Warsaw-based Jutro Medical, an AI-first primary care operator combining online and in-person care, has raised €24 million in new funding led by Warsaw Equity Group, with participation from Vinci, naturalX Health Ventures, Fluent Ventures, Aternus, KAYA VC, and Inovo VC. The round also includes a debt component from mBank and Orbit Capital. The raise extends the company’s previously announced Series A, bringing the total to €36 million. Founded in 2020, Jutro Medical has grown from a single clinic focused on technology-enabled care into an integrated primary care operator with its own electronic health record (EHR), standardised clinic operations, and AI-based tools. In its first four years, Jutro Medical prioritised building a proprietary EHR and the underlying software and data infrastructure used across its clinics. The company says this foundation has enabled it to add an AI layer more efficiently, allowing AI agents to support administrative tasks such as intake and drafting visit documentation. Clinicians begin appointments with relevant context prepared, review and adjust information as needed, and retain responsibility for all clinical decisions. Use of AI is optional, and patients can choose a traditional appointment. The company’s approach is positioned against broader pressures in primary care, where workforce shortages, rising administrative workloads, and uneven access continue to limit capacity. Primary care spending in Europe exceeds €200 billion annually, including around €9 billion in Poland, yet many clinics still rely on manual or paper-based processes that can slow access to care. Jutro Medical follows an acquisition-led strategy, bringing acquired clinics onto a shared operating and technology platform that includes a common EHR, workflows, and AI tools. The company says it added nine clinics to its network this year and is targeting around 20 acquisitions annually, with the aim of supporting more consistent service delivery and faster integration. By running our own clinics on our own software, we’ve learned firsthand which tasks can be handled by AI. Instead of hiring more staff, we now build AI agents that do the same work – freeing clinicians to practice medicine, not paperwork. These agents already manage thousands of patients interactions every month, says Adam Janczewski, founder and CEO of Jutro Medical. The new capital will be used to support further clinic acquisitions in Poland and to expand the model into other European markets. Jutro Medical also plans to continue developing AI agents to automate additional administrative and operational tasks, while clinicians focus on diagnosis and treatment. Over the longer term, the company aims to build a pan-European primary care operator by consolidating a fragmented market of small practices.

A Berlin-based audio startup, which leverages its own AI models to let users generate synched sound for video, has raised $41m in a seed round, led by Index Ventures and Andreessen Horowitz. The funding round in Mirelo also lured in Berlin-based investor Atlantic and California-based VC TriplePoint Capital. Mirelo has raised around $44m to date and has bagged angel investment from several tech luminaries, including Mistral co-founder and CEO Arthur Mensch and Revolut executive Antoine Le Nel. Mirelo, which has a 10-strong team, was founded by a pair of former musicians, CJ Simon-Gabriel, and Florian Wenzel, who met as AI researchers at Amazon. Mirelo’s big play is that while AI has transformed the creation of text, images and video, sound is lagging behind. It points out the laborious process of adding music and audio to visuals, involving creators and sound designers spending hours searching stock libraries and manually syncing effects. Mirelo, founded in 2023, has developed its own AI models for sound in video. It says a user can upload any video, and in a matter of seconds, Mirelo produces matching audio for anything happening on screen.  It says its sound generation tech is a good fit for AI-generated videos or the gaming worlds. It builds its own AI models from scratch, training them on data for which it says it has licensing deals in place. Its customers are typically individual creators and small studios while its API is used by companies wanting to leverage its models into their platforms or tools. Mirelo recently released a new video-to-sound model, Mirelo SFX v1.5, which it says can generate various soundtrack versions faster than real-time. The startup says its models require 50 times less compute than typical LLMs. The startup will use the funds to advance its tech and try and grow its customer base. Simon-Gabriel, Mirelo CEO, said: “Think of the difference between talkies and silent films – video without sound has so much less feeling and atmosphere. “Mirelo’s first step is about democratising access, empowering everyone to create the sound that their (AI) videos deserve. "But we’ll also empower professionals to rework audio, to do more of what they love, to be more expressive and imaginative in what they can achieve, while handling the boring stuff such as synchronisation. Our bigger mission is to become the audio layer for all visual content across videos, gaming, social media, films and beyond.” Wenzel said: “There’s a deep affinity between music and engineering; maybe that’s why so many of Mirelo’s team are musicians, and why musicians have always been early adopters of new technology. “There’s something about the intersection of mathematical precision and expressiveness that seems to draw people to both fields.” Guido Appenzeller, partner at Andreessen Horowitz, said: "To date, a16z has invested in multiple world-leading generative models each with a different focus area. Mirelo is tackling one of the most technically challenging and least explored areas of generative media: a specialised model for sound effect creation. “CJ and Florian have assembled a research-driven team whose breakthroughs in tokenisation, data curation, and conditioning rival far larger efforts and we’re excited to back Mirelo as they scale their technology for the next generation of video models.”

Iconic, an interactive entertainment and AI-native platform company, has raised $13 million in its seed round, co-led by venture capital funds Kindred and Northzone, with further investment from leading industry players.  The round also brings together a highly curated group of the world’s top AI, gaming, and system engineering leaders from Google, Meta, Disney, DeepMind and OpenAI. Founded by John Lusty and Junaid Hussain, Iconic began in 2023 as a small, technically focused team exploring how advances in AI could enhance human creativity and transform the way players interact with and experience games.   From the outset, the team was equally driven by a desire to improve life for developers, enhancing the creative process whilst reducing the rapidly increasing cost and complexity of building games, and it is this ethos that attracted CEO Andrew Bowell, formerly Product Head at Unity. Through its pioneering on-device AI technology, Iconic is bringing intelligence, agency, and personalisation to the heart of the player experience, allowing game studios to build entirely new genres of games whilst driving down development costs. Earlier this year, Iconic debuted the demo of its voice-driven narrative puzzle game. It enables every word spoken by players to actively shape the world they are playing in.  By applying SLLMs, the technology ensures that internet connectivity is not required, allowing game play across a range of environments without cloud costs or privacy issues. Since launching with NVIDIA at Gamescom, The Oversight Bureau has received strong, consistent praise for its unique level of immersion and responsiveness. With early prototypes demonstrating the potential of voice-driven, character-rich worlds powered by on-device intelligence, this became the backbone of Iconic’s formal launch in 2024, bringing talent from Unity, Meta, Sony, Microsoft, Cambridge University, and major gaming franchises, including GTA and Star Wars.  Andrew Bowell, CEO of Iconic, said, “Our voice-driven gameplay experience is transforming traditional entertainment, utilising novel technology and innovative digital systems to enhance creativity, revolutionise the player experience, and redefine the boundaries of gaming. We are excited to announce our successful seed round led by Kindred and Northzone, with further support from leading industry players, including Google, a testimony to Iconic building the next iteration of interactive entertainment.”

Emmi AI is an Austrian deep-tech company that builds AI-driven physics simulation technology to accelerate engineering processes in fields like Fluid Dynamics, Multiphysics, and Solid Mechanics. For a company doing this kind of work, how people collaborate matters as much as the tech itself. And it turns remote work on its head with its hybrid, remote-first approach.  Every month, they fly everyone to Linz, Austria, for a week. I spoke to Miks Mikelsons, COO, to learn all about it. A research-heavy team, with applied outcomes in mind Today, Emmi AI employs around 30 people, with research forming the backbone of the organisation. Roughly two-thirds of the team come from academic or scientific backgrounds. “We’re very research and science-heavy,” says Mikelsons. “About 20 of our people come from academia.” Around 40 per cent of the team is based across different locations such as Austria, London, and other parts of Europe. Competing for talent without forcing relocation Once a month, for a full week — always the first week of the month, Emmi AI brings everyone together to the same location and covers all the costs of travel and accommodation. Mikelsons  asserts:  “We’d rather spend an extra €1,000 per person per month on bringing people together than invest in the fanciest office or compete in the most aggressive hiring markets. This allows us to attract talent who might not want to relocate. “We’re still distributed across Europe, but this model works well here. It would be harder across the US, but in Europe it’s very achievable.” For someone deciding whether to stay in the US or return to Europe, this model is very compelling. For example, the company hired someone originally from Spain who had been in the US, at the University of Pennsylvania. Competing on culture, not compensation From the beginning, Emmi Ai decided that as a scaling company in one location, it needed to differentiate. “Especially for research-driven companies, culture matters a lot. We wanted strong chemistry and bonding early on, so we invested in being together." “We’re not the company offering the biggest salaries in AI research right now. Some people are getting extremely high compensation offers, and we don’t compete on that,” Mikelsons admits. And the result is that people recommend the company to their networks. “What we offer instead is a way of working and a culture people value. That’s how we’ve been able to attract talent from places like Oxford and Cambridge.” In-house tech by an all-star team  Emmi AI has developed its technology entirely in-house, with its core architecture built in Austria by co-founder and Chief Scientist Johannes Brandstetter and his research team. Brandstetter previously worked on Microsoft Aurora, widely regarded as the world’s first foundation model for weather forecasting. Following the breakup of that original team, the researchers went on to found their own companies. Brandstetter chose to return to Austria from Amsterdam to build Emmi AI. “We have our own technology stack,” says Miks Mikelsons, COO of Emmi AI. “The architecture was built by Johannes together with his team in Austria.” Deeptech for real-world problem solving  “Johannes is a pure researcher,” Mikelsons explains. Unlike many startup founders, Brandstetter comes from a purely academic background, with no prior business or operational experience. Emmi AI’s leadership team is intentionally structured to balance those strengths. “Together with Arno Hollosi, our CTO, and myself focusing on operations and scaling, we bridge deep research with real-world deployment.. As we always say, we apply groundbreaking research to real-world problems and focus on business needs,” Mikelsons adds. “That combination is still relatively rare.” How Emmi AI is rethinking how physical systems are designed and tested In simple terms, Emmi AI uses AI to run complex physical simulations — like fluid flow, heat transfer, structural mechanics, and other engineering problems — orders of magnitude faster than traditional methods. According to Mikelsons. “People sometimes ask,:'What is simulation and what does it do in engineering?' I always tell the story that a hundred years ago, people tested designs by simply crashing them into a wall. Then came wind tunnels, where you could test how a design behaves under air pressure. Later came numerical simulation — equations and formulas that calculate how a particular design will behave in the real world.” However, this process is very expensive and computationally heavy and can take days or weeks.  “With AI, we can now do it in seconds or minutes. That changes the way you design and work in engineering entirely,” he shared.  Industrial use cases: where simulation meets reality The company is active in sectors such as automotive and energy.  “For example, we have customers producing power transformers: those big machines you see near cities that convert high voltage to low voltage. They’re full of metal and oil, and they involve very complex behaviours like transient simulations.” Large grid assets such as power transformers are designed to last for decades, but they are also slow to replace. That reality shapes how electricity networks are operated today. “If you order one of these machines today—say from Brazil or another country — you might get it five years from now,” says Mikelsons. With replacement timelines stretching into years, grid operators have little margin for error. Assets are therefore run cautiously, often well below their theoretical limits, to minimise the risk of failure. “Because of that, grid operators run these systems very conservatively.”  AI-driven simulation offers a way to change that dynamic. By modelling how equipment behaves under different conditions, operators can gain a far more precise understanding of performance and risk. “What we can build are models that simulate operational behaviour,” Mikelsons says.  “That allows operators to anticipate challenges and actively control how these systems behave in practice.” Rather than relying solely on conservative assumptions, grid operators can use simulation to make informed, real-time decisions—unlocking." Letting the team self-organise In terms of employee adoption, Mikelsons asserts that it's all about setting clear rules and planning upfront. “From the interview process onward, people know exactly how this works. It’s always the first week of the month. It’s always the same location. Costs are covered. People really enjoy it. Some take the night train, others fly in. The organisational overhead isn’t actually that big.” In terms of logistics, the company’s office in Linz fits around 25 people comfortably, maybe 30 at a stretch and is hot desking by design.   The company is not aiming for hundreds of people, “but maybe 50 by the end of the year.” Emmi AI also organises activities outside work, such as dinners, bouldering, and spending time in nature.  “We try to make it special without wearing people out,” shared Mikelsons. One of the secrets is that the team increasingly self-organises. At the beginning, management structured everything. Now people suggest activities, breakfasts, and experiments. They try things, see what works, and adjust. For people thinking of doing something similar, Mikelsons advises that clarity is key. You need to be clear about the identity you want to build: “If you’re fully remote, set clear rules for that. If you meet once a year, plan everything around that. Budget, communication processes, meeting structures — everything follows from that decision." Ultimately, Emmi AI believes that the best companies don’t invest only in the next fundraising round or the next customer. They invest in how they collaborate and how they work together.

Most organisations do not wake up one morning and decide to overhaul how they manage messaging and streaming. The shift usually begins with something far less glamorous. A delayed release because a queue was not provisioned on time. A compliance reviewer asking for audit evidence that takes days to assemble. Or a capacity scare on a Kafka cluster that no one saw coming. The familiar moment in a war room, when everyone realises the issue is happening somewhere between five different platforms and no one has the full picture, is also a common trigger. These incidents are usually dismissed as “part of the job”. They sit quietly in the background, tolerated but not solved. They accumulate, and eventually the realisation sets in. The organisation is operating its most critical digital plumbing through a system of fragmented tools, tribal knowledge, spreadsheets, screenshots, and luck. The good news is that there is a way out of this. A new operational model is emerging that allows large organisations to run their messaging and streaming estates with far more efficiency, resilience, and auditability than what has been possible before. But before we get there, we need to understand how the current model became so strained. The Reality No One Talks About: Middleware Has Become Too Fragmented to Manage Conventionally If middleware were still a neat, single-platform world, most enterprises would not have a problem. But the world changed. Acquisitions happened, and digital programmes layered new technologies on top of old ones. Critical systems stayed on MQ, and cloud teams adopted native messaging. Modern apps moved to Kafka. Integration teams added Solace, and microservices brought in RabbitMQ. Different business units made different choices at different times. Now most organisations operate a collection of platforms that were never designed to be viewed or run together. This creates three immediate problems. 1. Operational Fragmentation Every platform has its own way of working. Kafka has partitions and consumer groups, and MQ has channels and queues. Solace has VPNs and message spools, and cloud brokers follow their own patterns. Tools are inconsistent, naming conventions drift, and monitoring is disconnected. Incident diagnostics spread across too many places, and the operational view becomes blurred. Teams spend time stitching context instead of solving problems. 2. An Unsustainable Human Workload The people who understand this infrastructure are both scarce and overloaded. They are asked to provision objects manually, review ACLs, check configurations, investigate drift, run failovers, and validate release plans. They also decode logs, triage incidents, and locate the source of message failures. Repetition becomes the norm, and heroics become the expectation. This is not a scalable operating model for a multi-platform estate. 3. Blind Spots in Risk and Compliance Most organisations can prove that “something happened,” but not necessarily “what happened,” “where it happened,” or “why it happened”. Regulators and audit teams want traceability, consistency, and evidence. Middleware estates rarely provide it. A fragmented environment makes even basic audit questions difficult. Who changed this configuration? Which systems participated in this transaction? Was the failure internal or external? Did messages retry, and was the security model consistent? These questions require coordinated visibility, which is difficult when data is spread across incompatible logs and systems. This gap is becoming more dangerous as regulations tighten around operational resilience. The Hidden Costs: Waste, Delay, and Defensive Operations. The consequences of this operating model are often underestimated because they are dispersed across many teams. Infrastructure Waste Most organisations cannot see true utilisation across all messaging technologies. They over-provision Kafka storage and leave unused queues and topics running for years. They maintain oversized clusters or duplicate environments because it is easier than cleaning up. Storage, compute, and licensing bills grow gradually. They are rarely challenged because no one has system-wide context. Slow Delivery and Change Friction Provisioning a new topic or queue should take minutes. In most enterprises, it becomes a mini-project involving approvals, compliance reviews, manual configuration, and cross-team coordination. Release cycles slow down not because of application development, but because of the plumbing beneath it. Incident Resolution Drag A business-critical slowdown might start in one platform and surface in another. Without visibility, teams chase symptoms. War rooms stretch into hours, and incidents that should be diagnosed quickly turn into cross-functional investigations. Mean Time to Recovery expands, and customer-facing systems suffer. Compliance Overhead Audit requests become painful exercises in log mining, screenshot gathering, Excel reconciliation, and interpretation. Evidence gathering interrupts real work. Compliance results take weeks. Reviewers lose confidence in the underlying controls, and findings start appearing in reports. These costs accumulate quietly but powerfully. A New Pressure Point: Auditability Has Become Strategic A decade ago, auditability was mostly an internal concern. Today it is a board-level conversation. Regulators across financial services, healthcare, energy, and the public sector now require organisations to prove the resilience and traceability of their operational systems. Messaging and streaming platforms sit at the heart of these systems. They remain some of the least auditable components in the digital landscape. Why Auditability is so Hard Today There is no unified audit trail. Kafka, MQ, Solace, RabbitMQ, and cloud brokers all produce different artefacts, and correlating them manually is slow and error prone. Configuration drift is constant, and even small changes create gaps in compliance evidence. Without unified configuration intelligence, drift remains invisible. RBAC inconsistencies multiply risk. Each platform has its own security model, and proving consistency across them is almost impossible manually. Incident reconstruction takes too long. When things go wrong, teams must recreate the past using logs from multiple systems, often with incomplete or misaligned timestamps. Compliance slows the business. Approvals, reviews, and evidence all take longer. This becomes a tax on every change and every release. Without built-in auditability, a middleware estate simply cannot operate at the speed the business requires. The Shift: Lean Operations as a Strategic Imperative Lean operations is not a slogan, nor is it about doing more with less. It is the recognition that the old operating model cannot sustain the scale, complexity, and regulatory expectations of modern middleware estates. A lean model has four defining characteristics. 1. Unified Visibility Teams need to see the entire estate in one place. This includes health, flows, dependencies, performance, lineage, configuration, and security. It means actual end-to-end operational clarity, not summaries or partial views. Without this, speed and reliability are impossible. 2. Automation and Controlled Self-Service Provisioning, validation, drift detection, ACL checks, failover routines, and compliance evidence should not rely on manual effort. Automation removes friction. Policy-based self-service allows developers to work faster without increasing operational risk. 3. Resource Optimisation A lean model gives clear insight into what is oversized, under-utilised, misconfigured, or simply no longer needed. The result is lower infrastructure cost, more predictable capacity planning, and fewer performance surprises. 4. Built-in Auditability Audit trails must be complete, consistent, and automatically captured. Configuration history must be reliable. Access models must be validated across platforms. Incident reconstruction must be fast, and evidence must be exportable without effort. Lean operations is what happens when you combine these principles. It is an operating philosophy supported by the right platform capabilities, not a tool. The Future State: Middleware as a Governed, Efficient, and Transparent Layer Organisations that embrace this model experience a radically different operational reality. Release cycles become smoother because provisioning and compliance do not hold them back. Outages become less frequent and shorter because teams can identify root causes quickly. Platform teams spend less time firefighting and more time improving. Infrastructure costs fall because utilisation is visible and manageable. Audit requests that once took days are delivered in minutes. Regulators gain confidence in the organisation’s operational discipline. The biggest shift, however, is cultural. Developers stop waiting for middleware teams. Middleware teams stop playing catch-up, and compliance teams stop battling for evidence. Everyone operates with the same truth, the same visibility, and the same level of control. This is the future state that progressive organisations are now moving toward. So What Makes This Future State Possible? Very few platforms are capable of supporting the operational model described here. Most observability tools focus on metrics rather than message flows. Most monitoring solutions are tied to a single platform. Integration tools typically manage connectivity, not operations. Open-source utilities provide valuable functions but lack governance, auditability, and cross-platform consistency. Cloud services help but introduce their own silos. To reach a fully lean operating model, organisations need something that is still rare. They need a unified operational command plane that spans every messaging and streaming platform in the estate. It must provide: A single operational view across all technologies. Transaction-level lineage and flow analysis. End-to-end audit trails. Consistent configuration and security governance. Automated provisioning and validation. Self-service within guardrails. Capacity and cost intelligence. Multi-cloud and hybrid compatibility. Integration with existing processes, not disruption of them. When these capabilities come together, the fragmented middleware world becomes manageable. It becomes transparent, and it becomes compliant. This is the model that forward-thinking organisations are now adopting. This is exactly the model made possible by meshIQ Core. meshIQ appears at the end of this story not because it is an afterthought, but because the logic leads naturally to it. Once you understand the operational, architectural, and compliance realities of modern messaging and streaming, the need for a unified control plane becomes obvious. meshIQ is one of the few platforms purpose-built to deliver it. For many organisations, it has become the turning point from reactive, high-cost operations to a lean, governed, and resilient operating model. Want to Explore This Further? If you want to understand how a lean operating model could apply to your own messaging and streaming landscape, meshIQ offers briefings and assessments for platform, architecture, and risk teams. You can start the conversation at meshiq.com/contact.

Europe's first National Security VC firm, MD One Ventures and Randox, a global diagnostics and healthcare company from the UK and Ireland, today announce the launch of Randox for Builders, a security and biotech incubator and accelerator. Randox for Builders gives early-stage companies the funding and hands-on support they need to grow faster.  At its core, Randox for Builders is about strengthening national resilience by developing technologies that will shape the future security and health of the UK and its allies.  By fast-tracking solutions with real-world impact, the incubator aims to ensure that the next generation of breakthrough capabilities is built, tested and deployed far earlier than traditional systems allow. Selected founders and their startups will gain access to Randox’s global leadership in diagnostics and biotechnology, leveraging resources rarely accessible to early-stage ventures, including: Access to advanced laboratories & manufacturing facilities    Clinical trials and validation Commercial partnerships Distribution channels Regulatory framework advice and support World-leading resources for IP and Research Deeply established routes to market - B2B and B2C Alongside investment, founders get instant access to a ready-made network of world-class scientific experts, R&D, and commercial resources.  The MD One Ventures team includes Co-founder Will McManners, who spent 10 years in the British Army, and served as an officer in a Specialist Military Unit, Commando and JTAC, before working at BlackRock, Investbridge Capital and Palantir. Alongside McManners, providing strategic oversight is Cecilia Fortugno, PhD, who serves as both Vice President and Chief Operations Officer at Randox Biosciences and the Senior Technical Advisor for the new accelerator. Wil McManners, Co-founder of MD One Ventures, commented: "This is not a traditional accelerator, it's a strategic partnership designed to de-risk and accelerate companies that solve national security and public health challenges. The access our founders receive to Randox's infrastructure is literally a money can't buy opportunity. We are looking to support world-class founding teams that can deliver solutions to fundamental issues affecting our National Infrastructure, Health and ultimately, Security". Dr Cecilia Fortugno, Vice President and Chief Operations Officer at Randox Biosciences and the Senior Technical Advisor for Randox for Builders, said: "For forty years, Randox has invested deeply in R&D to drive diagnostic and preventative healthcare. This program with MD Ones is a natural extension of that mission. By opening our technical infrastructure to the next generation of innovators, we are ensuring that the solutions to future health and security challenges are being built and scaled rapidly right now." The incubator has already started investing, with initial companies including Untap Health, which delivers automated wastewater-based diagnostics and Airfinity, which provides a health intelligence and bio risk forecasting platform, integrating AI-driven simulations.

As renewable generation expands and conventional baseload plants retire, electricity supply has become more volatile — amplifying price swings and increasing pressure on grid stability. Battery energy storage systems (BESS) address this imbalance by absorbing excess power when generation is high and discharging it when demand peaks. In doing so, they stabilise the grid, reduce renewable curtailment, and smooth electricity prices for both consumers and businesses. As a result, battery storage is now a bankable infrastructure asset. Today, Tier-one suppliers, primarily from China, offer containerised systems with performance warranties extending up to 20 years. Those guarantees underpin project-finance structures that can support up to 70 per cent debt financing — something that would have been unthinkable when the technology was still regarded as experimental. I spoke to Nikolas Samios, Managing Director, PT1, to understand the promise and opportunity of this rapidly evolving asset class. PT1’s thesis: Upgrading the physical world PT1 is an early-stage venture capital fund launched in 2018, focused on upgrading the physical world. Software and AI now underpin almost everything, but there is still a vast physical layer beneath that — energy systems, infrastructure, the built environment, robotics — that needs to evolve alongside it, and that’s where the Firm steps in. PT1 has made around 27 investments in Europe across two funds, and is headquartered in Berlin with a second office in London. It's now planning a third fund vintage for 2026.  PT1 focuses on three core areas: Electrification of everything, including energy, transport, and industrial systems. AI and robotics applied to the physical world, especially where labour shortages exist, and automation hasn’t yet penetrated — for example, construction. Infrastructure resilience, including climate resilience and the protection of critical assets such as grids and pipelines. The Firm doesn’t invest in defence per se, but Samois acknowledged that surveillance, maintenance, and monitoring of critical infrastructure is becoming increasingly important. Batteries inflection point Batteries often outperform gas-powered plants by responding faster, emitting nothing, and avoiding many of the siting and permitting constraints that plague thermal assets. “Batteries themselves are decentralised, modular, and quick to deploy. At scale, they also dampen peak pricing, lowering average electricity costs system-wide. That broader economic benefit helps explain the growing enthusiasm from both policymakers and investors.” Why PT1 followed the data, not the impact narrative Samios admits that PT1 were never impact-first investors. “Instead, we started by looking at the data.” Germany’s nuclear exit, coal phase-outs across Europe, and the acceleration triggered by Russia’s invasion of Ukraine have all amplified this shift toward battery storage. According to Samios, the second major driver was cost: “Battery prices fell much faster than even optimistic forecasts from consultancies like McKinsey or BNEF. Chinese industrial policy created massive manufacturing capacity, pushing prices down week by week. When you combine grid volatility with falling battery costs — and layer in AI-driven optimisation — you reach a point where battery storage becomes commercially viable without subsidies. That was the key insight: this could become a new, standalone asset class. One that large institutional investors would eventually allocate to, once risk and bankability were proven.” He admits that traditional renewable infrastructure has largely been commoditised. But, it’s increasingly hard for infrastructure funds to achieve double-digit internal rate of returns (IRRs) in solar or wind without taking emerging-market risk: “Battery storage changes that. It benefits from volatility rather than being harmed by it. And as volatility is structural, not temporary, the opportunity persists for decades.  Our role as an early-stage VC is to identify these asset classes early, take the initial technology and execution risk, and help companies mature to the point where they can absorb large pools of institutional capital.” For Samios, where innovation really happens now is in system control and trading: “Early battery projects followed a simple arbitrage model — charging during periods of excess solar and discharging at night.  Today, AI-driven trading systems analyse vast volumes of real-time data across multiple European electricity markets, optimising decisions in 15-minute intervals. Machines now outperform even the best human traders in this context, because they can process weather patterns, grid constraints, outages, and market signals simultaneously. That intelligence directly translates into higher returns on the same physical asset.” The Texas oilman test  Battery storage plays a different role in energy trading because it does not rely on subsidies in most markets.  According to Samios:  “That insulation from political swings is critical. At PT1, we focus on climate technologies that have reached a commercial tipping point — where they make economic sense even to conservative investors. A simple test we use is whether a Texas oilman, advised by Goldman Sachs and McKinsey, would invest purely on financial grounds. If the answer is yes, scale follows — and with scale comes impact. Battery storage passed that test.” Early conviction, institutional scale In just one week this September, two portfolio companies from PT1, Terra One and Voltfang, secured €1 billion to finance large-scale battery projects in Germany.  PT1 was one of the first institutional investor in both companies back since 2022, spotting the need for grid-scale storage before it became mainstream.  Terra One raised €150 million mezzanine financing, triggering an additional €500–600 million in project debt from banks, unlocking €750 million for ~3 GWh of new capacity “This is enough to power 20 per cent of German households for one hour,” shared Samios.  German battery specialist Voltfang launched a long-term partnership with infrastructure investor Palladio Partners to develop, finance and operate large-scale battery storage systems across Germany, targeting around €250 million in investments by 2029. This scales Europe’s largest second-life battery factory into repeatable grid projects. Flexibility is critical for risk mitigation PT1’s investment in Voltfang reflects the firm’s view that flexibility is a core form of risk mitigation in energy storage. From a venture perspective, Samios argues that the appeal lies in business models that are not locked into a single supply pathway.   “What we like about companies such as Voltfang is flexibility,” he says. “They’re not solely dependent on second-life batteries; they’ve built systems that can integrate batteries from multiple sources — unused first-life inventory, surplus stock, and second-life EV batteries that still retain 80 to 85 per cent of their original capacity.”  For stationary storage applications, energy density is far less critical than it is in vehicles, making second-life batteries particularly compelling.  This multi-source strategy improves supply resilience, lowers the carbon footprint of storage systems, and strengthens the overall investment case — especially for customers with explicit sustainability targets. Samois believes that in more liberalised markets in Germany, Australia, and parts of the US, private capital is clearly leading. Renewable energy created a globally investable infrastructure class, and battery storage now fits naturally into that same capital pipeline. “Battery projects can be structured very similarly to solar or wind assets, but with higher returns. That’s why large investors—pension funds, insurers, multi-asset managers—are moving quickly once bankability is demonstrated.” In contrast, gas peaker plants (power plants that generally run only when there is a high demand) require state guarantees to be investable, because they sit idle most of the time. Batteries operate autonomously, generate revenue continuously, and stabilise the grid without public subsidies. A broader European momentum builds behind storage Beyond the investments of PT1, over the past year, a wave of funding rounds and acquisitions has underscored growing investor confidence. In 2024, Swiss startup Libattion, which builds stationary energy storage systems using upcycled electric vehicle batteries, secured €14 million in funding, reflecting rising interest in circular and second-life battery solutions. Momentum has only increased in 2025. In January, large-scale battery storage developer green flexibility raised over €400 million to deploy utility-scale battery storage systems across Europe, marking one of the sector’s largest infrastructure-backed investments to date. Young company Scale Energy, developing decentralised industrial battery storage systems, raised a €2 million Seed round in February this year. There’s also momentum with companies like Delta Green which aims to turn ordinary European homes into a virtual power battery, enabling households to shift consumption, discharge batteries, and export rooftop solar at times of peak demand. However, this is a sector requiring deep domain expertise. You need founders who understand complex systems—regulation, infrastructure, financing, and often have decades of industry experience. According to Samios, the strongest teams combine that expertise with entrepreneurial ambition.  “Our role is not to build companies from scratch, but to support excellent teams with market access, strategic insight, and connections to later-stage capital. That’s where PT1 adds value: helping companies become bankable, scalable, and relevant to the largest capital pools in Europe.” Lead image: An edited Voltang battery storage photo.

IVFmicro, a University of Leeds spinout developing technology intended to improve IVF outcomes by increasing the quality and number of embryos produced per cycle, has raised £3.5 million in pre-seed funding. The round was led by Northern Gritstone, with support from the Innovate UK Investor Partnerships Programme. An estimated 1 in 6 couples globally experience fertility issues. IVF success rates remain relatively low, with around 25–30 per cent of cycles resulting in success for women under 35. Contributing factors include limitations in standard embryo culture processes, such as repeated handling, subjective embryo selection, and reliance on highly skilled operators, which can also add cost. In the UK, a single IVF cycle costs patients an average of about £5,000, and access through the NHS can involve long waiting lists and eligibility criteria. IVFmicro has developed a microfluidic device designed to support embryo culture and handling using very small volumes of nutrient-rich fluid. The company says the device can be used in any IVF treatment cycle and is intended to increase both the number of viable embryos available for transfer and the likelihood of implantation and pregnancy. IVFmicro reports a 10–15 per cent improvement in embryo quality and quantity. Helen Picton, Scientific Director and co-founder of IVFmicro, said the company is applying extensive research in reproductive biology to develop a practical and accessible approach aimed at improving outcomes for patients undergoing fertility treatment. Our goal is to make IVF more effective, more predictable, and ultimately more hopeful for those striving to start a family. The company plans to use the funding to support its next verification and validation phase, ahead of trials involving human embryos in fertility clinics.

Quantum Systems and Frontline Robotics today announced the creation of “Quantum Frontline Industries” (QFI), a German-Ukrainian joint venture that will establish Europe’s first fully automated, industrial-scale foreign production line for drones for the Ukrainian Armed Forces. Under the Build with Ukraine initiative, the new venture will mass-produce battlefield-proven multi-use drones developed by the Ukrainian company Frontline Robotics. 100 per cent of systems produced in Germany will be delivered to the Defence Forces of Ukraine in volumes defined by the Ukrainian Ministry of Defence. The production line will combine Ukrainian battlefield-proven technology with German industrial automation, creating a new model of cross-border defence co-production: the German Model. It will also open employment opportunities in Germany for Ukrainians. Quantum Systems will provide industrial infrastructure and production operations, while Frontline Robotics contributes licensed designs, training, and full lifecycle support in line with NATO standards. “Ukrainians have revolutionised the drone war, now we will revolutionise the industrial war together. For Quantum Systems, this is the logical next step of our proven track record in support of Ukraine. Together with Frontline Robotics, we will build on our proven experience and create Europe's first foreign production capacity at this scale for Ukraine.”*said Sven Kruck, Co-CEO of Quantum Systems Yevhen Tretiak, CEO of Frontline Robotics, shared:  "We see this as an important mission - to build the first Ukrainian-German defence joint venture with our partners Quantum Systems. We are confident that our example will pave the way for future collaborations of this kind. This cooperation will supply the Defenсe Forces of Ukraine with thousands of drones to drive back the Russian aggressor." Matthias Lehna, Managing Director of the new Joint Venture, stated: “QFI has three goals: Scale, Expand, and Create. Our new Joint Venture will bring together German engineering excellence with Ukrainian sense of urgency to mass produce urgently needed drones for Ukraine, expand its portfolio, and create new products for end users to push the boundaries of what is possible.”  Matthias Lehna will serve as the Managing Director of Quantum Frontline Industries. The 37-year-old served as an infantry officer in the German Armed Forces before joining the Cyber Innovation Hub in Berlin and later Quantum Systems as Director of Governmental Relations and Business Development in 2023. "Our drones are essential and in high demand on the frontline in Ukraine, which is why we need to scale up serial production. In wartime, finding safe locations for manufacturing inside Ukraine is difficult. Partnering with Quantum Systems allows us to expand our production capacity and strengthen the Defence Forces even further. We are truly glad to have such a partner by our side," said Mykyta Rozhkov, Chief BD Officer of Frontline Robotics.  etails on the location of QFI have not been made public due to security precautions.

Last week, we tracked more than 75 tech funding deals worth over €1.6 billion, and over 15 exits, M&A transactions, rumours, and related news stories across Europe.Click to read the rest of the news.

London-based AI startup PolyAI has raised $86 million in a Series D funding round.The funding round in the AI assistant developer for call centres was co-led by existing investors Canadian B2B software investor Georgian, London-based investor Hedosophia and US VC firm Khosla Ventures.Additional investors were NVentures (Nvidia’s VC arm), Sands Capital, Squarepoint Ventures, Citi Ventures, Point72 Ventures and the British Business Bank, which invested £15m ($20.1m). The British Business Bank is also a major LP in UK VC funds.The London-based startup, which did not declare a valuation following its raise, says it will use the funding to advance its tech, as it looks to increase its enterprise customer numbers.PolyAI works with major businesses, amid growing enterprise 24/7 demand for call centre support, which suffers from high attrition rates.It says it has over 100 enterprise customers, including Las Vegas casinos, Hilton and Marriott hotel chains, US delivery service FedEx, and the financial institution Unicredit.The University of Cambridge spinout has developed AI voice assistants for call centres which guide customers through enquiries, handling millions of calls, which can, some say, sound indistinguishable from human voices.PolyAI has worked with linguists to build voice assistants that reflect human speech patterns and the voices can be tailored by accent, tone and vocabulary. The tech can complete many tasks a customer service rep can, including taking payment information as well as names, addresses and account numbers.PolyAI uses its own proprietary AI models as well as models from major model companies like OpenAI and DeepSeek.Last year, PolyAI raised $50m in funding, valuing it at close to $500m.The Series C was led by investors Hedosophia and NVentures. It has previously raised $66m from investors.Nikola Mrkšić, CEO and co-founder, PolyAI, said: "This Series D financing is proof of the industry’s confidence in our abilities and the potential of our technology. “This investment will kick-start the next stage of our growth cycle and ensure that we can continue to deliver best-in-class technology for enterprises looking to transform their customer and employee experience.”Chancellor of the exchequer, Rachel Reeves, said: “We are investing in companies like PolyAI so we can grow the economy and create good jobs. Our backing, combined with our world‑leading universities, strong private investment, and our AI Growth Zones makes the UK one of the best places in the world to build an AI startup."

Zurich-based cybersecurity company Soverli has raised $2.6 million in pre-seed funding to develop a sovereign smartphone architecture designed to operate alongside Android and iOS for OEMs, enterprises, governments, and consumers. The round was led by Founderful, with participation from the ETH Zurich Foundation, Venture Kick, and cybersecurity industry figures. Based on more than four years of research at ETH Zurich, Soverli’s patent-pending approach is intended to run multiple operating systems simultaneously on a single device while keeping them isolated. The company says this enables a customizable and auditable sovereign OS to operate in parallel with Android on standard smartphones, with users able to switch between environments quickly. As a demonstration, Soverli showed Signal running inside its sovereign OS and said the setup isolates the app from Android and reduces the attack surface, with the goal of keeping messages confidential even if Android is compromised. The company adds that the approach requires no hardware modifications and is intended to work on current commercial smartphones without limiting typical use. Soverli positions the product within broader efforts, particularly in Europe, to strengthen digital sovereignty and operational continuity, arguing that smartphones remain a gap because secure communications and device management depend on the underlying OS. Early prototypes developed at ETH Zurich drew interest from public-sector and enterprise stakeholders as well as European manufacturers and integrators, contributing to the team spinning out as an independent company. The initial focus is mission-critical communications, with public-sector pilots underway in emergency response and critical infrastructure contexts. The company says an isolated environment can continue operating on a separate software stack if the primary OS is disrupted, helping keep communications and core workflows running. The same approach is also being evaluated for secure communications and enterprise bring-your-own-device use cases. With the new funding, Soverli plans to expand its engineering team, support more smartphone models, strengthen integrations with mobile device management systems, and scale partnerships with OEMs.

German quantum sensing company QuantumDiamonds GmbH has announced an investment of more than €150 million to establish a production facility for quantum-based chip metrology systems. The facility, planned for eastern Munich, is expected to receive significant public support from the German federal and Bavarian governments under the European Chips Act. QuantumDiamonds, a spin-off from the Technical University of Munich, develops and commercialises quantum sensing technologies for semiconductor metrology and failure analysis. Its patented Quantum Diamond Microscopy (QDM) systems are used by foundries and integrated device manufacturers worldwide. The company recently reported that QDM can identify internal defects in commercial package-on-package devices that are not detected by conventional techniques such as lock-in thermography and CT X-ray imaging. QuantumDiamonds says these results have contributed to increased demand for its systems. Initial deployments have been completed in Europe, with additional installations planned for Q1 2026 in the United States and Taiwan to support development and qualification work at major semiconductor manufacturers. QDM systems use nitrogen-vacancy (NV) centres in diamond to map electrical current with micrometre-level precision in a non-destructive manner and on short timescales, including within complex chip packages. The company positions this capability as relevant for advanced 2.5D and 3D architectures used in AI, mobile, and automotive electronics. According to Kevin Berghoff, CEO and co-founder of QuantumDiamonds, the investment marks the company’s shift toward global production: We’re building the tools the chip industry needs to inspect what was previously invisible—and doing it in Germany, with European IP and talent. The Munich site is expected to include sensor production lines for quantum-grade diamond substrates, cleanroom integration for QDM inspection systems, and joint development laboratories with semiconductor partners, alongside application support for fab integration and inline process control. The project has been designated as a first-of-a-kind facility under the European Chips Act. After evaluating alternative locations in the United States, including Phoenix, Arizona, the company selected Germany as its industrial base, citing access to specialised expertise, an established supply chain ecosystem, and public–private innovation frameworks in Europe. QuantumDiamonds has also received a start-of-works confirmation, indicating that construction can begin without affecting future eligibility for public funding, and allowing the company to proceed with activities such as equipment procurement and facility preparations.