In India, the emerging wave of artificial intelligence (AI) is becoming increasingly conversational. As companies seek to replace traditional call centers with intelligent voice agents, startups are navigating a uniquely complex landscape where scale, language, and latency intersect.
According to data from Tracxn, Indian voice AI startups raised $160.58 million across 37 funding rounds between 2019 and 2026. The funding peak occurred in 2023 with $41.6 million invested across five rounds, while 2026 has already seen $30.2 million across three rounds.
Bengaluru-based Gnani.ai, co-founded in 2016 by Ganesh Gopalan and Ananth Nagaraj, specializes in voice-first AI solutions. The company’s platform manages over 30 million spoken interactions daily across more than 12 languages, serving over 200 clients in sectors like banking, telecom, automotive, and various government entities. Notably, it is one of four ventures selected under a government initiative aimed at foundational AI development.
“Our agentic AI platform is designed to handle India-specific nuances like multilingual conversations and turn-taking,” Gopalan, the firm’s CEO, stated. “While it’s easy to deploy a basic voice AI agent today, the challenge lies in scaling the solution—ensuring low latency, high accuracy, and affordability for the Indian market. That’s where we excel.”
Gnani.ai recently introduced Inya VoiceOS, a voice-to-voice model that eliminates the need for intermediate speech-to-text (STT) and text-to-speech (TTS) components. The current model is built on 5 billion parameters, with a 14 billion-parameter upgrade anticipated shortly. The Vachana STT and TTS models offer human-like speech and minimal training voice cloning in 12 Indic languages.
To ensure data sovereignty, Gnani.ai processes all data through local data centers and maintains a large proprietary voice dataset. The company operates three layers: AI agents tailored to specific needs like banking collections and onboarding; an intermediate layer for partners to create their own agents; and a foundational AI layer with models such as STT and TTS available via APIs.
Gnani.ai has reported a 2–3 times annual growth in recurring revenue, adding around 120 customers in the past year alone, with expectations to double or triple this number in the coming year. The company is expanding to markets such as Japan, the US, and West Asia, while targeting 6-7 verticals by year-end. Recently, it secured $10 million in Series B funding, with plans for a Series C investment soon.
India boasts over 700 dialects, and most global AI models predominantly support English and Hindi. Navana.ai, a voice AI infrastructure company, is tackling this challenge by developing models from the ground up, gathering proprietary data nationwide to enable scalable voice agents.
“We build not just voice agents but also the models that enable them,” explained Raoul Nanavati, co-founder and CEO of Navana.ai. The company recently partnered with the Indian Institute of Science (IISc), Bangalore, to create RESPIN—one of the largest open-source speech datasets in India—capturing over 10,000 hours of audio across nine languages and 38 dialects.
Navana.ai offers voice agents for both inbound and outbound calls in 22 languages, with a pricing structure based on per-minute usage. It has raised $1.5 million and is concluding its Series A funding round.
“Voice-first culture is inherent to India. However, for the past decade, digital India has been constrained to text-based interactions. The gap lies in capacity and reliability; businesses can’t provide sufficient human agents for every conversation across numerous languages, especially during peak times. Voice AI addresses this shortfall,” stated Sneha Roy, co-founder and COO at Murf.AI, founded by alumni from IIT-Kharagpur.
Murf.AI confronts India’s linguistic diversity, addressing challenges with global voice models that struggle with code-switching. The company provides two primary models: Falcon, a real-time TTS engine supporting over 35 languages, and Speech Gen 2, designed for content creation with customizable tone and pacing.
“Our models use ethically sourced speech, with consented recordings ensuring voice actors earn royalties on their contributions,” Roy said. Murf.AI serves enterprise content teams through Murf Studio, a SaaS platform, and businesses via the Murf Voice API. Operating in over 195 countries, the company serves 10 million users.
Murf.AI has secured $11.5 million in two funding rounds, growing 13 times in four years, with an ARR of ₹85–90 crore. The number of paying customers increased by 500%, and the company is on track to double its revenue.
Himani Agrawal, COO of Microsoft India and South Asia, noted that, due to the sensitive nature of voice systems, organizations are increasingly favoring in-house AI systems rather than standalone tools. “As AI is integrated into mission-critical applications, governance and integration with existing frameworks become essential,” she said.
“India is inherently a voice-first society. Talking is more natural than typing or texting. In B2B, significant business occurs via phone—whether it’s in insurance, loans, or even FMCG distributors coordinating with retailers. Currently, much of this remains unscaled and manual, presenting considerable opportunities,” commented Vardhan Dharnidharka, Principal at Stellaris Venture Partners.
Published on April 13, 2026
