, the packaging curved, or there might be glare, damaged text, multiple languages, or unusual fonts. OCR can also make mistakes. Then you have to separate the recognised text into meaningful ingredients, normalise those ingredients, and match them against aliases without creating dangerous false positives.

“That’s why LB includes a review-before-analysis step. It can interpret a label without a barcode, but it remains clear that text alone can’t authenticate the exact product,” explained Bálint.

This is further compounded by different barcode standards, packaging formats, and identification systems across countries and industries — LB recognises several common one-dimensional and two-dimensional barcode formats, but according to Bálint, recognition alone isn’t enough.

The app classifies the payload before attempting a product lookup, validating common product identifiers such as EAN, UPC, and GTIN, as well as decoding GS1 data where available.

“Where that information is encoded, it can also expose details such as batch or lot numbers and package dates.”

An important part of the process is deciding what not to treat as a product identifier. A QR code might contain a website, Wi-Fi credentials, or contact information rather than product data. LB rejects those as non-product content and doesn’t automatically open them.

Database coverage and packaging conventions also vary by country and industry. When those sources disagree or are incomplete, the physical label provides an independent fallback.

Machine learning reads, but doesn’t decide

In terms of tech, Bálint uses machine learning in a narrow, practical role, mainly for perception and language. On-device models can help recognise barcodes and printed text, identify languages, and translate content. Google’s barcode recognition, for example, can run on the device without requiring a network connection.

“But I deliberately don’t give a generative AI model responsibility for deciding whether a product is safe,” he explained.

After recognition, LB uses deterministic rules, bundled ingredient knowledge, validated identifiers, and the user’s selected profile settings.

“The same input should produce the same warning, and the app can explain what triggered it. My approach is simple: machine learning helps the app read. It doesn’t get permission to invent the answer.”

A local-first approach to privacy

Personal profiles, allergen settings, notes, favourites, and scan history remain on the device. LB doesn’t require an account, and there’s no third-party advertising or analytics backend collecting user activity. Barcode and label recognition and bundled ingredient analysis can operate locally.

Some features naturally require connectivity, such as searches of public product databases, live external evidence, or recall lookups. Translation may also require downloading a language model or using a selected online translation method.

Local-first doesn’t mean pretending the internet is never used. It means local processing and user control are the default, while network-dependent actions have a clear purpose and boundary.

Verifying what the scanner tells you

Bálint explained that there are really two questions: whether LB’s own logic is behaving correctly, and whether an external product record is current.

“I can rigorously test the first, but no independent scanner can guarantee the second. The build process validates our bundled JSON datasets for structure, accepted fields, duplicate aliases, and warning levels.

Deterministic regression tests cover known ingredient relationships, barcode validation, GS1 decoding, and false-positive cases. The app also includes an offline self-test in App Health.”

For users, warnings identify their source, analysis coverage shows matched and unmatched text, and external records retain their source attribution. Most importantly, LB reminds users to compare important results with the current physical packaging and official information.

When building the tech is the easy part

Bálint is building and shipping a consumer product at an age when many developers are only beginning their studies.

“I’m comfortable spending huge amounts of time solving technical problems. Communication, outreach, and many of the practical aspects of running a public product are much harder for me.

I’m the developer and product owner, but I’m not doing everything alone. My parents have supported me with testing, communication, research, outreach, and the practical work involved in releasing a real product. I wouldn’t have been able to do it in the same way without them.”

LB is free, account-free, and ad-free, and it’s built without a conventional marketing budget, sponsors, or advertising revenue.

“My parents have contacted allergy organisations, foundations, doctors, and newspapers in many countries, sending several hundred emails. Often there was no response. In some cases, organisations asked for payment to include the free app in a newsletter,” said Bálint.

Even app-store distribution has produced unexpected challenges. At one point, a Google Play testing requirement meant finding 12 testers who would use the app for two weeks and keep it installed.

“Our first attempt failed because we had only 11. There have been many moments when the technical problem wasn’t actually the hardest one. The technology was often easier for me than getting people to see what I had built,” he shared.

When traditional education doesn’t fit

Mónika raised another significant aspect of Bálint’s learning story. At school, he was often judged against a traditional structure that didn’t fit the way he thinks and processes information.

She explained:

“Bálint is autistic, and he doesn’t always approach a task by asking, ‘What is the expected way to do this?’ His instinct is often closer to, ‘What actually works, and is there a better way?’

At one point, someone in the German school system told him he would probably never achieve more than a Hauptschulabschluss, or HSA. That prediction clearly didn’t describe his potential.

For me, that’s one of the most important parts of his story: don’t mistake someone’s difficulties for the limits of their potential.

His way of thinking can make some traditional situations difficult, but that same way of thinking can be extremely valuable when he’s solving technical problems.”

Building differently, not fitting a template

Bálint admits that being a developer doesn’t mean everything else is easy.

“I can become very stressed by things that other people might consider simple, and sometimes I can’t easily control that stress. I’m autistic, and I can hyperfocus very deeply on one thing at a time. When that happens, almost all my attention goes towards the problem I’m trying to solve. 

I was also born with right-sided clubfoot, and I have some articulation difficulties. These are parts of who I am, but I don’t want them to define what people think I’m capable of. I don’t think people should have to fit a standard template to be taken seriously.”

Keeping the consumer app free

While Bálint wants to keep the basic consumer version of the app free, he’s open to the underlying technology becoming an SDK, API, or licensed component for retailers, accessibility services, consumer-goods companies, or other product-discovery systems. That could include collaborations around scanning, product identification, label understanding, accessibility, or parts of the analysis engine.

“Any collaboration would need to preserve the principles behind LB: user agency, privacy, transparent sources, and honest uncertainty. I wouldn’t want the technology turned into another advertising or behavioural-tracking layer.”

Responsible business partnerships could help support the free consumer product rather than replace it.

What comes next

Bálint wants to keep building useful things, learning, and improving. He’s open to honest technical criticism, collaboration, and opportunities to work with people interested in what he builds, whether that means developing LB further or contributing his programming skills to other projects.

From her perspective as his mother, Mónika wants Tech.eu readers to understand that Bálint may not always express himself perfectly in words.

“But he expresses himself extraordinarily well through what he builds.”

Two German DefenceTech companies used Chancellor Friedrich Merz’s visit to Kyiv this weekend to deepen their links with Ukraine, in a sign of how the country is becoming an increasingly important development and manufacturing base for Europe’s next generation of autonomous defence systems.

As announced on Sunday, Munich-based drone company Quantum Systems is set to have several tens of thousands of interceptor drones financed by Germany under its winter 2026/2027 military assistance package, with the systems to be manufactured in Ukraine.

Meanwhile, Munich-based ARX Robotics and Ukrainian DefenceTech company Roboneers have expanded their existing relationship into a strategic partnership covering the integration and joint development of unmanned ground systems.

The agreements formed part of a broader push during Merz’s 4 October visit to increase German-Ukrainian cooperation in defence technology and production. Germany also announced around €1 billion in additional military assistance during the visit.

For the European startup ecosystem, the notable part is not just the procurement volume. Both deals build on a model in which German capital and industrial capacity are increasingly being combined with Ukrainian engineering, manufacturing and direct operational feedback.

Capital moves into defence

The two agreements also come against a substantial increase in capital flowing into German defence technology.

EU-Startups’ 2026 coverage includes more than €1.2 billion in disclosed funding across Quantum Systems and a group of European companies working in adjacent areas such as autonomous systems, drone operations, aerial intelligence, precision guidance and counter-drone technology.

Germany accounts for most of that total: Quantum Systems raised a €1 billion Series D in July, following a separate €150 million financing package in February, while Hannover-based INLEAP Photonics secured €20 million for laser-based drone defence and Berlin-based SPREAD AI raised €25 million to expand engineering software used across defence, aerospace and heavy industry.

EU-Startups has also followed both companies in the current agreements over several years: Quantum Systems previously raised €160 million and a further €180 million in 2025, while ARX Robotics’ funding history includes a €1.15 million pre-Seed round in 2023, a €9 million Seed round in 2024 and a Series A that reached €42 million in 2025.

The figures point to a German DefenceTech ecosystem in which autonomous platforms and the software, sensing and counter-drone technologies around them are attracting increasingly large pools of private capital.

Production shifts closer to the frontline

Founded in 2015, Quantum Systems develops autonomous aerial systems and accompanying software. Its Ukrainian footprint predates the latest order. Quantum Systems opened a production facility in Ukraine in April 2024, later expanding local manufacturing capacity and its Ukrainian workforce. By February 2025, the company said the site employed 80 people and was preparing to increase that number to 120 while producing locally manufactured Vector reconnaissance drones.

The newly announced interceptor programme pushes that localisation considerably further. The drones were developed by Quantum WIY Industries, part of Quantum Systems’ German-Ukrainian network, and are intended to counter increasingly capable Russian attack drones.

Sven Kruck, Co-CEO of Quantum Systems, said: “Ukraine needs interceptor drones at industrial scale. By expanding production in Ukraine, we can respond faster to the immediate threat while building an industrial capability that will also strengthen Germany and its allies.”

A similar development is taking place on the ground. Founded in Munich in 2022 by former Bundeswehr officers Marc Wietfeld, Maximilian Wied and Stefan Roebel, ARX Robotics develops unmanned ground vehicles and Mithra OS, its software platform for connecting and autonomising military vehicles.

Its partnership with Roboneers is also moving beyond supplying equipment into shared production and development.

In June, the two companies created ARX Industries, a joint venture designed to manufacture the Rys Pro unmanned ground vehicle in Ukraine and Germany. ARX said at the time that the venture aimed to produce several thousand systems in its first year before scaling towards tens of thousands annually.

The new agreement signed in Kyiv extends the relationship into deeper technical integration and joint development.

Marc Wietfeld, CEO ARX Robotics said: “Software-defined unmanned defence solutions are key for landforces on a modern battlefield where every action can be seen by the enemy. Together with Roboneers we provide the Ukrainian forces with a robust but smart UGV fleet at scale and at the same time ensure that the lessons learnt from the battlefield are incorporated into the landsystems development of other western armies.”

A wider innovation pipeline

These partnerships sit within a wider infrastructure being built around Ukrainian defence innovation.

In May, Germany and Ukraine launched Brave Germany, a programme run with Ukraine’s Brave1 defence innovation cluster to provide grants to German and Ukrainian startups working across unmanned systems, AI, communications, laser and missile technologies.

Brave1 said in September that it had awarded more than 1,000 grants since 2023, worth a combined €122 million (UAH 6.2 billion), including support for areas such as interceptor drones and ground robotics.

During his Kyiv visit, Merz explicitly described the relationship as one in which German defence companies learn from Ukraine’s wartime experience while German and Ukrainian businesses establish joint ventures and manufacturing capacity. “German and Ukrainian companies are jointly developing technologies that benefit both countries. That makes us safer and stronger,” he said.

From battlefield to European market

For startups, Ukraine is consequently becoming more than an end market for European defence technology. It is emerging as a place where systems can be developed, manufactured, deployed and iterated in unusually short cycles.

The Quantum Systems and ARX Robotics announcements show what that model can look like at industrial scale: European investment and manufacturing capacity paired with Ukrainian engineering and battlefield experience, with technologies developed for an immediate defence requirement feeding back into the wider European market.

The post German startups deepen Ukraine ties over weekend as innovation moves closer to the frontline appeared first on EU-Startups.

OpenAI is testing a visual ad format during image generation in ChatGPT, placed by guardrails that assess whether a conversation is emotionally vulnerable or sensitive before an ad appears. Ads already run in 31 European countries, and ChatGPT’s designation as a very large online search engine means it must publish a public ad repository by […]