Startups are increasingly turning to native-language artificial intelligence tools to widen their hiring and cut recruitment timelines, particularly for frontline and customer-facing roles where comfort with English has often been a barrier. The shift reflects both the scale of hiring needs in a tight labour market and a growing recognition that language choice can materially affect candidate participation and assessment quality.
Cloud kitchen operator Curefoods began using native-language AI tools for hiring in 2025 after realising that a large share of applicants for roles such as chefs and store operations staff were more comfortable speaking in their native languages. The company now conducts first-level screenings through automated voicebots that interact with candidates in multiple Indian languages, reducing manual effort and shortening time-to-hire.
“We are now able to engage applicants who prefer Hindi, Tamil, Telugu, Kannada, Bengali, and other regional languages, allowing us to tap into a far broader and more diverse talent pool, especially across tier-2 and tier-3 locations,” Richa Batra, group head of HR at Curefoods, told FE. According to the company, automated screening has eased recruiter workload while enabling faster decision-making.
Scaling Recruitment in Bharat
The experience is mirrored across other startups with large frontline workforces. At Flexiloans, which works closely with MSMEs across the country, turnaround time for frontline hiring has improved by about 30–40% after adopting native-language AI tools.
“It has made the entire process faster, more inclusive, and far more accurate. Candidates can respond in a language they are comfortable with, which gives us a truer sense of their abilities,” Ritesh Jain, co-founder of Flexiloans, said. He added that structured insights generated by these systems help reduce bias and speed up shortlisting, particularly for sales, customer-facing and collections roles where spoken communication matters more than written English.
Most startups rely on third-party platforms for such capabilities, driving growth in a cluster of B2B AI firms offering native-language hiring solutions. Companies such as Vahan AI, Bolna AI and Samvadini are seeing rising demand as employers look to scale recruitment without proportionately expanding HR teams.
“We talked to some of the recruiters who use our platform, and they said that startups are using native-language AI hiring because it lets them tap talent in Bharat at scale,” Sarbojit Mallick, co-founder of talent acquisition platform Instahyre, said. He pointed to the IndiaAI NLTM’s Bhashini app, which already supports more than 22 Indian languages, enabling voicebots and chatbots that mirror how hundreds of millions of users communicate on mobile and messaging platforms.
The broader labour market context is also pushing automation. The country’s AI workforce is estimated at about 2.35 million professionals, yet the sector faces a demand–supply gap of roughly 51%. As a result, founders are under pressure to automate high-volume, low-complexity tasks such as initial screening, answering routine queries and interview scheduling. Native-language voicebots, which can handle thousands of parallel calls, help cut recruiter time and cost per hire while improving completion rates among non-English-first candidates.
Bhashini Effect
“Recently, some e-commerce and tech startups projected workforce increases of 70–74%. The country’s diversity will make them adopt native-language AI tools to reduce drop-offs, widen access to tier-2/3 talent, and keep hiring funnels friction-light,” Mallick said.
Jobs marketplace startup Apna has taken a similar approach for sales and customer-facing roles, where regional language fluency is often essential. It introduced an internal AI Calling Agent in July to manage the first layer of screening end-to-end. Recruiters set questions, after which the system calls applicants, analyses responses and generates shortlists. The company says this has cut manual screening time by more than half while improving consistency.
Apna now offers the tool to client companies as well. “We have seen that the companies using the tool experience similar efficiency gains,” Kartik Narayan, CEO of Apna said, adding that nearly 30–40% of its sales hiring shortlists now originate from Hindi screenings.
As hiring volumes rise and competition for talent intensifies, startups are increasingly betting that native-language AI can help surface capable candidates who might otherwise be filtered out early.