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.

This week, we tracked more than 70 tech funding deals worth over €1.6 billion and over 15 exits, M&A transactions, rumours, and related news stories across Europe. In addition to this week's top financials, we've also indexed the most important/industry-related news items you need to know about. If email is more your thing, you can always subscribe to our newsletter and receive a more robust version of this round-up delivered to your inbox. Either way, let's get you up to speed. ? Notable and big funding rounds ?? Elvy raises €500M to power its next-generation energy solution ?? Iceye raised €150M in Series E funding ?? Fal raises $140M Series D to power the next era of real-time generative media ??‍?? Noteworthy acquisitions and mergers ??  Mollie buys GoCardless in €1.05bn deal ?? Tekpon’s bold bet: Why a SaaS marketplace bought TNW without seeing the numbers ??  Sortlist acquires Overloop AI and becomes a complete commerce platform by focusing on AI ?? The Canadian company Senstar is acquiring the Munich-based 3D LiDAR technology company Blickfel ? Cofounder VC launches new early growth Fund to back CEE startups beyond Seed stage

This week sees the launch out of stealth of CYBRET AI, an autonomous security and development lab building autonomous systems that understand modern attack behaviour, reason across complex environments, and operate at machine speed. From deep attack understanding to real-time reasoning and response, its work focuses on pushing security beyond human-only operations. Although the financials have not been publicly disclosed, CYBRET AI is backed by leading Nordic funds and experienced operators, including Skyfall, Inception Fund, Visionaries Club, Wave Ventures, FR8, and founders from companies such as F-Secure, AMD Silo AI, and Hoxhunt. Founder and CEO Adrian De Gendt is a Nordic child prodigy — Norway’s youngest cybersecurity analyst in history, a two-time finalist (and the youngest ever) in the Norwegian Astronomy and Astrophysics Olympiad, and the youngest student to attend both high school and university. After dropping out of a Masters degree in Artificial Intelligence at just 19, Adrian has been deeply immersed in hacking, programming, and cybersecurity since his early teens. He is now determined to build a world-class team and a global category-defining company with strong Nordic roots but a global mindset. According to Ernesti Sario, Co-founder, FR8, it's rare to see someone this young carry such technical depth with such relentless drive: “From our first conversations, it was clear that Adrian was onto something special. He is one of those few builders who refuse to accept the limits everyone else quietly lives with. We’re proud to be among the early believers.” For Oliver Molander, General Partner, Inception Fund, Adrian represents the new generation of technical talent emerging from the Nordics in AI — founders like those behind Lovable and Legora –- marked by fearlessness and a global-maximum mindset from day one. "We’re extremely excited to back him and equally excited about the talent the Nordics and Europe are currently producing.”

British AI company Applied Computing, which develops foundational AI for energy operators, today announces the opening of its new office in Bangalore, marking its official expansion into India and deepening its commitment to one of the world’s most strategically significant energy markets. The expansion will create new jobs across AI research, engineering, energy modelling and commercial operations. The move follows significant traction in India, where Orbital has already been proven inside major refining environments and is now being actively deployed with leading operators. Applied Computing’s flagship platform, Orbital, is the first foundation model built specifically for energy operations, bringing superintelligent, physics-grounded optimisation to some of the most complex industrial environments in the world. Applied Computing has built-up a senior team in India, including the appointment of former Shell executive Dan Jeavons, one of the world’s leading industrial AI figures, who relocated from London to Bangalore several years ago. Following his decision to join the firm this summer, Dan decided to remain in India.  Jeavons previously led Shell’s global AI programme and brings two decades of experience spanning upstream, downstream and integrated gas. I spoke to him to learn more about the country, why it’s been gaining so much traction when earlier startups haven't, and its market expansion into India. Jeavons spent almost 20 years with Shell in different capacities, always in the data and analytics space. And then data and analytics blurred into AI as the world headed in that direction. For the last 13 years, he was leading Shell’s core AI program; his last role at Shell was VP for Computational Science and Digital Innovation.  He explained, “I led about 350 researchers globally, working on everything from seismic processing to wind turbines, manufacturing plants, and electric vehicle charging—building various types of AI for all of that.” During this time, he got to know Sam Tukra, “an incredible talent we quickly identified at Shell, but he was very convinced he needed to go and start his own company. So he built what is now Applied Computing, where he now works as Chief AI Officer.” ‘My ChatGPT moment’: why Orbital convinced a Shell veteran to switch sides Tukra visited him after putting together a research team from Imperial and partnering with Callum Adamson, the CEO and co-founder, and an Entrepreneur-in-Residence at Imperial. He recounts: “He came to see me and showed me what Orbital is, the foundation model we’re developing at Applied Computing. I always say it was my own personal ChatGPT moment.  I’d been very close to the developments of large language models, so ChatGPT itself didn’t really surprise me." The real breakthrough he saw in Orbital was the ability to combine physics, time series and language into a common foundation model.  “For our world — the world of energy operations — that is an absolute game-changer because it brings into one integrated model almost every question you could ask about the operations of a site. So it becomes a true general AI you can deploy into some of the world’s most complex industrial landscapes. I got very excited, and long story short, they convinced me to come over and help build the company. It wasn’t in the life plan — but here I am as President.” Why industrial AI struggled — and why that’s now changing I’ve written 100s of thousands of words about industrial IoT throughout my career. However, Industrial IoT, in many respects, failed to deliver on its promise. Most factories are built on decades-old machinery, proprietary protocols, and safety-critical systems that are difficult or costly to connect, making integration economics unattractive. Projects also suffered from unclear and slow ROI: large upfront investment in sensors, connectivity, integration, and security often delivered only incremental savings, so pilots rarely scaled. Further, while IIoT generated vast amounts of data, organisations lacked the analytics maturity to turn that data into actionable outcomes as they depended on an AI capability that didn’t yet exist. Only now, with foundation models, edge AI, and domain-specific intelligence, is it becoming feasible to rethink industrial systems. Jeavons admits that, as someone who spent a decade working on Industry 4.0 projects, data-driven methods only really impacted the peripheral operations. “You could do equipment failure prediction, integrity management, inspection, rust detection, classification — those worked and delivered value.But the utopia we are glimpsing now with AI? I felt that was achievable with the prior generation of tech. But it wasn't. It wasn’t explainable enough. It was too black box. It wasn’t appropriate to deploy into the core of operations. With the next generation of models, all of that is changing. And I think we will see a radical transformation in heavy industry in the next few years.” According to Jeavons, most critical infrastructure runs on physics-based simulations. When you design a facility, these are the equations that govern its operation, because they’re governed by the laws of physics.  “We can say that if we operate within these constraints and boundaries, we can produce the desired output from the process. We run that process a lot of times, then embed that into a control system. What that allows you to do is run the facility in steady state within those boundary conditions. Operators are there to make sure those operating limits aren’t breached.” However, this fails to integrate all the data the plant generates continuously. That data gets used, but only for root-cause analysis or incident detection, but its siloed and disconnected from operations. Then you have a whole variety of engineering disciplines sitting around the plant using subsets of that data to derive insights that operators might want to know. Orbital completely rethinks this. It can combine the physics from the simulator and integrate it with the data — not just time-series data, but also language data: the reports written, the work orders generated, the inspection reports created five years ago. Jeavons equates it with the aeroplane and the control tower.  “The pilots are flying it — that’s what operators do. But in these sites, you don’t have the control tower where you can see everything else going on. We’re saying: you can build a control tower. Across not just one site, but 40 sites. You can compare operations. You can look at when a piece of machinery failed and ask: where else is that likely to happen next? You can say: I’ve seen this integrity condition here, under these conditions—have we checked over there? Your ability to look across the entire business and empower that with A I— that’s where the transformation comes from.” Asking operational questions in natural language while protecting proprietary data  For Jeavons, the language interface makes an enormous difference: “The ability to ask simple questions in natural language and interrogate all the data — engineering drawings, shift logs, maintenance history, time series — that ability to cut across silos is game-changing. Each engineering discipline is looking at one slice. Orbital lets you ask questions across all of them.” I was curious about how Orbital handles proprietary data, a major issue in industrial environments. Crucially, Applied Computing brings its model to the customer’s data. Orbital has a foundational understanding of physics, the domain language, and time-series behaviour.  “It’s a transfer-learning principle. We augment it with the customer's data—in their environment," explained Jeavons. “Training happens inside their infrastructure, or an environment they control. That means we don’t expose their data to the world or to other customers. We do not ask for their data to train a global model. The model remains our IP, but everything produced in the customer’s environment is theirs to use under the contractual terms. And the data never leaves their environment." From pilot to production in under a year Less than a year into the market, the company is deploying into real customer environments and seeing strong outcomes.  According to Jeavons, “The biggest thing customers tell us is the ability to approach a problem from multiple different angles, unlike before, where you needed a whole team of experts. The biggest benefit is the ability to use AI to rethink how you run your business and answer questions you couldn’t answer before. That’s where senior leaders are really engaging—because they believe this will change the game.” Applied Computing raised £9 million in May this year. The funds are being used for research: “At our core, we are a research company developing a next-generation foundation model for the energy industry,” explains Jeavons. “AI moves daily, and we must stay at the cutting edge.” The second use is go-to-market strategy. The company has hired domain experts as “it’s great having a killer model. The challenge is deploying it, solving users’ problems, and earning the right to expand within accounts,” shared Jeavons.  He sees his role as to bridge the tech with industry needs and shape the narrative and deployment to drive impact.  “To drive material change in these organisations, you have to work at the C-suite level. It’s not just technology—it’s rethinking how you run your business. That’s why we focus on a few strategic customers and high-level conversations to drive outcomes.”   Rising energy demand meets India’s leapfrog-ready infrastructure Applied Computing’s expansion comes as India’s energy landscape reaches a pivotal moment. While global policy trends push towards decarbonisation, India’s energy demand continues to rise sharply, driven by industrial growth and a rapidly expanding population.  According to Jeavons, India is the fastest-growing energy economy in the world. “There’s incredible talent here. I lived in Bangalore for three years — I moved here with Shell and stayed because I’ve been so taken with the country and its potential. We’re celebrating the opening with friends, customers, and partners. We’ve already had customers come into the office to work with us and see the research team. It creates a phenomenal space for accelerating the technology." He believes that. while Europe has been phenomenal in many areas— "just look at the startups that have emerged from the region." India can leapfrog in areas where it isn’t constrained by legacy systems. "That entrepreneurial instinct is very real. That’s why I’m excited about Applied Computing being here: we can run the leapfrog playbook.” He shared:  “Orbital is already delivering results with customers here, including at some of the largest refineries on the planet. By establishing our base in Bangalore, we’re investing directly in the talent, partners and ecosystem that will define the future of industrial intelligence.” It's a sentiment echoed throughout the company. According to Callum Adamson, CEO and co-founder of Applied Computing,  “India is not just another geography for Applied Computing - it is our primary market and a proving ground for the future of industrial AI." "The country’s refining and petrochemical sectors are central to the global economy, and the decisions made here will influence energy stability and emissions worldwide.  Orbital is already deployed in India, delivering impact at unprecedented scale, and our investment in Bangalore strengthens our ability to support operators as they modernise and transform their most critical infrastructure.” Why India is becoming ground zero for industrial AI India's country’s refining and petrochemical sectors are set to grow substantially over the next decade, and many of its critical assets rely on ageing infrastructure where AI-driven optimisation can have outsized impact. India’s openness to technology adoption and its willingness to deploy AI at an operational scale make it one of the most important markets globally for industrial intelligence.  The combination of demand growth, infrastructure complexity and a culture of technological experimentation positions India as the ideal environment for Orbital to deliver immediate system-wide benefits. Jeavons is joined by Hari Ramani, Vice President of Commercial Markets, who will lead customer engagement and global market development: “Energy operators in India are managing extraordinary complexity across ageing and emerging infrastructure. They’re looking for solutions that improve efficiency today while preparing for a more sustainable tomorrow.  Orbital provides that bridge — delivering actionable, physics-grounded intelligence across entire facilities. The appetite for real-world AI adoption here is unmatched, and today’s expansion positions us to serve this demand at scale.” Lead image: Dan Jeavons, Applied Computing.

Swedish energy company Elvy has secured a €500 million financing package from Scayl and a banking partner to fund home energy packages offered through a monthly subscription model. The packages include solar panels, heat pumps, and home battery systems, and are designed to remove the need for large upfront investments. Elvy is providing integrated home energy solutions, combining smart technology with installation services and customer support to help households reduce energy costs and emissions as it expands across Sweden. Under the subscription, homeowners receive equipment, installation, maintenance, and coverage for the home’s electricity needs at a fixed monthly cost. The system is managed by Elvy’s AI engine, which monitors and optimises household energy generation and consumption. Elvy’s CEO and co-founder, Johan Outinen, says the focus is not primarily on the technology itself, but on delivering peace of mind to homeowners: Our customers want heating, warm water, and reasonable electricity costs. It shouldn’t require big investments or that they become energy experts in their free time to optimise energy consumption. As electricity prices remain volatile across Europe, more homeowners are looking for solutions that offer cost predictability alongside environmental benefits. Elvy’s model is intended to help households reduce dependence on the grid, lower long-term energy expenses, and improve home sustainability and potential property value, while lowering barriers to adopting modern energy systems. Supported by the €500 million financing, the company expects to make these systems available to tens of thousands of households and increase its capacity to onboard up to 15,000 new customers.

Dutch payments firm Mollie is acquiring UK payments fintech GoCardless in a €1.05bn deal, the two fintechs have confirmed.The two fintechs have billed the combination as creating a “payments powerhouse”, confirming rumours of the tie-up which surfaced in the summer.GoCardless, which employs around 800 people, is a payment platform that lets businesses collect one-off and recurring payments, such as subscriptions and membership fees, via direct debit, rather than credit cards or bank transfers. The fintech, which has also made a play in open banking, is headed up by Hiroki Takeuchi, a well-known figure in the UK fintech ecosystem.Mollie, which employs more than 900 people, is primarily known as a payments fintech, focusing on the European SME market, processing tens of billions of Euros in transaction volumes each year. Mollie competes against the likes of PayPal, Stripe, Adyen and legacy players like JP Morgan.The FT reported that the deal was made up of 90 per cent stock and a small cash element.A spokesperson for GoCardless said it was too early to say if the deal would lead to job cuts.The fintechs said that the combination creates a company serving over 350,000 businesses that integrates card payments and bank payments into a single offering.Koen Köppen, CEO of Mollie, said: "GoCardless built the definitive solution to optimise this process with its global bank payment network. By bringing them into Mollie, we take a huge step towards fulfilling our vision and creating one complete platform for sustainable growth."Takeuchi, co-founder and CEO, GoCardless, said: "This deal brings together two highly complementary businesses that have built best-in-class products across Europe and beyond.  "By combining our expertise in card, bank and hyperlocal payments into one provider, we can better serve our customers, accelerate growth and raise the bar for the industry. It’s a win for European fintech and we’re confident that the new company will be greater than the sum of its parts.”GoCardless, which is profitable, was valued at $2bn in 2022.  It is backed by Balderton Capital, Accel, Permira and BlackRock.Mollie, which is backed by Blackstone, was valued at around $6.5 billion in 2021.

Hello Vet, the UK’s first veterinary practice to invite pet owners into treatment and recovery rooms, has raised £15 million in Series A funding to bring its transparent and collaborative approach to vet care to more British pets and their owners.  This takes the total investment to £21 million, following a £6 million Seed round in August 2023. Hello Vet’s Seed and Series A rounds have been supported by leading investors, Addition and Future Positive, alongside 15 leading and specialist vets. Hello Vet was founded in 2022 by two healthcare entrepreneurs, James Lighton and Alessandro Guazzi, and veterinary surgeon Dr Oli Viner.  Starting with their first site in London Fields in July 2024, the trio set out to open vet clinics that treat both people and pets better. Hello Vet allows clients into its procedure rooms to hold their pets’ paws as anaesthesia is administered and to be present when their pets wake up. This reduces stress for both pets and people and has been shown to improve outcomes and speed recovery, while building trust as clients observe firsthand the expertise and quality of care delivered. The company also improves access to professional care by providing a complimentary WhatsApp triage service. This allows any registered pet owner to speak with a qualified practitioner immediately, without visiting a Hello Vet clinic, saving owners more than £75,000 in fees in the last year alone. Across the UK, vets face some of the highest burnout and attrition rates of any profession. One in three is considering leaving the profession within five years, and around 10 per cent leave each year. Hello Vet is investing in proprietary technology and AI applications designed to reduce administrative time by up to 90 per cent. By removing routine paperwork and operational tasks, the company frees up its clinical teams to focus on what matters most: delivering exceptional care to pets. James Lighton, co-founder and CEO, shared: “We know that most veterinary professionals come into this industry because they love working with animals. But too many good people are leaving this vocation. We want to become Britain’s best place to work, to ensure working in a vet clinic feels like the dream job it should be." “When we treat our teams better, pets and their people benefit too. It’s a win-win.” Robbie Horwitz, partner at Addition, says: “Hello Vet’s focus on better support for veterinary professionals is redefining what pet care can look like in the UK. We’re proud to back Hello Vet as they set a new standard for how vets, pets and owners experience care.” Hello Vet has over 7,500 registered patients. The funding will support the company’s UK expansion, with plans to launch clinics across the UK, and hire a team of 200 vets and vet nurses over the next two years. This growth is focused not just on scale, but on building a supportive, sustainable environment for veterinary professionals.

Global tax automation platform Yonda Tax has raised £11 million in investment funding.  Yonda Tax automates global tax compliance from registration to filing and remittance, so businesses can focus on scaling. Every jurisdiction has its own filing requirements and deadlines, which often change with little notice. In addition, tax authorities worldwide are intensifying their scrutiny of cross-border compliance, which is why Yonda Tax automates global tax compliance from start to finish, ensuring businesses remain fully compliant as they expand across borders. Yonda Tax has grown over 100 per cent YoY, and headcount has more than doubled over the past 12 months as it expands globally, highlighting strong market demand for accurate, personalised tax support for growth businesses. Around 60 per cent of clients are based in the US, with growing customer bases in the UK, Australia, Canada, and Singapore.  The platform serves a wide range of clients, from eCommerce brands selling through Shopify and other platforms, to high-growth SaaS and AI companies. Yonda Tax also differentiates itself through its subscription-based pricing model. Unlike many competitors who charge variable fees based on transaction volume or require annual contracts that scale with company growth, Yonda offers a fixed monthly fee based on the number of regions a client files in. This approach provides businesses with predictable, transparent costs so they can focus on scaling their business. The round was led by Kennet Partners, with participation from NYO Capital and Portfolio Ventures.As businesses scale beyond their home markets, managing indirect taxes such as VAT, GST, and Sales Tax becomes one of their most complex and time-consuming operational challenges.  According to Gareth Kobrin, Co-Founder of Yonda Tax, the company was started after seeing founders do everything right, yet still get tripped up by the nightmare of international tax.  “So we built Yonda as the partner we wish they’d always had, leveraging decades of accountancy expertise to create a personal, highly accurate technology that takes tax off their plate so they can focus on building.  After years of bootstrapping, working with Kennet has been a natural fit from the start and validates all the hard work we’ve achieved. We are incredibly excited to be able to support even more of the world’s most promising young companies.” Hillel Zidel, Managing Director of Kennet Partners said: “Unlike many competitors who take a “tech first” approach, Yonda positions itself as a “tax-first, tech-second” company, a genuine partner rather than a cold SaaS product.  That combination breeds accuracy and trust that stands out in this space, and it’s why we are proud to be their first institutional investor and to support their next stage of global expansion.” The funding will be used to enhance platform features and functionality, and to support its expansion into new industries and tax jurisdictions.

Rotterdam-based Lynk, a collaborative AI contract workspace that helps businesses manage and control their agreements, has closed a pre-seed round led by European AI investor Curiosity VC, with participation from strategic angel investors. Lynk is developing a contract intelligence layer integrated into the contract-control process. The platform automates audit tasks, identifies potential risks, and flags key actions throughout the contract lifecycle. It is designed to support faster decision-making, prevent missed obligations, improve financial outcomes, and reduce manual administrative work related to contract management. Lynk is currently used by both enterprises and small businesses in real estate development and general contracting in the Netherlands, and its product has been developed in close collaboration with industry stakeholders to address the complexities of contract management in these sectors. Ruben van Gaalen, founder and CEO of Lynk, explained: Companies we work with often manage more than 100,000 pages of active contractual obligations. Until now, this has been audited manually and tracked in Excel. Itʼs not only extremely labour-intensive, itʼs also highly error-prone. Our workspace and its AI capabilities now make it possible to this work reliably and at scale. AI is expected to significantly change how contract control is carried out. Over the next five years, the way large organisations audit and manage contractual obligations is likely to be fundamentally reshaped across legal, operational, and financial control functions. Manual contract related tasks are projected to be increasingly handled by AI systems that can also incorporate a company’s contextual data, allowing professionals to focus more on higher-value activities. Lynk will use the funding to accelerate commercial expansion, support its international rollout, and extend the product into additional sectors where complex, high-value agreements require improved control.

UK-based AI workload startup Runware has raised a $50 million Series A round led by Dawn Capital, with participation from Speedinvest, Comcast Ventures, and existing investors including Insight Partners, a16z speedrun, Zero Prime Ventures, and Begin Capital. Runware provides infrastructure for enterprises to integrate AI into media-creation workflows. Its customers include Wix, Together.ai, ImagineArt, Quora, Higgsfield, and a range of other enterprise accounts. The company focuses on three challenges in the media AI market: fragmented access and usability, latency affecting user experience, and unit costs that do not scale efficiently. Runware addresses these by aggregating AI models behind a single API and developing high-performance AI inference hardware and software designed to lower both capital and operating expenditure. Its Sonic Inference Engine platform aims to deliver performance comparable to top-tier GPUs at significantly lower cost. Ioana Hreninciuc, Runware co-founder, noted that bringing AI to millions of users has become essential for product teams, yet remains technically challenging and costly: We give clients the best price and developer experience in a single API, so they can roll out any new model in minutes—without integrating dozens of providers, managing RPMs, or negotiating huge commitments. Through our API, they offer unlimited AI features to end-users, and we see them hit repeated growth peaks as a result. Runware, which has offices in London and San Francisco, plans to use the Series A funding to further develop its “one API for all AI” platform, extend the capabilities of the Sonic Inference Engine, and expand its team.

Crypto has created a financial system that runs on code, moves vast sums at the speed of the internet, and can be attacked from anywhere.  A single missed check or stray line of code isn’t a minor bug — it can take down an entire protocol.  Bug bounties began as an informal pact between developers and security researchers. But as DeFi ballooned into a multibillion-dollar ecosystem, the threat landscape shifted.  Today’s adversaries include nation-state outfits, organised crime groups, and financial engineers who can drain a protocol in seconds.  This escalating threat landscape demanded a more structured, scalable defence — something the early bug-bounty model wasn’t built for. Into this gap steps Immunefi, an on-chain security platform focused on protecting crypto protocols from hacks and vulnerabilities, founded by Mitchell Amador.   Founded in Lisbon in 2020 — although now with a Singapore HQ — Immunefi has reportedly paid over $100 million in rewards to white-hat hackers. It coordinates some of the industry’s largest bug bounties while setting an industry standard and helps prevent billions in potential losses. Further, it developed the internet’s first bug-bounty court to bring legal certainty, enforceability, and a sense of order to a space where a single dispute can shape the future of a project. I spoke to Amador to learn all about it.  Enter the scaling bug bounty standard Before introducing its Bug Bounty Court, Immunefi first set out to fix the incentives themselves with a new standard for how bug bounties should work. A bug bounty is a reward offered by a company to security researchers (“ethical hackers”) who discover and responsibly report vulnerabilities in its software or systems. However, traditional low bounties don’t incentivise top security researchers to responsibly disclose bugs. In turn, the Scaling Bug Bounty Standard is a DeFi security model where bounty payouts are tied to the real economic impact of a vulnerability, rather than a small fixed reward.  Instead of offering, say, $10k for a critical bug, a protocol sets the bounty as a percentage of the funds at risk (often up to ~10 per cent). DeFi systems can hold millions — or billions — of dollars in a single contract.  By scaling rewards with potential damage, the model: makes ethical disclosure financially competitive with exploits,Bug bounties attract better security talent, and significantly reduces the incentive to steal. But avoiding exploits also depends on preventing new bugs from shipping in the first place. As part of this, Immunefi has developed a pull request (PR) review program that allows security researchers to earn bounties not by finding new bugs, but by reviewing code changes (pull requests) before they go live. According to Amador: “PR Reviews is a CI/CD pipeline security tool. It integrates our AI systems and top human hackers into every step of code review." Instead of waiting for a hack to happen or searching the entire codebase, researchers review the new or modified code that developers submit for release. “We’re building the multi-layered SecOps stack that can get us there — multiple defensive layers powered by LLMs to customise every tool per protocol. Think of it as a SecOps platform with an intelligence layer. With it, we can keep the industry safe scalably. If we don’t, and trillions flow on-chain, we will be subsidising cybercrime for 20 years.” Why bug bounties need a court However, traditional bug bounties rely heavily on goodwill and trust, but in Web3 the stakes are much higher: millions or billions can be at risk, and researchers typically must disclose the vulnerability before getting paid.  Immunefi Arbitration is a legally binding dispute-resolution system created specifically for the bug bounty world, where security researchers and crypto projects often disagree on whether a bug is valid, how severe it is, or how much the reward should be.  When a conflict arises, Immunefi first attempts to settle it through mediation. If mediation doesn’t resolve the issue — and the bounty program is enabled for arbitration — either side can trigger a formal arbitration claim. At this point the case is handed to the London Chamber of Arbitration and Mediation (LCAM), an independent body whose arbitrators evaluate the vulnerability report, the evidence, and the program’s rules.  The researcher becomes the claimant, the project becomes the respondent, and both sides submit documentation and arguments. The arbitrator then issues a ruling that is legally binding and enforceable internationally through established arbitration frameworks such as the New York Convention.  It carries legal weight and can be enforced in courts around the world if necessary.  Ultimately, the process is designed to be faster, cheaper, and more practical than taking a dispute to a traditional court, which would be prohibitively slow and expensive for most researchers. For Amador, these systems weren’t theoretical — they grew out of years of witnessing crypto’s worst failures firsthand. The paranoia that built a security platform Mitchell Amador has worked with teams across the ecosystem — including Ethereum, Lido, MakerDAO/Sky, Filecoin, Stacks, LayerZero, Chainlink, Arbitrum, and Polygon — on incident response, vulnerability disclosure, and security standards. Amador has participated in numerous onchain incident “war rooms” and has been involved in efforts to recover funds and coordinate responsible disclosures.  Amador admits, “I’ve seen a lot of security events go wrong. Basically every project I worked on in the mid-2010s in crypto had some major cyberattack or incident.  Everything and anything under the sun was happening. So I became super paranoid.” However, this was before DeFi took off; there were no real on-chain financial markets, but he could see the tech taking off.  “I knew this was going to be huge — and we were going to get a huge wave of attacks. When people realise they can steal a million dollars over the internet, everybody and their dog is going to try.” He did the math and concluded that all of DeFi — and the potential for on-chain finance — would be destroyed before it began.  “It has been totally delegitimised in the eyes of the law. Imagine a world where 25–30 per cent of assets are stolen in the first year, “ he said. The modern attack landscape The modern attack surface shows exactly why that paranoia was justified. According to Amador, as the market matured, code became more complex. Real on-chain financial products have emerged over the last four years, such as lending markets like Aave, Automated market makers like Uniswap, perpetual futures,  and prediction markets. This has brought forth a wave of security complexity and an explosion of new vulnerabilities. There are two broad types: Flash-loans: where a hacker uses a giant flash loan to manipulate the market or protocol rules, and profit from that distortion — and a broader category of financial-engineering attacks where funds are accessed by gaming the financial design of the protocol. Web2-style “off-chain” compromises where attackers hack people and traditional IT infrastructure around a crypto system, instead of exploiting smart‑contract code directly. For example, in the $600 billion Ronin bridge hack, four North Korean actors compromised a service provider and internal systems to gain validator keys and then drained the bridge. “Criminal organisations run like startups whose sole job is to steal your money.” According to Amador: “From day one, there are literally North Koreans stalking you. The moment you announce fundraising, they are spear-phishing your dev team. That’s literal, not figurative. There’s too much money at stake, and the cost of attack keeps falling." He suggests that everyone must start paranoid, "There is no DeFi or on-chain company that survives with a reactive approach.” "Instead, everyone must be proactive before launch: audits, code review, and bug bounties. VCs mandate it. It’s night-and-day from traditional industries.” Amador asserts that when it comes to security threats, the risk of social engineering is massive. Crypto is the most lucrative place in history for social engineering. “Criminal organisations run like startups whose sole job is to steal your money. And I came to the conclusion that the only way we could do that is to have a scalable way of incentivising and coordinating the security community to defend these projects." He believes the stakes are clear: while “magical internet money” works remarkably well, the ecosystem risks subsidising cybercrime for decades if security doesn’t keep pace. Current hack rates of 3.6–4 per cent, he warns, are simply unsustainable. Yet Amador is adamant that the core technical challenges are solvable. In his view, the crypto security community already knows how to secure contracts, prevent contagion, detect scams, monitor chains, and harden code to aerospace-grade standards. The tools exist and are effective. What’s missing, he argues, is broad adoption — particularly from traditional finance players entering the space. “We know how to secure contracts, resist contagion, detect scams, monitor chains, and harden code to aerospace levels. The tools exist and work.  What’s missing is adoption — especially by traditional finance." He sees this as a battle between the excellence of the crypto security community and human ignorance. “If people adopt these tools, crypto becomes the most secure financial system in history.  If not, we will learn the lesson the hard way.”

Zilch, the UK BNPL fintech, has received a licence which it says will remove its reliance on third parties and allow it to build more payment methods in-house.Zilch, which is backed by Goldman Sachs and eBay, also said it had strengthened its ties with Visa, which earlier this year replaced Mastercard as Zilch’s card network partner.The UK fintech has received a payments services licence from the UK's main financial regulator, the FCA.Zilch said the licence means it will be less reliant on third parties and would be able to build more payment methods in-house, as well as bring products to market quicker.It comes ahead of the full rollout of Zilch’s one-click checkout feature, Zilch Pay, next year.Philip Belamant, co-founder and CEO of Zilch, said: “This is a major step change for Zilch, bringing us firmly into the payments tent and giving us a true seat at the table to shape the ecosystem. “It opens the door to new opportunities, setting us up to move even faster, more efficiently and cost-effectively."Zilch also said it has secured “Principal Membership” of Visa for the first time, and that Zilch and Visa intend to explore new opportunities to collaborate on payments.In November, Zilch, which has over 5m customers, bagged over $175m in an equity and debt funding round as it eyed acquisition targets. The funding round was led by KKCG, the Czech investment group, with participation from BNF Capital, the family office, and other strategic investors.