Vahan.ai, one of India’s leading AI-driven recruitment platforms focused on blue-collar workers, has raised fresh capital from LemmaTree, the Singapore-based investment arm of Temasek. In a strategic development, Vahan has also acquired L.earn, a mobile-first upskilling platform previously backed by LemmaTree through its initiative GoodWorker.
With this new partnership, Vahan aims to significantly enhance its technology stack and upskilling capabilities to reshape how millions of informal sector workers access job opportunities. “With LemmaTree’s backing and the integration of L.earn, we’re reimagining how workers access livelihoods—through voice-led interfaces, multilingual support, and embedded skills that adapt to each user’s context,” said Madhav Krishna, CEO and founder of Vahan.ai.
Currently, Vahan places around 40,000 workers per month and has facilitated more than 1 million job placements across 920+ Indian cities. The company’s clients include major players such as Zepto, Swiggy, Blinkit, and Zomato. At the core of its platform is a GPT-4o-powered voice-based recruiter, designed to overcome challenges like digital illiteracy and language barriers—common issues among India’s blue-collar workforce.
The recent capital infusion will be used to scale Vahan’s AI capabilities, enhance its multilingual support by adding eight additional Indian languages, and support the company’s planned expansion into international markets, including Southeast Asia and the MENA region.
“This partnership accelerates Vahan.ai’s ambition to build the most advanced AI-led infrastructure for employment in India’s informal sector,” Krishna added. Echoing this vision, Glenn Gore, CEO of LemmaTree, stated, “We are thrilled to join forces with Vahan.ai… unlocking new opportunities for millions, driving both economic empowerment and operational efficiency.”
This move signals a major leap in AI-led employment solutions for underserved labor markets and underscores a growing emphasis on voice-first, inclusive technologies that match India’s complex linguistic and socio-economic landscape.
