AI app builder Anything secured an $11 million investment at a $100 million valuation. The company aims to provide end-to-end development tools for non-technical users, addressing a perceived gap in the expanding “vibe-coding” market.
The field of “vibe coding,” where users build software with AI tools via natural language prompts, is undergoing significant expansion. This is evidenced by the performance of key companies. In July, Swedish startup Lovable reached $100 million in annual recurring revenue (ARR) eight months after its launch. The company projects closing the year at $250 million ARR and aims for $1 billion ARR within the next 12 months. Separately, Replit announced its ARR increased from $2.8 million to $150 million in less than a year.
This rapid growth has spurred numerous competitors, creating a dynamic field. Nikhil Basu Trivedi, a general partner at VC firm Footwork, noted, “This is one of those spaces where every company is growing like a weed.” He argues that these companies, including Lovable and Replit, share a significant shortcoming. While they excel at generating prototypes, they fall short of enabling users to launch production-ready software because they lack comprehensive infrastructure for a fully functional product.
Anything, an AI application launched a month ago, was created to solve this problem. It offers an integrated suite of tools including databases, storage, and payment functionality, allowing users to move from concept to a published web or mobile app within one platform. This strategy addresses the gap left by other tools that require users to source and integrate their own backend services. The company’s approach demonstrated immediate market fit, achieving a $2 million annualized run rate within its first two weeks.
On Monday, Anything announced it has raised an $11 million financing round at a $100 million valuation. The investment was led by Footwork, with additional backing from Uncork, Bessemer, and M13. Basu Trivedi confirmed the company’s initial growth rate was a critical factor in his firm’s decision to lead the round despite market competition.
The company was co-founded by former Google colleagues Dhruv Amin and Marcus Lowe, who designed Anything to empower nontechnical people. Amin distinguishes their goal from that of competitors, stating, “You haven’t really seen real businesses built on top of any of these tools.” He elaborated on their ambition: “We want to be the Shopify of the space, where people build apps that make money on top of us.” This vision frames the platform as a tool for entrepreneurship.
Amin reports that users have already built and published functional applications on the App Store, including a habit tracker, a CPR training app, and a hairstyle “try-on” app, with some beginning to generate income. The idea for this comprehensive tool emerged less than a year ago. Amin and Lowe, partners since 2021, previously ran a development marketplace that combined AI tools and human developers, which generated around $2 million in ARR. They shut down that business in 2023, pivoting after realizing generative AI would soon offer faster, cheaper solutions.
This pivot led to the development of an AI-powered app-building tool, for which they raised pre-seed and seed funding from Uncork and Bessemer Venture Partners. A central strategic decision was to build all backend infrastructure in-house. This was prompted by their observation that competitors, such as Lovable and StackBlitz’s Bolt, relied on third-party databases like Supabase. They believed an in-house solution would be a key differentiator, even though it required more development time.
Anything is not alone in this strategic direction; other startups like Mocha and Rork are also building their own infrastructure, with Rork projecting $10 million ARR by year-end. The intense competition does not concern Basu Trivedi. “It seems there’s enough demand out there for different types of app-building products,” he said, suggesting the market is large enough to accommodate various approaches and that Anything’s integrated model is well-positioned.
