The AI in Engineer.ai’s platform, called the Builder, draws from a library of ‘Components’ to build the repetitive blocks in the app.
Conventional thinking says that one needs to know coding or be an engineer to create an application. Engineer.ai proves it otherwise, getting Artificial Intelligence (AI) to do the job, or at least most of it. Says Sachin Dev Duggal, CEO and founder of Engineer.ai, “I am an engineer and many like me don’t want to do repetitive codes like Facebook login. We have to utilise engineers to do the important things—like the logic and flow of an application and actually thinking through a customer’s problem,” he explains. Engineer.ai treats app creation as an assembly line production process. When an app needs to be designed, the majority of it is done in the first couple of hours by the AI on his platform. And then, software engineers (from a workforce of 26,000) work on the little parts remaining to complete the app (like how technicians fix a car’s chassis, engine and wheels in a car assembly line), thereby leaving the repetitive work to AI and focusing on the creative parts that actually need human attention. The AI in Engineer.ai’s platform, called the Builder, draws from a library of ‘Components’ to build the repetitive blocks which have already been built before. “Some 60% of software is ‘Components’ which need not be done again. This could be Facebook login or integration with an analytics provider,” says Duggal. The rest 40% is business logic and design. To do this, Engineer.ai partners with a number of software companies from whom developers are brought on board, depending on the complexity and features of the project/apps that need to be delivered. The developers’ time do not overlap with their original employers. This method also brings down the price that the end-customer has to pay when hiring a full-time developer and building his/her software from scratch. The algorithm also tracks the development of the software and prices it accordingly. Duggal says that 90% of his customers pay less than the maximum price that’s estimated at the time of getting an order. The company has customers starting from school children to enterprises. The company raised $29.5 million in Series A round in 2018 led by venture capital firms Lakestar and Jungle Ventures, with participation from Softbank’s DeepCore. Engineer.ai’s revenue stood at $ 23.1 million in FY18 and is expected to register $45 million in FY19. It aims to cross the $100-million revenue-mark before the end of 2020. “Initially, it was a little challenging to convince the companies to share their workforce with us . But actually, 20 % of their workforce is usually idle in-between their company projects,” says Duggal. Engineer.ai does the project management and resource allocation for its own projects. “So we pay for their people to work with us and avoid all the costs associated with a project for them. It’s a win-win situation for us both. With time, we got more partners providing their workforce,” he says. Currently, over 152 companies are in partnership with Engineer.ai to share their workforce. At the moment, as much as scaling looks like the primary task at hand as a startup, the company is also aiming to improve the quality of the apps developed. Duggal believes that he has a headstart in this space as this market is bound to expand exponentially with more and more people wanting to build applications on their own. He thinks that competition in this space should increase to spread the word about this model of app development.
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