Crowdbotics raises $40M to turn ‘ideas into code’ with managed app development platform
App development can be tedious and difficult, but that’s sometimes only half the battle. Often simply getting the idea itself into code is the hardest part, which means knowing what open-source components are needed to make a project come to life.
That’s where Crowdbotics comes into play. Thea startup today announced it has raised $40 million for its managed app development platform that helps users turn “ideas into code.”
New Enterprise Associates led the Series B funding round with participation from existing investors Jackson Square Ventures, Homebrew, Bee Partners and Harrison Metal. The new round follows the company’s previous funding a year ago in January 2022, which netted the company $22 million.
Crowdbotics differs from a low-code/no-code development platform, which allows users to drag and drop components together to design the flow of an app and have it built and released for them. Instead, the company has users define the requirements for the app, seeks out components and offers fully fleshed out code. That code can then be used immediately as an app or taken by the customer’s software development team to be customized to their needs.
“When low code works, it’s great, but there’s a lot of stuff it doesn’t work for and those are places where you need real code,” Chief Executive Anand Kulkarni told SiliconANGLE in an interview. “The extensibility, the transparency, the power of what you get from using real code to build software, that’s what Crowdbotics gives you.”
Using Crowdbotic’s platform, customers can build and launch React Native and Django apps by using a visual editor that allows them to prototype, design and deploy user interface layouts and backend data models. The system then generates and exports high-quality, auditable source code for each component by following the requirements set forth by the users based on desired use cases.
Kulkarni said that Crowdbotics has a growing and extensible library of open-source components that its platform can choose from, which users can white-list for their projects when they select a use case. These components have been crowdsourced from thousands of open-source projects, thus the name of the company. The arrangement allows the platform to produce full code for components, which can be important for a multitude of industries where security and regulatory compliance are important.
“You get the power of full code, which means that it’s applicable in cases where low code can’t go — which is a much bigger application market than just low code,” Kulkarni said. “If you look at which customers end up using Crowdbotics and you see the most uptick in customer success, it’s in domains where you need to have actual code for security reasons or for compliance reasons. Those are application domains such as healthcare, finance and government, which are our three biggest sectors.”
The company is even an early adopter of GPT-3, OpenAI LLC’s generative AI model capable of understanding conversational language. It uses GPT-3 to allow users to describe screen layouts or features in plain language and then have the platform provide AI-powered code suggestions. These suggestions can then be added to the project with a single click.
The AI isn’t always 100% capable of producing good results, but it’s good enough to have been integrated for producing back-end application programming interface code and layouts, Kulkarni said. It’s just another tool in the company’s toolkit that helps set it apart from other competitors on the market.
Kulkarni said that with the new funding, Crowdbotics will begin by focusing on market education trying to get users to see that there’s an alternative to low-code approaches where you can build apps based on requirements and get full code. Second, he said, the company will expand its product for its existing customers and third it will further expand its own features and capabilities such as adding DevSecOps functions.
The company also intends to expand its current use of GPT-3 by implementing more of it on the platform. In the future, Kulkarni hopes to allow users to describe what kind of an app they want in specific or vague terms and have it take the users’ actual words and create a requirements framework that the platform can then use to create code.
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