Industry reports and the growth of voice model companies in the Indian market suggest a growing demand for voice AI solutions in the country. Voice is a popular medium for communication among people and businesses in India. That is why enterprises and startups are eager to use voice AI to be more efficient at customer support, sales, customer acquisition, hiring, and training.
But recognizing market demand is one thing, while proving businesses will pay is another. Y Combinator rejected the application from Bolna, a voice orchestration startup built by Maitreya Wagh and Prateek Sachan, five times before finally accepting it into the fall 2025 batch. They were skeptical that the founders could turn interest into revenue.
When applying for Y Combinator, the feedback received was that while it was great to have a product that could create realistic voice agents, Indian enterprises were not going to pay and the founders would not make money. The startup applied with the same idea for the fall batch but was then able to show it had revenue of more than $25,000 coming in every month for the last few months. At that time, the company was running $100 pilots to help users build voice agents. Now the startup prices those pilots at $500.
The momentum has continued. The startup said that it has raised 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. The round also includes individual investors.
Bolna is building an orchestration layer, essentially a platform that connects and manages different AI voice technologies, to suit the idiosyncrasies of interactions in India. This includes noise cancellation, getting verification on the caller ID platform Truecaller, and handling mixed languages.
Feature-wise, the company has built specific nuances for Indian users, such as speaking numbers in English regardless of the core language, or allowing for keypad input for longer inputs.
The key differentiation of Bolna is that it makes it easy for users to build voice agents by just describing them, even without deep knowledge of the underlying technology, and start using them for calls. The company said that 75% of its revenue comes from self-serve customers.
Because Bolna is an orchestration layer, it does not depend on a single model, so enterprises can easily switch when a better model becomes available. The platform allows customers to switch models easily or use different models for different locales to get the best performance. An orchestration layer is necessary for enterprises to ensure they are getting the best models, as one model can be better today and another better tomorrow.
The company has a range of clients, including car reselling platform Spinny, on-demand house-help startup Snabbit, beverage companies, and dating apps. Most of these are small to midsize businesses that use Bolna’s self-serve platform.
Separately, Bolna is pursuing large enterprise deals. For these large enterprises and custom implementations, Bolna has a team of forward-deployed engineers who work directly with clients. The startup has signed two large enterprises as paying customers and has four more in the pilot stage. Currently, Bolna employs nine forward-deployed engineers and is adding two to three people to that team every month to support this enterprise push.
Bolna has seen steady growth in both call volumes and revenue. It is now handling over 200,000 calls per day and is on the verge of crossing $700,000 in annual recurring revenue. While 60% to 70% of call volume is in English or Hindi, other regional languages are steadily rising.
Akarsh Shrivastava, part of the investment team at General Catalyst, said the firm found Bolna impressive because its orchestration layer is flexible for various kinds of customers. Bolna allows the freedom to choose any model and has a stack behind it to mold it according to requirements. It is 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.