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Accel leads $150m round for Swedish AI startup Lovable
Swedish AI startup Lovable is reportedly raising over US$150 million at a nearly US$2 billion valuation, led by Accel with participation from Creandum and 20VC.
This development comes after Lovable’s previous funding round in February 2025, where it raised US$15 million in a pre-series A round led by Creandum.
Founded in 2023, the company launched its web app-building product in November 2023.
The platform lets users build full web apps using text prompts, including front-end interfaces and backend functions, with pricing starting at US$25 per month for 250 credits.
For instance, one app created for US$250 contains over 29,000 lines of code.
Lovable recently launched a beta AI agent for code editing and debugging, priced based on usage.
Accel, 20VC, and Lovable have not commented on the funding reports.
🔗 Source: TechCrunch
🧠 Food for thought
1️⃣ AI startups are experiencing compressed growth cycles with unprecedented velocity
Lovable’s trajectory from a $15 million “pre-Series A” to potentially raising $150 million at a $2 billion valuation just months later exemplifies the accelerated funding cycles in AI startups today.
The company’s claim of reaching $50 million in ARR within six months of product launch represents an extraordinarily steep growth curve compared to traditional SaaS benchmarks, where reaching $10 million ARR typically takes 4-5 years1.
The compressed timeline between funding rounds reflects a broader pattern in the AI sector, where investors are moving aggressively to secure positions in startups showing early traction, sometimes before traditional metrics fully validate the valuations.
This pattern creates both opportunities and challenges for founders, who must navigate rapid scaling while building sustainable business foundations.
2️⃣ Usage-based pricing emerging as the dominant model for AI products
Lovable’s decision to charge for its new AI agent based on usage reflects a significant shift in SaaS pricing models directly driven by the economics of AI deployment.
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