NEW DELHI, January 21, 2026
Voice AI in India: From Skepticism to $6.3 Million Seed Round
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A startup once dismissed by Y Combinator is now poised to capitalize on India’s booming demand for AI-powered voice solutions.
- Industry reports and the growth of voice model companies indicate a rising demand for voice AI in India.
- Bolna, a voice orchestration startup, overcame initial skepticism from Y Combinator to secure $6.3 million in seed funding.
- The company’s platform simplifies the creation of voice agents, even for users without deep technical expertise.
- Bolna is already handling over 200,000 calls daily and nearing $700,000 in annual recurring revenue.
India’s appetite for voice technology is undeniable, and businesses are eager to leverage artificial intelligence to improve customer service, sales, and even hiring processes. But turning that interest into revenue? That’s a different story. Just ask Maitreya Wagh and Prateek Sachan, the founders of Bolna, a voice orchestration startup that faced repeated rejection from Y Combinator.
From Rejection to Revenue
“When we were applying for Y Combinator, the feedback we got was, ‘great to see that you have a product that can create realistic voice agents, but Indian enterprises are not going to pay, and you are not going to make money out of this,’” Wagh recalled. The startup applied five times before finally being accepted into the fall 2025 batch. The turning point? Demonstrating over $25,000 in monthly revenue, fueled by $100 pilot programs that have since increased to $500.
That momentum continued on Tuesday, when Bolna announced a $6.3 million seed round led by General Catalyst, with participation from Y Combinator, Blume Ventures, Orange Collective, Pioneer Fund, Transpose Capital, and Eight Capital. Individual investors Aarthi Ramamurthy, Arpan Sheth, Sriwatsan Krishnan, Ravi Iyer, and Taro Fukuyama also contributed to the round.
Building an Orchestration Layer for India
Bolna is developing a platform that connects and manages various AI voice technologies—an orchestration layer—similar to startups like Vapi, LiveKit, and VoiceRun. However, Bolna is specifically tailored to the nuances of the Indian market, addressing challenges like noise cancellation, caller ID verification through Truecaller, and handling multilingual conversations.
The platform also incorporates features tailored to Indian users, such as consistently speaking numbers in English regardless of the primary language and enabling keypad input for longer text entries.
What makes Bolna different? The company emphasizes ease of use, allowing users to build voice agents simply by describing them, even without extensive technical knowledge. Currently, 75% of Bolna’s revenue comes from self-service customers.
Wagh explained that Bolna’s orchestration layer provides flexibility, allowing enterprises to easily switch between AI models as technology evolves. “Our platform allows customers to switch models easily or even use different models for different locales to get the best out of them. An orchestration layer is necessary for enterprises to ensure they are getting the best models because one model can be better today and another one can be better tomorrow,” he said.
A Growing Client Base
Bolna’s clients include car reselling platform Spinny, on-demand house-help startup Snabbit, beverage companies, and dating apps—primarily small to midsize businesses utilizing the self-serve platform. The company is also actively pursuing larger enterprise deals, supported by a team of nine forward-deployed engineers who work directly with clients.
Bolna is experiencing consistent growth, currently handling over 200,000 calls per day and approaching $700,000 in annual recurring revenue. While 60% to 70% of call volume is in English or Hindi, usage of other regional languages is steadily increasing.
Akarsh Shrivastava, from General Catalyst, highlighted Bolna’s flexibility as a key investment factor. “Bolna allows you the freedom to choose any model and has a stack behind it to mold it according to your requirement. It’s a good option for people who want to own some part of the stack, want flexibility in model picking, and want to be able to maintain those products themselves,” Shrivastava said.
