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Lovable closed a $400 million Series C at a $13.3 billion valuation, and the investor list reads less like a funding round than a map: Menlo Ventures leading, EQT's Scaleup Europe Fund co-leading, and new money arriving from Balderton Capital and Carmignac in Europe, Kaszek Ventures and LTS Growth in Latin America, Tencent and World Innovation Lab in Asia, and Regent in the United States. Accel, Antler, CapitalG, DST Global, Evantic Capital, HubSpot Ventures and Salesforce Ventures all returned.

The geographic spread is the point. Lovable's pitch is that the people closest to a problem should be able to build the software that solves it, and that constituency is not concentrated in any one market. Assembling backers on four continents is also a practical hedge for a European company that intends to sell everywhere at once.

The numbers behind the round

Since opening in November 2024 the Stockholm company counts more than 60 million projects created on the platform and over 900 million monthly visits to the applications people have built with it. Its reach inside large enterprises went from employees at half the Fortune 500 in year one to nearly two-thirds now.

Those are impressive figures, though they need reading carefully. A project created is not a business launched, and enterprise reach measured by individual employees signing up is a weaker signal than seats an organization has actually bought. The more telling number is what users say they intend.

Close to eight in ten told the company they are building a business or a monetizable side project, and over a third of that group already report revenue — self-reported, but enough to reframe Lovable from a prototyping toy into something closer to the substrate a small company runs on.

Shipping the boring parts

The product work since December 2025's Series B has been correspondingly unglamorous and load-bearing. Payments arrived so builders can charge for what they make; SEO and AI-search tooling so anyone can find it; connectors into Google Workspace, Microsoft 365, Salesforce, Stripe and ElevenLabs so it fits an existing stack. On the governance side the company added scheduled security scanning, publishing controls, abandoned-app cleanup, workspace insights, per-app trust centers, and AIUC-1 certification, which it bills as the first security standard written for AI agents.

That list is the tell. Tools that let non-engineers generate software tend to hit a wall the moment the software matters, because nobody has answered who patches it, who can publish it, and what happens when the person who made it leaves. Building the compliance scaffolding first is what separates a company chasing weekend projects from one chasing budget lines.

The customer stories track the same shift from experiment to dependency. A product executive at Nursa spent one weekend building an enterprise product for nursing schools; the company subsequently deployed Lovable to more than 200 staff, rebuilt its core platform far faster than planned, and started decommissioning ten SaaS subscriptions as teams replaced them with their own tools. Brazilian founder Rafael Milagre assembled the CRM, finance systems and AI sales workflows for a 54-person education company serving over 1,200 clients. In Britain, Lex Deak built a fashion discovery app he credits with saving £25,000 to £30,000 a month.

Teams at Adidas, NVIDIA and Deutsche Telekom use it internally for much the same reason, and Zendesk senior product director Jorge Luthe described the arc plainly: a quick prototyping trick that turned into how his teams build internal training tools and roadmap applications instead of paying for off-the-shelf equivalents. Each of those anecdotes is a SaaS vendor losing a renewal, which is the part of this story the software industry should be reading closely.

The next chapter

Three priorities shape what the capital funds. The product is meant to get proactive — noticing what needs attention and doing work unprompted — while integrations reach deeper into corporate systems and security, permissions and governance keep hardening.

Then there is a training loop aimed at outcomes rather than correctness: the company wants to learn not merely whether an app was built properly but whether it generated revenue or fixed a workflow, and to push those aggregate lessons back to everyone building. It will keep matching each slice of work to whichever model handles it best, post-training open-source models along the way. Staying model-agnostic is a deliberate bet that the advantage sits in the platform rather than in any single vendor's weights.

Finally, hiring. Roughly 450 employees by year end, weighted toward machine learning, product, infrastructure and security, with Stockholm remaining the center of gravity as London, Boston, San Francisco and New York expand. EQT's Victor Englesson, who co-heads the Scaleup Europe Fund, called Lovable among the most ambitious and fastest-growing AI companies the firm has encountered — and, pointedly, evidence that Europe is not short of founders.

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#series-c

Lovable Raises $400M at a $13.3B Valuation to Turn App Building Into Business Building

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Lovable Raises $400M at a $13.3B Valuation to Turn App Building Into Business Building