The round was led by CapitalG and Menlo Ventures’ Anthology fund, with participation from NVIDIA’s venture arm NVentures, Salesforce Ventures, Databricks Ventures, and strategic investors including Atlassian Ventures and HubSpot Ventures. It comes just one month after Lovable announced it had hit $200 million in annual recurring revenue.

The company has grand aims to make software engineering accessible to anyone by promoting “vibe-coding,” a process in which a user describes in plain language the product they want to build or the function of a piece of software they want to create, and AI writes the code to produce that result. 

“Our mission is to let anyone be a builder,” Osika said.

He predicted a world where every company can build its own bespoke software, rather than depending on expensive, and less customized products from major tech vendors. For instance, rather than purchasing different tools for customer relationship management, project tracking, or inventory management, Osika envisions companies using Lovable to simply build whatever they need on demand. 

Companies are already seeing results from some of Lovable’s products. At Zendesk, teams using Lovable have been able to move from idea to working prototype in three hours instead of six weeks, according to Jorge Luthe, the company’s Senior Director of Product. While at management consulting firm McKinsey, Osika said engineers used his company’s product to build in a few hours what they had been waiting four to six months for their internal development team to deliver.

“Anyone being able to go with an arbitrary software problem and just explain it to Lovable and solve it, is becoming a universal reality,” he said. 

Skeptics say that vibe coding doesn’t always result in the best quality software. The code vibe coding tools produce can be inefficient or contain security flaws that could present a serious risk to the company deploying it, depending on what it is being used for. In addition, just because tools like Lovable allow people without any coding experience to create software for their specific needs, it doesn’t mean that those non-developers will be able to maintain that code over time, these critics say.

Lovable says it sees three main use cases emerge among enterprise customers, Osika said. Some organizations are building core business systems entirely on Lovable; others are using it to build internal tools that previously stalled in development backlogs for months; and some product teams are using it to validate ideas with functional prototypes rather than static designs.

“Enterprises are reworking entire workflows with AI, because you can build AI applications with Lovable in just one prompt,” Osika said. “It becomes kind of the work where work gets done.”

Competition heats up in AI-powered coding

Lovable is operating in an increasingly competitive landscape and facing competition from fellow start-ups as well as bigger players that are now releasing their own coding products. While Lovable uses foundational models from OpenAI, Google, and Anthropic to power its own product, these companies are now releasing their own coding tools that could compete more directly.

“We just see them as partners,” Osika said of the competition with major AI labs. “I think as software and AI kind of converges, there’s going to be more overlap in what companies do, but what people say and why they choose us, despite that there are other alternatives, is that Lovable just works.”

Matt Murphy, a partner at Menlo Ventures who led the investment, said that Lovable’s strategy is to build a “beloved layer” of software on top of the AI labs’ models that customers want to pay for. “The numbers speak for themselves,” Murphy said, noting that Lovable has transformed a latent market of tens of millions of people into developers.

“Lovable has done something rare: built a product that enterprises and founders both love. The demand we’re seeing from Fortune 500 companies signals a fundamental shift in how software gets built,” Laela Sturdy, Managing Partner at CapitalG added.