The Collapse of Mastery

In a small workshop in 15th-century Florence, a young apprentice watches his master's hands move across wood with practiced precision. For fourteen hours each day, he sweeps floors, prepares tools, and absorbs. This is his seventh year of apprenticeship - not unusual for the time. The path to mastery back then was measured in decades, not quarters.

The Japanese had a word for this: "shokunin" - the artisan's relentless pursuit of perfection through repetition. A sushi chef would spend years just learning to prepare rice before ever touching fish. A swordsmith's apprentice might spend a decade simply tending the forge before crafting their first blade.

In 1885, Friedrich Nietzsche made a prescient observation after using one of the first commercial typewriters: "Our writing tools are also working on our thoughts." Little did he know how prophetic these words would become.

This historical progression shows how each new technology replaces not only physical labor but also the mental and creative skills that humans took generations to perfect.

The first wave of machines replacing humans came with the Industrial Revolution:

• The spinning jenny (1764) replaced six spinners with a single worker

• The mechanical loom dealt the death blow to master weavers

• The steam hammer made the blacksmith's practiced swing obsolete

But these were just the beginning. The calculator stripped away the mental mathematics that accountants had spent years perfecting. CAD software eliminated the careful hand-drafting skills that architects developed over decades. The digital camera made obsolete the darkroom expertise of master photographers, and CNC machines replaced the practiced hands of machinists.

The compression of time

This transformation goes beyond machines taking over human jobs—it's a fundamental shift in our perception of time. What Gladwell termed the "10,000 hours rule" for achieving mastery has now been distilled into algorithms that can produce results in seconds that once took decades to attain through practice.

The painstaking journey that once defined mastery is being systematically eliminated. Designers who spent years perfecting typography now compete with AI that generates flawless layouts instantly. Photographers who mastered light and composition face algorithms that produce striking images from text prompts alone. Writers who honed their craft through countless drafts watch as language models produce polished prose on demand.

There's more. Code is increasingly written by machines that learn from the collective work of human programmers. Video generation has leapt from crude approximations to near-photorealistic output in mere months. Complex creative productions that once demanded orchestras of specialists—each having invested their 10,000 hours of mastery—now materialize at the prompt of integrated systems requiring little more than a human curator (yes, pun intended).

This progression follows a relentless logic, consuming domain after domain. When AI code generators made a jab at software developers in 2022, many dismissed it as merely "autocomplete on steroids." When synthetic media engines threatened filmmakers in 2023, industry veterans insisted that "real cinematography" would always require human sensibility. When music composition tools began producing compelling original scores in 2024, musicians retreated to the supposed sanctuary of live performance.

But by early 2025, the wave had reached shores once thought safely distant from automation's tide. Venture capitalists now find their own expertise under assault (oh no!). AI systems trained on decades of investment data are pattern-matching successful startups with unprecedented accuracy and delivering due diligence in seconds rather than weeks (we'll come back to that part later in this essay).

This is not merely technological displacement—it's the systematic conversion of hard-won human judgment into commodified processes available to anyone with an internet connection. The collapse of mastery isn't just happening to others; it's coming for everyone who built careers on information processing, pattern recognition, and creative synthesis—even those who, like most VCs, once believed themselves to be the architects of disruption rather than its subjects.

The Data-Driven Approach

Now, let me set the proper context for these reflections. Two recent developments have motivated me to write this essay: a blog article on the (alleged) collapse of the data-driven approach in venture capital, and Crunchbase's announcement of its transformation into an "AI-first crystal ball" for predicting venture outcomes.

What exactly is data-driven venture capital, and why examine it through the lens of mastery? Data-driven VCs differentiate themselves from traditional investors by using vast datasets, algorithmic analysis, and automation throughout their investment process. Where conventional VCs built careers on pattern recognition developed through years of experience—the apprenticeship model of professional judgment—the quantitative approach promises to compress this learning curve through computational power.

Traditional venture capital embodies the classic mastery paradigm: partners spend decades developing intuition through repeated exposure to successes and failures, building networks of relationships that generate unique deal flow, and cultivating judgment that can't be easily articulated or replicated. The 10,000 hours manifest in the ability to assess founding teams, evaluate market timing, and sense when to double down or cut losses.

The data-driven revolution promised to shortcut this journey by identifying statistical patterns invisible to the human eye. It suggested that mastery could be accelerated, or even rendered obsolete, through sufficient computational horsepower applied to the right datasets. Not years of practice, but rather access to data, is the key.

To power this approach, data-driven VCs deploy a sophisticated technology stack mining diverse information sources. The foundation typically includes structured databases like Crunchbase, PitchBook, and Dealroom for baseline metrics. But true competitive advantage comes from alternative data sources that provide early signals before they manifest in traditional channels.

The Arms Race for Signal

As early as 2015, a quiet technological arms race was brewing in venture capital. By 2019, several of my VC friends were confidently declaring their competitive advantage came from proprietary data infrastructure—sophisticated "scrapers" harvesting early signals before they reached the broader market.

These companies assessed hiring speed by using LinkedIn data, monitored GitHub repositories for new developer tools, evaluated social media sentiment about startups, and analyzed email domains and pitch deck metadata to identify companies preparing for fundraising. The most advanced companies built detailed data pipelines that powered their unique scoring systems.

Several firms have built their identities around data-driven investing:

• SignalFire launched its proprietary "Beacon" platform in 2015 as a "Bloomberg terminal for startups," hiring a CTO and PhD data scientists to mine alternative data for growth signals.

• EQT Ventures built "Motherbrain" in 2016, an AI platform that tracked startups across their lifecycle and identified Peakon early—a company later acquired for $700M - reinforcing the messaging around Motherbrain's superiority

• Earlybird Venture Capital developed "EagleEye" in 2018, a machine learning tool credited with discovering Aleph Alpha before competing firms

• ICONIQ Growth assembled a 57-engineer analytics team to benchmark portfolio metrics against proprietary datasets

• Social Capital pioneered "Capital-as-a-Service" in 2016 to automate early-stage diligence, later inspiring Tribe Capital's "Magic 8-Ball" model for identifying network effects

More recently, new entrants are continuing this quantitative approach:

• Correlation Ventures was among the first to algorithmically select investments based on historical VC outcomes

• Quantum Light Capital, founded by Revolut's founder in 2022, uses machine learning on LinkedIn data and corporate filings to identify fast-growing startups

Meanwhile, the previously elusive signals began their inevitable march toward commoditization. By 2020, specialized data providers flooded the venture capital landscape, each charging premium subscription fees on the promise of superior signal quality. These vendors marketed the illusion of informational edge—promising VCs privileged intelligence supposedly unavailable to competitors.

The market dynamics created a perfect prisoner's dilemma: if you manage hundreds of millions with only a dozen investments yearly, wouldn't you pay whatever it takes to discover opportunities before competitors? Surely there's a reason why this or that company charges several thousand dollars a month for this, right? Fear of missing the next unicorn drove firms to either subscribe to increasingly expensive intelligence platforms or invest substantial resources into building proprietary capabilities.

But by early 2025, the fundamental flaw in this approach became undeniable. AI, particularly Deep Research capabilities, has rapidly commoditized access to knowledge that once required months or years to assemble. The structural barriers protecting information advantages have simply dissolved.

What's remarkable is the speed of this commoditization curve. Just two months ago, Google's Deep Research commanded premium pricing; now it's bundled into standard Workspace subscriptions. OpenAI's comparable (or even superior) capabilities are available to anyone paying $20 monthly (with limits, though). The price-to-quality ratio isn't just declining—it's collapsing.

To illustrate the impact on VC, consider Tiger Global's renowned research team, which once thrived by employing numerous MBB consultants. This team, once a unique asset with hundreds of analysts creating exclusive market maps and competitive overviews, now appears outdated. Currently, a single GP with access to Deep Research can produce similar analyses in mere hours instead of months and at a significantly lower cost. The competitive advantage that once justified large teams and substantial operational costs has essentially vanished.

The Algorithmic Paradox

I want to be upfront about something: I don't believe that data-driven venture capital is dead. Quite the contrary—certain aspects of this approach have become table stakes that no firm can reasonably ignore.

Thanks to automation software, we can now manage previously time-consuming tasks, allowing us to handle larger deal funnels without proportionally increasing team sizes. We can systematically track thousands of startups, flagging those that reach specific growth thresholds or hiring trends, and trigger follow-ups when new signals indicate momentum. By utilizing off-the-shelf software tools to extract real-time metrics and benchmark startups against their peers almost instantly, we can significantly cut down the time required for due diligence. Who would want to give that up?

What I don't believe, though, is the assumed "superiority" of data-driven approaches, and here's why:

1. The half-life of competitive advantage in data has plummeted. AI capabilities are advancing exponentially, month after month, making any firm's custom tools yield diminishing returns as differentiators. What took a specialized data science team months to develop in 2020 can now be replicated in weeks or even days. The proprietary signals derived from LinkedIn scraping, sentiment analysis, or founder profiling that once provided a genuine edge are now easily replicable at scale. With each new LLM training run ingesting larger portions of the internet, the barriers around proprietary data pipelines continue to erode. By 2025, what once was a competitive advantage lasting years has shrunk to months or even weeks.

2. Venture capital's fundamental advantage has always been information asymmetry—knowing something others don't. The proliferation of startup databases and the systematic scraping of public (and not-so-public) data by AI companies has dramatically leveled this playing field. The asymmetry has shifted from possessing unique information to knowing which analytical tools to deploy in which contexts—a distinction that itself is rapidly diminishing as AI agents become more sophisticated at selecting and applying the right tools for specific analytical tasks. Soon, even the meta-knowledge of which tools to use where will be encoded into generally available systems.

3. We're witnessing a troubling homogenization of venture decision-making. When dozens of firms use similar data sources and algorithms, they inevitably reach similar conclusions. Founders report receiving nearly identical outreach messages from competing VCs within hours of each other—all referencing the same analyses and market projections derived from increasingly standardized research methodologies. This convergence creates a profound paradox: if data-driven models truly outperform human judgment, then the logical endpoint is algorithmic investing that eliminates the human investor entirely. The industry's reluctance to pursue this conclusion to its logical end suggests skepticism about pure quantitative approaches.

4. Predictive models suffer from the classic "garbage in, garbage out" problem, but with a temporal twist. Models trained on historical data assume that past patterns will predict future outcomes—a dangerous assumption in rapidly evolving markets. What if the metrics that predicted success for SaaS companies in 2015-2020 become irrelevant in an AI-first economy? What if the frameworks for evaluating founding teams don't account for the skills needed to navigate entirely new technological paradigms? Historical data provides a rearview mirror precisely when we need a telescope. It's the risk of algorithmic entrenchment—cementing decision frameworks that only made sense under specific historical conditions. How can predictive models trained on pre-AI era startup data possibly capture the success factors for companies building in fundamentally different technological landscapes? This creates a conservative bias in supposedly forward-looking tools, potentially missing paradigm-shifting opportunities that don't fit established patterns. The very tools designed to identify outliers may systematically filter them out when they appear in novel forms.

Investment theses are homogenizing at an unprecedented speed. In 2022, when generative AI burst onto the scene, we watched as virtually every major venture firm published remarkably similar market maps and opportunity landscapes within weeks of each other. Research agents will accelerate this convergence, with algorithmic analysis driving firms toward identical conclusions about opportunities.
Lawrence Lundy-Bryan

The Philosophical Shift of VC Data Providers

Until now, I haven't addressed the second catalyst for this essay: Crunchbase's recent "pivot" toward becoming an AI prediction company. Founded in 2007 as a TechCrunch project, Crunchbase evolved from a simple startup database into a venture information repository, tracking companies, investors, and funding rounds worldwide.

Crunchbase has maintained a successful business model by merging professional curation with crowdsourced contributions from founders and investors. This approach established a continuously updated resource serving not only venture capitalists but also entrepreneurs researching competitors, journalists verifying claims, and service providers seeking potential clients. For years, it operated primarily as a retrospective database, documenting what had already happened in the startup ecosystem.

Now, Crunchbase aims to fundamentally reimagine its role by introducing an AI-powered prediction engine that transforms its vast historical dataset into forward-looking intelligence. The platform aims to offer features that recommend high-potential startups, forecast which companies will likely raise funding soon, and flag early momentum signals that might escape human attention. By analyzing aggregate usage patterns—which startup profiles are being frequently viewed, saved, or researched—Crunchbase can allegedly identify companies gaining attention before traditional metrics reflect their momentum. The company claims its funding prediction feature achieves 95% accuracy in backtests, essentially offering investors advance notice of which startups will soon raise capital.

These claims warrant healthy skepticism. The landscape of VC funding data platforms—dominated by Dealroom, Crunchbase, PitchBook, and CB Insights—has evolved beyond competing merely on data completeness. These providers now vie to generate superior predictions and insights from their data, marking a fundamental shift from pure aggregation to predictive intelligence. For example, Dealroom's predictive algorithm ("Dealroom Signal") combines over a dozen inputs – including growth metrics (e.g. employee or product growth), completeness of company profile, founding team composition (serial founders, education/work history), and timing since last funding – into a single score indicating promise. Similarly, CB Insights' proprietary "Mosaic Score" algorithm integrates diverse data points to gauge the "health" and momentum of private companies.

As basic funding data becomes increasingly commoditized, I see clients naturally gravitate toward providers offering actionable intelligence ("which startups should I invest in now?") rather than just raw information ("what startups got funded last month?"). And there are things these platforms are really good at predicting. For instance, an academic study trained a deep learning model on Crunchbase data to predict major success events (like IPOs or unicorn valuations). In simulations, the model demonstrated impressive performance – achieving a theoretical 14× return on capital by picking high-potential startups at Series B/C stage (it successfully identified companies like Revolut, Klarna, and GitHub as future breakouts)​. This indicates that, under testing, AI models can significantly outperform random or broad investing by homing in on startups with the best success profiles. However, it's worth noting that real-world accuracy can vary over time; Crunchbase itself cautions that their 12-month forward predictions are ~70+% accurate, reflecting the uncertainty inherent in longer horizons.

However, algorithms excel primarily at near-term, binary outcomes like "will raise next round or not"—predictions based on recognizable patterns in structured data. Long-term "startup success" measured by significant exits remains stubbornly difficult to forecast algorithmically. The factors that ultimately determine whether a company becomes transformative often hinge on unique innovations, the execution qualities of its team, and adaptability, all of which leave minimal footprints in structured datasets.

AI is undoubtedly helping data providers improve accuracy, completeness, and timeliness. Machine learning models cross-verify information across multiple sources, flag anomalies, and intelligently fill gaps with well-informed estimations. These systems continuously monitor news feeds, regulatory filings, and social media to capture funding events and leadership changes almost in real time. This accelerates data collection dramatically. Instead of waiting for press releases or announcements, AI systems parse patent filings or social media posts and alert users immediately.

This capability enables significantly faster deal sourcing and screening for those who leverage it effectively. The fundamental goal is improving hit rate and efficiency—automatically highlighting the 5 companies out of 5,000 that exhibit the strongest combination of success signals, allowing investors to focus their limited attention where the data suggests it matters most.

Yet this apparent "democratization" paradoxically means investors increasingly access identical datasets and signals as their peers. When the same algorithmic insights are available to everyone with a subscription, the informational edge that historically differentiated venture firms dissolves. Not to mention that these platforms still rely on data that remains an imperfect approximation of reality—compare something as seemingly straightforward as the investor roster of well-known unicorns like Revolut or Bolt across these platforms, and you'll quickly discover discrepancies, particularly in historical datasets.

When everyone has the same information delivered through increasingly similar analytical lenses, what truly distinguishes exceptional investors is precisely what we've been discussing: mastery—the ability to ask questions others aren't asking, see patterns others miss, and exercise judgment that transcends algorithmic recommendation.

The Return of Mastery

I know what you're thinking. It's tempting to end on a romantic note where human expertise triumphantly overcomes cold machinery—the master craftsperson standing resolute against algorithmic encroachment. This is not that story. Or perhaps it is, just not in the way we might expect.

Where, then, does mastery survive in this algorithmic landscape? It persists in three crucial domains:

• The uniquely human capacity to define meaningful problems worth solving—to ask questions no algorithm knows to ask (at least not yet)

• The curatorial judgment to recognize quality amid infinite algorithmic variations—to discern signal from sophisticated noise

• The integration of technical tools with deeply human insights about what fundamentally moves markets and people

Yet we must be honest with ourselves: these are fundamentally different from what mastery once meant. The traditional apprenticeship model assumed that expertise was embodied—knowledge lived in muscles and neurons, not databases. True mastery wasn't just about outcomes but about the transformative journey that turned novices into masters.

We may indeed be witnessing the end of certain forms of human mastery, replaced by systems that can perform without understanding, produce without practice, and create without consciousness. The essential question isn't whether we should resist this transformation but how we redefine human value and purpose when many traditional paths to mastery have disappeared beneath our feet.

New Funds

🇬🇧 Cambridge Innovation Capital - £100M - Opportunity Fund

Cambridge Innovation Capital (CIC) has launched a new £100 million "Opportunity Fund" targeting deep tech and life science companies, backed by Aviva and British Patient Capital. The fund aims to address the UK's late-stage funding gap by offering up to £20 million per investment in growth-stage companies, with a particular focus on the Cambridge ecosystem. CIC has already made its first two investments into established tech firms that spun out of Cambridge: Pragmatic Semiconductor and quantum computing specialist Riverlane. This initiative comes amid concerns about UK deep tech companies seeking overseas funding, with foreign capital accounting for 60% of late-stage VC investments in the UK compared to just 15% in the US. The fund is part of the broader goal to establish the Oxford-Cambridge corridor as the heart of "Europe's Silicon Valley."

🇦🇹 Fund F - €28M - First Fund - Final Closing

Vienna-based Fund F has closed its first fund at €28 million, significantly exceeding its initial target of €20 million. The venture capital firm focuses specifically on female-founded startups, requiring portfolio companies to have at least one female co-founder with equal representation on the cap table. Led by Lisa-Marie Fassl and Nina Wöss, the fund plans to invest approximately €300,000 per startup in 25 pre-seed and seed-stage companies across Europe, while reserving 60% of the fund for follow-on investments.

The European Investment Fund (EIF) led the final closing with a €10 million commitment, alongside other supporters, including Austria Wirtschaftsservice GmbH (AWS), Raiffeisen Landesbank Steiermark, and super angel Hansi Hansmann of the Hanswomen Group. The fund's LP base also includes entrepreneurs, angel investors, family offices, and institutional investors, with one-third being women.

Fund F follows a sector-agnostic investment strategy but prioritizes climate tech, femtech & healthtech, fintech & insurtech, and HR tech. Since its first closing, the fund has already invested in 14 companies, including senevo, KOA Biotech, AI-BOB, Sirius, and Cordon Technologies. Vienna stands out as a hub for female entrepreneurship in Europe, with 35% of Viennese startups founded by women (25% higher than the rest of Europe).

🇩🇰 IDC Ventures - €150M - Fund of Funds

Copenhagen-based IDC Ventures (IDCV) has launched its inaugural fund of funds, VC4 FoF I, with a €150M cap and €33M already secured in its first closing in January 2025. The fund takes a conservative investment approach while maintaining broad diversification across investment stages, geographies, and technology sectors. VC4 FoF I aims to preserve capital through diversification in top-tier technology venture capital funds, planning to invest in approximately 30 funds with a focus on sectors including fintech, marketplaces, and healthtech across the US, Latin America, and Europe. Led by Managing Director Bobby Aitkenhead and Managing Partner Gonzalo Hinojosa, the fund has partnered with Creand Wealth Management to establish an exclusive investment vehicle for institutional and high-net-worth investors. The GPs have already invested €15M across 10 funds, including Soma Capital, G Squared, and Ensemble, with some achieving over 4x returns in previous investments.

New Rounds

🇺🇸 Achira - €31.54M - Seed

Greek co-founded Achira has raised €31.54M in seed funding led by Dimension, with participation from Amplify Partners, Compound, and NVentures (NVIDIA's VC arm). The biotech startup combines AI and physics-based simulations to create high-fidelity, scalable models for molecular dynamics in drug discovery. The company's goal is to "turn drug discovery into 90% compute and 10% experiment," with first-generation models expected to be announced later in 2025.

🇨🇭 amnis - €10.7M - Series B

Zurich-based fintech AMNIS Treasury Services (amnis) has secured €10.7M in Series B funding led by Swisscom Ventures, with participation from existing investors including Lansdowne. The round also includes a CHF 2M non-dilutive debt agreement with Swiss growth capital investor Lendity. Founded in 2014, amnis focuses on global transaction banking for SMEs, offering currency exchange, cross-border and local payments, real-time transfers, and local accounts in Switzerland, Germany, Great Britain, and the US. The company serves over 3,000 companies across 35 countries and plans to expand into additional European markets while enhancing its offerings with e-commerce solutions, accounting integrations, and embedded card solutions.

🇮🇹 Arsenale Bioyards - $10M

Arsenale Bioyards, an Italian neo-industrial company transforming biomanufacturing, has raised $10M in funding led by Planet A and byFounders, with additional backing from CDP Ventures, Acequia Capital, Plug N Play, Grey Silo Ventures, and other investors including industrial family offices. The company's proprietary platform integrates cutting-edge software with advanced bioreactors to make precision fermentation far more cost-effective—cutting expenses by up to 90%. The company already operates a pilot site in Pordenone, Italy, equipped with 1,000-litre precision fermentation capacity, including advanced bioreactors.

🇬🇧 Audiological Science - £12.4M

London-based Audiological Science, a provider of hearing-related medical technology, has received a £12.4 million investment from YFM Equity Partners. The company provides a range of ear health products, including hearing tests and hearing aids.

🇫🇮 Behavix - $2.5M - Seed

Helsinki-based Behavix has secured $2.5M in seed funding led by Vendep Capital and Superhero Capital, with participation from several angel investors. Behavix, a behavioral data company, offers valuable consumer insights using advanced AI and machine learning. Their platform provides real-time, high-precision analytics from opt-in, privacy-compliant online panels, making it a reliable alternative to traditional, fragmented market research data.

🇩🇪 Bliro - €2.8M

Munich-based Bliro has raised €2.8 million in funding led by LEA Partners, with participation from 468 Capital and Rockstart. The AI assistant company provides a conversation intelligence platform that works across all communication channels — whether in-person, on the phone, or in virtual meetings — without requiring intrusive bots or specific integrations. Unlike traditional platforms, Bliro transcribes fully in real-time, ensuring no audio recordings are created, which makes it easier to use in compliance with GDPR regulations. The company recently announced its iOS app, which transcribes and analyzes face-to-face conversations wherever they happen. Bliro is currently used by over 1,000 companies, including ImmoScout24, OMR, and Telefónica Germany.

🇬🇧 ClearScore - £30M - Debt Financing

London-based ClearScore has secured £30M in debt financing from HSBC Innovation Banking. The credit score and financial services provider, which has nearly 24 million customers, plans to use the funding to drive growth in the UK and overseas markets. ClearScore noted that previous financing from HSBC has helped the company make strategic acquisitions, including the recent purchase of Manchester-based credit marketplace supplier Aro Finance (its second acquisition after buying Moneyboard in 2022), expand its secured loan offerings, and enter the embedded finance space. Founded in 2015, ClearScore provides credit information and an online financial marketplace, is backed by Blenheim Chalcott, Brightbridge Ventures, Lead Edge Capital, and QED.

🇬🇧 Crown Plus - £3.9M

Telford, UK-based highways drainage contractor Crown Plus has raised £3.9M in funding from Midlands Engine Investment Fund II, through appointed fund manager Mercia Ventures. Founded in 2015, the company has developed its own range of equipment for the refurbishment of filter drains and gravel-filled drainage systems that need regular maintenance. Their most recent innovation, the VERGEBlaster, extracts weeds and cleans on site, reducing waste sent to landfill.

🇩🇪 ctrl+s - €1M - Seed

Berlin-based climatetech ctrl+s has raised €1M in seed funding led by HTGF, with support from industry expert and angel investor Benjamin Schulz. The company specializes in providing high-resolution insights into supply chains to support effective sustainability strategies and decarbonization efforts. They offer two main products: "item+s," which quantifies baseline sustainability impacts, and "supplier+s," a platform designed to engage suppliers in carbon reduction initiatives. Their recently enhanced "supplier+s" solution includes a carbon accounting module that streamlines the process of determining baseline carbon footprints, identifying high-emission suppliers, and facilitating collaborative emission reduction efforts. Given that 80% of a company's total emissions typically originate from its supply chain, ctrl+s provides a data-driven solution for fast, scalable, and precise CO₂ management without requiring extensive data collection, by combining statistical models with supplier-specific data. The company is already profitable and will use this seed funding to further develop its technology and expand its market reach.

🇧🇬 EnduroSat - €20M

Bulgarian space tech company EnduroSat has secured €20M in funding in a round again led by CEECAT Capital, with participation from other existing investors. A new investor, Romanian private equity firm Morphosis Capital, has joined the round, acquiring a minority stake in the company. EnduroSat develops "Satellite-as-a-Service" solutions that remove legal, technical, and logistical barriers to space data access. This funding comes almost two years after EnduroSat's €9.62M Series A round, bringing their total funding to €48M. EnduroSat currently collaborates with over 210 customers across commercial, scientific, and academic sectors worldwide.

🇳🇱 EvidenceHunt - €1.2M

Netherlands-based EvidenceHunt has raised €1.2M in funding led by Keen Venture Partners, with participation from Dff.ventures and Slimmer AI. Notable angel investors include Jeroen Tas (former Chief Strategy and Innovation Officer at Philips), Dinko Valerio (former CEO and Founder of Crucell), and James Shannon (former Head of Global Drug Development Novartis). The AI-powered medical research platform enables healthcare professionals to analyze medical data by streamlining the process of gathering and utilizing medical evidence. It quickly finds and summarizes biomedical publications, making complex medical literature more accessible. Launched 18 months ago, EvidenceHunt has already grown to 25,000 global users, including healthcare professionals, medical science experts, researchers, and students.

🇸🇪 Fibbl - €3M

Swedish 3D and AR platform Fibbl has raised €3M in funding led by Industrifonden. The company offers a platform that helps brands use 3D and augmented reality in their business. It starts with creating high-quality 3D models of physical products, which improves online shopping by replacing regular product images and videos. Their platform boosts customer interaction with features like 3D viewers, virtual try-ons, and augmented reality tools. It also gives content creators standard 3D files for marketing teams to make more marketing content and CGI experiences.

🇪🇸 Flanks - €14M

Flanks, a Barcelona-based wealth management technology company, has raised €14M in funding led by Motive Ventures, with participation from Battery Ventures and existing investors Earlybird, JME Ventures, and 4Founders Capital. Established in 2019, the company empowers the advisory services sector with its Flanks LUME solution, automating manual processes and converting intricate wealth data into actionable insights. More than 100 banks, advisors, and major financial institutions utilize its solutions, managing portfolios valued at over $39 billion through their platform.

🇷🇴 Footprints AI - €2.3M

Romanian retail media company Footprints AI has secured €2.3 million in funding led by Catalyst Romania (€1.5 million), with participation from SeedBlink (€100,000) and other private investors, including previous backers. Founded in 2017 the company provides an AI-powered retail media and data insights platform that integrates online and offline data for precise targeting and campaign optimization. The company has experienced significant growth, with revenue increasing sixfold in 2024 compared to the previous year. Footprints AI currently analyzes data from over 25 million consumers monthly and has partnerships with major retailers like Carrefour, Altex, Profi, and Wolt.

🇩🇰 Fuse Vectors - $5.2M - Pre-Seed

Copenhagen-based biotech startup Fuse Vectors has secured $5.2 million in pre-seed funding led by HCVC, with additional support from investors including BioInnovation Institute, EIFO, and Innovation Fund. The company develops a novel cell-free viral vector technology for gene therapy, replacing traditional, cell-based manufacturing methods that have hindered progress due to inefficiency and high costs. Fuse Vectors uses controlled biochemical reactions to produce viral vectors with greater precision, reducing production time and cost. Their enzymatic AAV capsid filling process eliminates cell-based AAV production through efficient technologies storing components in a module library.

🇬🇧 Ignota Labs - $6.9M - Seed Funding

Ignota Labs, a Cambridge, UK-based AI-driven drug turnaround company, has raised $6.9M in Seed funding led by Montage Ventures and AIX Ventures, with participation from Modi Ventures, Blue Wire Capital, and Gaingels. The company rescues promising but failing drugs, bringing new life to abandoned projects for patients. Their proprietary platform, SAFEPATH, uses deep learning to address safety challenges by uncovering the mechanisms behind drug toxicity, combining cheminformatics, bioinformatics, and multimodal data analysis to explain why and how safety issues occur.

🇧🇪 Jurimesh - €1.6M - Pre-Seed

Belgian legaltech company Jurimesh has raised €1.6 million in pre-seed funding led by Syndicate One, with participation from multiple business angels. The company develops an AI-driven due diligence platform that transforms the traditionally slow, costly, and error-prone legal due diligence process. Jurimesh integrates with data rooms, leveraging advanced AI-powered document recognition and Large Language Models to identify risks, suggest recommendations, and generate due diligence reports. Working closely with M&A law firms, the company has proven that due diligence can be faster, more accurate, and less labor-intensive. Notable angel investors include executives from Lighthouse, Teamleader, Aikido, Officient, Vendorvue, Intersentia, Yuki, Deloitte, Dovesco, and Henchman.

🇧🇪 Karomia - €2M

Ghent-based Karomia has raised €2 million in funding led by Entourage, imec.istart Future Fund and imec.istart Fund. Founded in 2024, the company has developed an AI-powered platform that streamlines Corporate Sustainability Reporting Directive (CSRD) compliance and ESG reporting. Their solution reduces reporting time by 90%, producing CSRD-compliant reports in hours rather than months by using AI to analyze company data, fill ESG reports, and flag missing information. The platform is currently used by over 45 customers across Europe and the US, from large enterprises to SMEs.

🇳🇱 LangWatch - €1M - Pre-Seed

Amsterdam-based LangWatch has raised €1M in pre-seed funding led by Passion Capital, with participation from Volta Ventures and Antler. The startup develops the first LLMops (Large Language Model Operations) platform to monitor, assess, and improve LLM-powered applications. For AI engineers, the platform offers advanced optimizers that identify effective prompts and models, reducing costs by supporting switches to more efficient alternatives.

🇬🇧 Leafr - £600K - Funding

London-based Leafr has raised £600K in funding led by Haatch VC, with participation from NextStep, Venture Catalysts and a handful of angels. The sustainability platform bridges the gap between corporates and sustainability talent, offering SMEs access to sustainability experts at about one-third the cost of traditional consultancies. The company has over 1,000 vetted sustainability consultants in its network, specializing in areas such as retail, manufacturing, and professional services. Notable clients include WD40, Freddie's Flowers, and the UN Foundation.

🇸🇪 Lovable - $15M - Pre-Series A

Swedish AI startup Lovable has raised $15M in pre-Series A funding led by Creandum. The company enables anyone to build production-ready software without coding knowledge through their GPT Engineer platform, which can create fully functional web apps through simple prompting. Lovable claims to have reached $17M in annual recurring revenue with 500,000 users building over 25,000 new products daily and 30,000 paying customers. This impressive growth was achieved with just $2M in capital from a €6.8M pre-seed round led by Hummingbird Ventures and byFounders last October. The company plans to expand its integration with third-party services, including Supabase for databases and GitHub for code storage. Angel investors in the round include Charlie Songhurst (Meta board), Adam D'Angelo, Thomas Wolf (Hugging Face), and Eric Bernhardsson (Modal).

🇬🇧 Magdrive - £8.3M - Seed

Oxfordshire-based spacecraft startup Magdrive has secured £8.3M ($10.5M) in seed funding as it prepares for its first in-orbit tests. Led by Redalphine, the round included contributions from Founders Fund, Balerion, Alumni Ventures, Outsized Ventures, 7percent, and Entrepreneur First. Founded in 2019, Magdrive is developing next-generation spacecraft propulsion technology. The company plans to conduct its first tests of the Magdrive Rogue thruster in June through a collaboration with D-Orbit. The funding will support building a new manufacturing facility in the UK and establishing a US office as the company works to scale its propulsion system to support increased commercialization of the space industry.

🇬🇧 Monument Therapeutics - £850K

Monument Therapeutics, a Manchester, UK-based neuroscience company applying digital biomarkers to psychiatric drug development, has raised £850K in funding led by ACF Investors, with participation from Wren Capital, o2h Ventures, and angel investors. Monument Therapeutics leverages digital assessments of cognition to match patients with new pharmaceutical treatments. The company has developed MT1988, a novel fixed-dose combination drug for the treatment of CIAS (Cognitive Impairment Associated with Schizophrenia). MT1988 has shown excellent pre-clinical results, combining two well-characterised small molecules that act on nicotinic receptors to enhance cognitive function while mitigating common side effects. The drug is intended to be used alongside existing antipsychotic medications, offering a complementary solution for patients.

🇮🇹 Mopso - €1M - Seed

Milan-based regtech startup Mopso has secured €1 million in seed funding led by Apside, the 50/50 investment joint venture of Intesa Sanpaolo and Zest S.p.A., along with Fin+Tech, Centro Istruttorie, and various business angels. Founded in 2021, the company specializes in AML and financial crime prevention. Mopso leverages semantic web technology and digital identity to streamline compliance processes. Their flagship products include Brain, which identifies suspicious transactions and high-risk clients by integrating millions of internal data points with external datasets, and Amlet, which enables the portability and reusability of due diligence data within an ecosystem of intermediaries. The company, which counts banks and asset management firms among its clients, recorded a 70% year-over-year revenue growth in 2024.

🇬🇧 Napo - £12M - Series B Funding

Napo, a London-based pet care company, has raised £12M in Series B funding led by Mercia Ventures, with participation from existing investors DN Capital, Companion Fund, MTech Capital, Helvetia Venture Fund, and others. The company offers comprehensive pet insurance that includes treatments such as dental cover and behavioral treatment.

🇵🇱 Nomagic - €41.94M - Series B

Polish AI-powered robotics company Nomagic has secured €41.94M in Series B funding led by EBRD Venture Capital, with participation from Khosla Ventures, Almaz Capital, and European Investment Bank (EIB). Founded in 2017, the company provides AI-powered robotic picking solutions that seamlessly integrate into e-commerce and multichannel fulfillment operations. Their technology optimizes efficiency and reduces costs for clients including Apo.com, Arvato, Asos, Brack, Fiege, Komplett, and Vetlog.one. The company has reported 220% ARR growth in 2024 and is targeting another 200% growth in 2025. Nomagic will use the funding to expand deployments across Europe, further develop its AI and robotics technology, and scale operations to support growing customer demand.

🇬🇧 Nothreat - Undisclosed - Seed Funding (£40M Valuation)

Nothreat, a London-based cybersecurity company specializing in AI-driven security and IoT protection, has raised an undisclosed amount in Seed funding, with the company confirming a £40M valuation. The round was led by Algara Group. Nothreat specializes in AI-powered cybersecurity solutions that offer real-time protection against cyber threats. Its continuous learning AI detects zero-day threats with 99% accuracy, identifying 55% more attacks than conventional systems. A key innovation is AIoT Defend, a lightweight, software-based firewall designed for IoT devices. Consuming only about 2 MB of RAM, it provides real-time, on-device protection without additional hardware. Nothreat is working with Lenovo to enhance IoT edge device security and is supporting Azerconnect Group in strengthening cybersecurity efforts at COP29, a climate conference organized by the United Nations.

🇬🇧 OneUp - £1.5M

Tamworth, UK-based OneUp has raised £1.5M in funding from Midlands Engine Investment Fund (MEIF) and Mercia Ventures. The company provides a platform that uses gaming technology to manage and motivate sales teams, enabling managers to track data, gain insights to improve performance, incentivize teams, and celebrate success. The company currently employs 40 people and has an ARR of £2.7 million, serving over 350 customers, including Hitachi Vantara and leading recruitment agencies such as Xcede and Premier Group.

🇬🇧 OrganOx - $142M

Oxford-based OrganOx has raised $142 million in funding led by Farallon Capital Management, with participation from Baillie Gifford, Octopus Investments, and Oxford Science Enterprises. The company, a spinout from Oxford University, has developed a portable normothermic machine perfusion device that maintains donor livers in a functioning state outside the body for up to 24 hours before transplantation. This technology has been shown to preserve higher-risk donor livers while potentially increasing the viable organ pool. OrganOx's flagship product, the metra, is FDA-cleared and CE-marked, and the company plans to use the funding to accelerate U.S. commercial expansion, advance its next-generation liver device, and broaden the application of its technology to other organs.

🇩🇪 QRaGo - €2.7M - Seed

German healthtech QRaGo has secured €2.7M in Seed funding led by āltitude and MobilityFund, with participation from existing investors including Segenia Capital and capacura. The company provides a digital platform that streamlines healthcare logistics for patient and material transport, connecting medical facilities, laboratories, transport companies, and health insurance providers to enhance efficiency and transparency. Their system enables healthcare providers to order transports within 30 seconds and receive real-time updates on arrival and departure times, while transport companies benefit from automated requests and optimized route planning. The company has announced new partnerships with Uber for transport and Debeka for health insurance, strengthening its service offering. QRaGo plans to double its reach this year and expand into Austria and Switzerland.

🇳🇱 QT Sense - €6M

Dutch startup QT Sense has secured €6 million in funding combining equity investment from QDNL Participations, angel investors, and grant funding from Interreg Europe. The company founded in February 2024 as a spinout from University Medical Center Groningen, develops technology based on specially prepared nanodiamonds that interact with individual cells. By monitoring the light emitted from these nanodiamonds, researchers can measure cellular activity in real-time at a single-cell resolution. Their technology has transformative potential for disease research and treatment, particularly for early sepsis detection, personalized cancer treatment, and drug development, offering deeper insights into cellular activity than current technologies can match.

🇬🇧 Relay - £27.6M - Series B

London-based Relay has raised £27.6M ($35M) in Series B funding led by Plural VC, with participation from Project A and Prologis Ventures. The ecommerce logistics startup is developing a "decentralised delivery model" made up of hyperlocal nodes that reduces shipping distances, consolidates deliveries, and cuts operating expenses. Its AI-powered platform assigns parcels, fine-tunes route pricing, and calculates minimum travel distance required, claiming to reduce delivery distances by up to 95% compared to existing systems. Customers include THG, My Protein, and Glossybox. The company previously raised £8M in 2023.

🇧🇪 Salvus Health - €500K

Antwerp-based Salvus Health has raised €500K to advance its smart service platform for pharmacists. Founded in 2020 by biomedical engineer Philip Van den Bergh and Catalan serial entrepreneur Salvador Severich, Salvus helps pharmacists reclaim time and focus on their advisory role by automating repetitive tasks like scheduling appointments and sending reminders. Their platform includes an integrated CRM system for targeted patient communication, such as displaying inhaler usage instructions or tracking medication adherence, and seamlessly integrates with third-party platforms. The company already serves over 150 pharmacies and approximately 100,000 active patients, with 50,000 vaccination appointments booked through the platform last year. Salvus aims for a 20% market share among Belgium's 4,500 pharmacies in the short term, with plans to expand into neighboring European countries.

🇬🇧 Shop Circle - $60M - Series B

Shop Circle, a London-based e-commerce solutions provider, has raised $60M in Series B funding led by Nextalia Ventures, with participation from Endeavor Catalyst and existing investors NFX, QED Investors, 645 Ventures, 3VC, and i80 Group. The company integrates multiple e-commerce apps into one unified platform, addressing the challenge merchants face when using dozens of separate providers for supply chains, inventory, and marketing. Shop Circle has experienced 110% year-on-year revenue growth and completed the acquisition of guided-selling software Aiden. Their deep integration with Shopify makes them the largest solutions provider in the Shopify app store, processing over 1 million trades weekly for 50 million users.

🇫🇮 Solid IO - €800K

Helsinki-based Solid IO has secured €800K in its first funding round led by Nordic Science Investments, with participation from BSV Ventures, Helsinki University Funds and a private European investor. The University of Helsinki spinout has developed a tumour-on-chip platform that replicates the patient's tumour microenvironment, generating high-accuracy, real-time data on how individual cancers respond to immunotherapies and combination treatments. Their technology integrates bioengineering organ-on-chip technology to help clinicians select the most effective therapy from day one, improving patient outcomes while reducing unnecessary side effects. Beyond improving personalized patient care, Solid IO's platform also serves pharmaceutical R&D by offering early patient stratification, biomarker validation, and treatment-response modeling.

🇨🇭 Sparta - $42M - Series B

Geneva, Switzerland-based Sparta has raised $42M in Series B funding led by One Peak, with continued backing from Singular and FirstMark. The company provides real-time market intelligence and analytics for global commodity traders, delivering actionable insights, price transparency, and data-driven decision-making tools that empower traders to stay ahead in fast-moving markets.

🇸🇪 SponsWatch - €1M - Seed

Stockholm-based SponsWatch has secured €1 million in seed funding led by node.vc, with participation from Venrex. The AI-powered sponsorship analytics company uses AI and ML to measure sponsorship exposure across various media platforms, including TV, social media, and podcasts. Their technology provides precise, data-driven insights to help brands and sports organizations optimize sponsorship strategies and better measure return on investment. The company's clients include top-tier Swedish football and hockey clubs, national and international federations, brands, teams, and athletes.

🇩🇪 Taktile - $54M - Series B

Berlin-born, New York-based Taktile has raised $54M in Series B funding led by Balderton Capital, with participation from existing investors Index Ventures, Tiger Global, Y Combinator, Prosus Ventures, Visionaries Club, and Larry Summers (former US Treasury Secretary). The AI decisioning platform empowers fintech companies and banks with complete control over AI-powered risk decisions through a no-code, highly flexible platform that allows teams to design, test, and optimize decision logic in real-time without depending on engineers. The company has assisted customer Zilch in reducing service provider and usage costs by 50% and serves clients across 24 markets, including the previously mentioned Zilch, Mercury, Kueski, Allianz, and Rakuten Bank. The funding increases Taktile's total raised to $79 million.

🇩🇰 TrackSights - €1M - Pre-Seed

Copenhagen-based TrackSights has secured €1 million in pre-seed funding from Maki VC. The startup is transforming automotive data intelligence with a platform that consolidates and simplifies data across the automotive market and specific vehicles, providing instant, actionable insights. TrackSights addresses the automotive industry's reliance on clipboards, spreadsheets, and fragmented data by offering a one-stop platform with a 360° view of the market. The startup validated its business model early, onboarding nine customers within the first two weeks. Their solution serves car dealerships for inventory and pricing decisions, leasing companies for forecasting residual values, financial institutions for risk assessment, and insurance companies for more accurate vehicle valuations.

🇬🇧 uFraction8 - £3.4M

Falkirk, Scotland-based uFraction8 has raised £3.4M in funding led by Foresight Group, with participation from the University of Edinburgh's Old College Capital, Scottish Enterprise, Alwyn Capital, Thia Ventures, and a grant from the Polish Agency for Enterprise Development. uFraction8 develops microfluidics-based filter systems that help bio-manufacturers increase productivity with energy-efficient and scalable perfusion systems. Their approach uses hydrodynamic phenomena as a new mechanism of filtration that can outcompete conventional systems in key areas. The company simplifies industrial processes using cell cultures to produce food, bio-pharmaceuticals and other bio-based products and chemicals.

🇨🇭 Unique - $30M - Series A

Zurich-based Unique has raised $30 million in Series A funding led by DN Capital and CommerzVentures, with Pictet listed as a strategic investor. Founded in 2021, Unique develops an AI platform for financial services, offering customizable AI agents for banking, insurance, and private equity clients. Their solutions include an investment research agent and a due diligence agent that examines documents like meeting transcripts to suggest potential questions for bank personnel. The company serves major Swiss financial institutions including Pictet, UBP, and Graubündner Kantonalbank. Originally focused on AI-powered video for sales teams, Unique evolved into a "co-pilot for finance teams" and plans to use the funding to accelerate international expansion, particularly in the US market. The company has raised a total of $53 million to date.

🇫🇮 Videobot - €2.8M

Finnish SaaS startup Videobot has raised €2.8M in funding led by Volta Ventures, Expon Capital, and Superhero Capital. The company has developed the world's first video experience (VX) platform that merges short-form video and AI-powered chatbots to enhance customer engagement. The company has already expanded to over 20 countries, with clients reporting up to 5x higher conversion rates. This latest investment brings Videobot's total funding to €5.5M, including an initial €2.2M in 2023 and €500K from Business Finland's Young Innovative Company program.

🇳🇱 Vivici - €32.5M - Series A

Netherlands-based Vivici has secured €32.5M in Series A funding led by state fund Invest-NL and pension fund ABP, with participation from The Hague's InnovationQuarter, as well as existing shareholders DSM-Firmenich and Fonterra which formed the startup as a joint venture in 2022. The precision fermentation company produces animal-free dairy proteins with their technology combining traditional fermentation with biotechnology advances to efficiently produce dairy proteins without animals. According to an independent assessment, their beta-lactoglobulin has a 68% lower carbon footprint than its conventional counterpart and uses 86% less water. Vivici plans to use the funding to expand production of its beta-lactoglobulin protein, enter new markets, and launch bovine lactoferrin in the second half of 2025 under its Vivitein brand. The company has already obtained regulatory clearance in the US through self-affirmed GRAS status and is targeting markets including the EU, Singapore, the UK, and Canada in the near term.

🇬🇧 WilsonAI - $1.7M - Pre-Seed

London-based WilsonAI has raised $1.7M in pre-seed funding led by Nomad Ventures, with participation from Autopilot Ventures, Entrepreneur First, Transpose Platform, and several strategic angels including Mei Z and various exited founders and law firm partners. The company develops an AI paralegal platform designed to assist in-house legal teams by automating routine tasks and streamlining legal operations. Their system manages legal requests by triaging inquiries, providing instant answers, and automating workflows, helping reduce the workload of legal professionals. WilsonAI also offers features such as knowledge management, information gathering, and automated reporting, enabling organizations to track key metrics like query resolution times. The company has already deployed its AI paralegal with 10 technology companies and will use the funding to enhance its AI capabilities, expand integrations with existing legal tech stacks, and accelerate customer onboarding across industries.

🇩🇰 ZeroNorth - $20M - Debt

Copenhagen-based ZeroNorth has secured $20M in funding from CIBC Innovation Banking. The company optimizes the shipping industry through AI-driven technology that helps reduce fuel consumption and carbon emissions. Since its founding in 2020 as a spin-off from Maersk Tankers, ZeroNorth has quickly established itself as a leader in maritime digital transformation, with its platform streamlining 1.5 million voyages in 2024 alone, resulting in over one million metric tonnes of CO2 emissions reduction. The company serves over 230 customers across the shipping industry with six core services, and reached profitability in December 2024 with nearly $40M in annual recurring revenue. The funding will support expansion through acquisitions, technology enhancement, and growing its 600-person workforce across ten global locations.

Acquisitions

🇳🇱 Just Eat Takeaway - €4.1B - Acquisition

Amsterdam-based Just Eat Takeaway.com is being acquired by Prosus for €4.1 billion in an all-cash deal, marking one of the largest acquisitions in Dutch tech history. Prosus — the investment arm of South African tech firm Naspers — has agreed to buy Just Eat Takeaway's shares at €20.30 each, a 22% premium over the company's recent three-month high but only a fifth of its pandemic-era peak of above €100 per share. Following the announcement, Just Eat Takeaway's shares climbed 53% on the Amsterdam Stock Exchange. The company, which was formed in 2020 through the merger of UK-based Just Eat and Dutch company Takeaway.com, will maintain its current leadership under the agreement. Prosus already owns iFood (Latin America's largest food delivery platform) and has stakes in Delivery Hero, Meituan, and Swiggy. The deal will create the world's fourth-largest food delivery group.

🇳🇴 Vev - Undisclosed - Acquisition of TIME Sites

Norwegian no-code design platform Vev has acquired TIME's website builder, TIME Sites, strengthening its position in the enterprise web development space. As part of the acquisition, Salesforce co-founder and TIME owner Marc Benioff has become a shareholder in Vev. Founded in 2017 Vev enables organizations to create interactive content and websites without complex coding, reducing time-to-market by up to 90% compared to traditional workflows. Their platform is used by brands like LIDL U.S., Schibsted, Politico Studio, and Pfizer.

TIME Sites, acquired by TIME in 2022, enables business users to quickly create dynamic, personalized customer experiences. Following the acquisition, Kristina Valkanoff from SITES will join Vev as Country Manager for the United States. The acquisition significantly enhances Vev's U.S. market presence, which already accounts for 60% of its customer base. The company has raised $7M in funding to date and has 33 employees across 6 countries. Financial terms of the deal were not disclosed.