Belong, a Bengaluru-based startup, is creating a “Google for people,” as co-founder Rishabh Kaul describes it.
The three-year-old recruitment firm is part of a new crop of companies using technology to simplify hiring processes, from sorting resumés to scheduling interviews. Belong, however, goes well beyond all that.
It scours the internet to unearth publicly available information on any and all possible candidates, including scanning their Twitter accounts, Facebook pages, LinkedIn profiles, and more. “Earlier, a resume was just like a balance sheet—what you declare about yourself at a given point of time,” explained Kaul. “Now, you have a rich stream of constant data.”
After gathering copious amounts of information, the platform ranks potential hires according to their suitability for a role at a particular company—much like how Google tailors search results for each user’s query.
Belong stands out also because it seems to have cracked the code by selling its product to an impressive clientele. This list spans e-commerce behemoths Amazon and Flipkart, telecom provider Airtel, ride-hailing services Ola and Uber, and online grocer BigBasket, among others.
Founded by Kaul, Vijay Sharma, Saiteja Veera, and Sudheendra Chilappagari, Belong’s basic proposition is simple: using artificial intelligence (AI) and machine learning to curate data from social media activity, and from niche platforms such as GitHub, ResearchGate, and Muckrack. “The technology acts like a magnet, finding different pieces of data on every white-collar person,” said Kaul.
The system scans all profiles with uniform precision to match every candidate to a company’s search requirements and previous hiring patterns. Where there is no precedent—say, if the company is setting up a centre for a new technology like the Internet of Things (IoT), or is expanding into an unexplored geographical region—Belong works with the employer to manually feed in ideal candidate profiles.
As companies approve and reject suggestions, the machine learning algorithm learns from the choices and fine-tunes the results further. However, Belong’s system does not eliminate candidates, it only re-orders them. So, while the grunt work is done by technology, the decision-making still lies with the human resources (HR) managers. “We want to make them (the managers) into Ironmen and Ironwomen, so we are being the Jarvis,” said Kaul.
The main cash cow for Belong, which has raised $15 million so far, is annual contracts. Kaul did not reveal how much it charges but said, “typically we need (companies) to hire at least 30 to 40 lateral people in a year for it to make return-on-investment sense.”
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