Lovable’s new funding push signals bigger plans for AI-built software

AI software creation platform Lovable has raised $400 million in a Series C round that values the company at $13.3 billion. Lovable announces in an official blog post that Menlo Ventures leads the financing, while EQT’s Scaleup Europe Fund co-leads it.

The round brings in investors including Balderton Capital, Carmignac, Kaszek Ventures, Tencent and Regent. Existing backers Accel, CapitalG, DST Global, HubSpot Ventures and Salesforce Ventures also participated.

Lovable lets users create software applications through AI-assisted instructions rather than conventional coding alone. The company says more than 60 million projects have been created on its platform since its launch in November 2024. It also reports that applications built with Lovable receive more than 900 million visits per month.

Product, security and enterprise expansion

The company plans to use the capital to accelerate product development, infrastructure and hiring. It expects to grow its workforce to about 450 people, focusing recruitment on machine learning, product development, infrastructure and security. Stockholm will remain its main base, alongside expansion in London, Boston, San Francisco and New York.

Lovable says its recent work has focused on helping customers run commercial applications, not just build prototypes. Newer capabilities include payment tools, search engine optimization and AI search features, integrations with services such as Google Workspace, Microsoft 365, Salesforce and Stripe, plus scheduled security scans.

The company also highlights governance tools for workplace use, including publishing controls, workspace insights and visibility over abandoned applications. Lovable says it has obtained AIUC-1 certification, which it describes as a security standard for AI agents.

Its next product phase will make the platform more proactive, according to the company. Lovable says it aims to identify tasks that need attention and help users complete them. It also plans to use aggregated patterns from successful projects to improve its AI systems, while continuing to combine several AI models in one product.