Lovable Becomes Fastest-Growing Software Startup In History

The Swedish AI company Lovable has become the fastest-growing startup in history to reach $100 million in revenue. After raising $200 million during a recent Series A round earlier this month, the company announced a new record in Annual Recurring Revenue (ARR) on Wednesday.

According to the announcement, it took Lovable just eight months to surpass the $100 million milestone in subscription revenue after reaching its first $1 million. The company also introduced a new AI agent as part of the update.

“Today, Lovable officially passed $100m in ARR – in just 8 months since our first $1M,” wrote the company. “This makes us the fastest-growing startup, not just in Europe, but in the world.”

Lovable, the popular “vibe coding” platform, also revealed that users have created over 10 million projects to date, averaging around 100,000 new projects per day.

According to Tech.eu, Lovable’s revenue growth has surpassed leading tech companies such as Cursor, OpenAI, and Wiz—recently acquired by Google for $23 billion. What sets Lovable apart is its focus on making software creation accessible to everyone—not just as an assistant for professional developers.

“The biggest barrier to building businesses is coding,” said Anton Osika, CEO and co-founder of Lovable, to Tech.eu. “99 per cent of people have great ideas and can execute on a business, but they don’t know how to write code. Lovable means anyone can go from idea to software in minutes.”

Osika added that the company is still learning about users’ needs and believes AI is making it easier than ever to unlock people’s creative potential.

Lovable also features agentic capabilities—it can search the web in real time, explore a user’s codebase, and debug errors automatically.

The AI agent, Lovable Agent, has been designed to help users develop more complex tasks with higher accuracy and fewer mistakes.

“When you give it a request, it doesn’t just execute—it interprets what you’re asking for, explores your codebase to understand the context, uncovers missing pieces, makes changes, fixes issues as they come up, and wraps it all up with a clear summary,” explained Lovable.