ElevenLabs targets all 22 Indian languages on its voice AI platform

ElevenLabs plans to expand its voice AI platform to all 22 officially recognised Indian languages, marking a major escalation of the company’s India strategy as demand for multilingual artificial intelligence grows. The company currently supports 14 Indian languages on its latest Eleven v4 text-to-speech model, and co-founder and CEO Mati Staniszewski said the remaining languages are expected to be added in the coming months.

The expansion comes as India becomes one of ElevenLabs’ most important markets outside the United States. Staniszewski said India is the company’s biggest market outside the US, while separate company and industry disclosures show rapidly increasing enterprise adoption of its voice technology. ElevenLabs is also planning to invest hundreds of millions of dollars in India, building local teams, developing India-focused models and expanding support for Indian languages.

Key takeaways

• ElevenLabs plans to support all 22 officially recognised Indian languages.
• Its latest Eleven v4 model currently supports 14 Indian languages, according to CEO Mati Staniszewski.
• Eleven v4 supports more than 90 languages globally.
• India has become ElevenLabs’ largest market outside the US, according to Staniszewski.
• The company plans to invest hundreds of millions of dollars in India, although it has not disclosed an exact figure.
• ElevenLabs is expanding local go-to-market, engineering, research and forward-deployed engineering teams.
• Enterprise customers already account for 55% of ElevenLabs’ revenue, according to reporting from the company’s India push.
• Indian companies including Meesho, IDFC Bank, TVS Motor and Cars24 are using ElevenLabs technology across customer support and other workflows.
• The company is positioning India not only as a market but also as a testing ground for voice AI applications that could eventually be exported globally.

Why ElevenLabs Is Targeting All 22 Languages

India’s language diversity makes the country both one of the hardest markets for voice AI and one of its largest potential opportunities.

The Indian government recognises 22 scheduled languages, ranging from Hindi and Bengali to Tamil, Telugu, Marathi, Gujarati, Kannada, Malayalam, Punjabi and Urdu.

For a voice AI company, supporting these languages is more complicated than simply translating written text.

A useful voice system has to understand pronunciation, accents, rhythm, regional variations and code-switching. In India, users can also move between English and an Indian language within the same sentence.

For example, a customer might explain a problem in Hindi while using English terms for a product, transaction or technical process.

A voice agent that translates everything into formal Hindi may technically understand the words but still sound unnatural to the person using it.

That is why ElevenLabs is emphasizing models designed around Indian speech patterns and real-world conversations rather than treating Indian languages as an afterthought.

The company says its India-focused technology is designed to handle Indian accents, Hinglish and regional speech patterns, as well as noisy call environments.

ElevenLabs Currently Supports 14 Indian Languages

At its Bengaluru Summit on October 6, Staniszewski said ElevenLabs currently supports 14 Indian languages on Eleven v4.

The company wants to extend that coverage to all 22 scheduled languages in the coming months.

The distinction between the company’s overall language coverage and India-specific coverage is important.

Eleven v4 supports more than 90 languages globally. ElevenLabs’ official documentation lists Indian languages including Hindi, Bengali, Gujarati, Kannada, Malayalam, Marathi, Odia, Punjabi, Sindhi, Tamil, Telugu and Urdu among its supported languages.

The 22-language target is therefore not about increasing the global language count from 14 to 22. It is about ensuring comprehensive coverage of India’s officially recognised language ecosystem.

That is a much more ambitious local-market objective.

Eleven v4 Gives ElevenLabs a Stronger Voice Platform

The India language expansion comes just days after ElevenLabs launched Eleven v4.

The new model was introduced on September 28 as the company’s latest high-quality text-to-speech system, alongside Eleven v4 Turbo for real-time applications.

ElevenLabs says v4 is designed to interpret emotion, context, pacing and delivery rather than simply converting written words into speech.

The model can respond to instructions describing how a sentence should sound and supports audio directions such as laughter, whispers and other sound effects.

It also improves multi-speaker dialogue and voice consistency.

Eleven v4 supports more than 90 languages, while v4 Turbo is designed for real-time voice agents with median inference latency of around 100 milliseconds and time to first speech of about 150 milliseconds.

Those capabilities are particularly relevant to customer-service applications.

A customer does not want to wait several seconds after every sentence when speaking to an automated support agent. Nor does a business want an AI representative that sounds robotic or fails to preserve context during a conversation.

From Text-to-Speech to AI Agents

The India push is also broader than ElevenLabs simply adding more languages to a voice generator.

The company is increasingly positioning itself as an infrastructure provider for AI agents.

That means businesses can use ElevenLabs technology to create systems that answer calls, handle customer-service conversations, assist with sales, provide information and perform other tasks.

This changes the competitive landscape.

A company building an AI voice agent does not necessarily want to develop speech synthesis, voice cloning, real-time audio processing and conversation infrastructure independently.

Instead, it can use a specialized provider and concentrate on its own business workflow.

ElevenLabs is attempting to become that infrastructure layer.

Its India website highlights applications in financial services, e-commerce, telecom and healthcare, including customer support, payment reminders, order tracking, appointment scheduling and other workflows.

India Is Already a Major Revenue Market

The language expansion is being supported by strong commercial traction.

In February, Staniszewski described India as ElevenLabs’ second-largest market after the US. At that time, the company said it was targeting $100 million in annual recurring revenue from India and planned to open a Bengaluru office and hire around 100 people.

The company has since expanded significantly.

A report published on October 6 said ElevenLabs’ revenue had reached a $600 million annual run rate and that India had become its second-largest market, behind the US. The same report said enterprise customers account for 55% of revenue.

These figures illustrate why language support is strategically important.

If Indian enterprises are already paying for voice AI, expanding from 14 languages toward all 22 gives ElevenLabs more opportunities to sell the technology to companies whose customers speak languages currently outside its strongest coverage.

Enterprise Adoption Is Moving Beyond Experiments

One of the most important changes in India’s voice AI market is that companies are moving from experimentation toward production deployments.

In February, Staniszewski said ElevenLabs was already handling around 60,000 support calls for one customer across English, Hindi and other Indian languages.

He also said the technology was handling nearly 50,000 outbound calls each month for IDFC Bank.

Those numbers are significant because they show voice AI being used at operational scale rather than simply being demonstrated in pilot projects.

ElevenLabs’ India customer examples now include Meesho, Kuku FM, Pocket FM, Cars24 and TVS Motor, according to the company’s India materials.

For companies handling millions of customer interactions, the economic case for voice AI can be straightforward.

A voice agent can operate around the clock, handle large numbers of simultaneous conversations and route complicated cases to human employees.

The technology can therefore become part of a company’s operating infrastructure rather than simply a customer-facing novelty.

Meesho Shows Why Indian Scale Matters

E-commerce is one of the clearest areas where Indian scale can accelerate voice AI adoption.

ElevenLabs says Meesho uses voice agents for multilingual customer support. The company’s India materials highlight real-time multilingual support as one of its major enterprise applications.

Earlier, Staniszewski said Meesho was handling around 60,000 calls a day across Hindi and other Indian languages.

The underlying opportunity is much larger than the number of calls.

India has hundreds of millions of internet users, but not every customer is equally comfortable navigating complex apps, typing long messages or communicating in English.

Voice can lower that barrier.

A customer who struggles with a written support form may be able to explain a delivery problem naturally over the phone.

That makes multilingual voice AI particularly relevant to companies serving customers outside India’s largest urban centres.

India Could Become a Testing Ground for Voice AI

Staniszewski has described India as more than just another market.

The country’s scale and linguistic diversity make it a useful environment for testing voice AI under difficult conditions.

An AI system that can operate across multiple Indian languages, accents, code-switching patterns and noisy telephone environments has to solve problems that are less visible in more linguistically uniform markets.

That creates a potential feedback loop.

Indian customers generate large volumes of real-world interactions. Those interactions can expose weaknesses in speech recognition, pronunciation, conversational flow and agent reliability.

Companies can then improve the technology for Indian use cases.

Once those capabilities work at scale, some of the underlying technology can potentially be applied to other multilingual markets.

In that sense, India could serve as both a major customer market and an AI development laboratory.

ElevenLabs Plans Hundreds of Millions of Dollars in India

The language expansion is backed by a much larger investment programme.

Reuters reported on October 6 that ElevenLabs plans to invest hundreds of millions of dollars in India. The company has not disclosed the exact amount.

The investment is expected to support local teams, AI model development and expanded language capabilities. ElevenLabs is also open to potential mergers and acquisitions in India, although it has not identified specific targets.

That is a significant change from treating India primarily as a sales market.

The company is building local capabilities across go-to-market, engineering, research and forward-deployed engineering.

Forward-deployed engineering is particularly important for enterprise AI.

Large businesses often need help integrating an AI agent with their existing customer relationship management systems, telephony infrastructure, databases and internal workflows.

A local engineering team can make those deployments faster and easier to maintain.

Funding Gives ElevenLabs Room to Expand

ElevenLabs’ global expansion is also supported by substantial funding.

The company said in May that it had surpassed $500 million in annual recurring revenue during the first four months of 2026, after ending 2025 at $350 million ARR.

It raised additional capital from investors including BlackRock, Wellington, D.E. Shaw, Schroders and NVIDIA’s investment arm, among others.

The company’s expanding revenue base gives it greater room to invest in research, infrastructure and local markets.

India is particularly attractive because the company is already seeing enterprise adoption rather than having to create demand from scratch.

The strategic question is whether ElevenLabs can maintain its technological advantage as competitors become more aggressive.

Competition Is Intensifying

ElevenLabs is not entering an empty market.

Indian AI companies such as Sarvam AI are developing speech and language models specifically for the country’s linguistic environment.

Global technology companies including Google and OpenAI are also improving multilingual speech capabilities.

Staniszewski acknowledged the quality of Indian competitors, including Sarvam, while arguing that ElevenLabs’ advantage is not just its underlying model but the broader product and enterprise infrastructure around it.

That distinction is important.

The competition may ultimately be determined by more than voice quality.

Businesses need reliability, low latency, security, compliance, integration tools, analytics, escalation mechanisms and the ability to deploy agents at scale.

A model that sounds excellent but cannot reliably complete a customer-service workflow may be less valuable than an integrated platform that can.

The India Opportunity Goes Beyond Customer Support

Customer service is likely to remain one of the largest use cases, but the potential applications are broader.

Banking and financial services

Banks can use voice agents for payment reminders, account-related questions, card servicing and other routine interactions.

India’s large customer base and multilingual population make this particularly relevant.

E-commerce

Voice agents can assist with order tracking, returns, refunds and product discovery.

Healthcare

Potential applications include appointment scheduling, patient intake, reminders and follow-up communication.

Telecom

Telecom companies can automate service requests, outage notifications and common customer questions.

Education and media

Voice technology can also be used for language learning, audiobooks, entertainment, dubbing and localized content.

This diversification matters because it reduces dependence on one specific enterprise use case.

Voice AI Could Become an Interface Layer

The larger strategic bet behind ElevenLabs is that voice will become a mainstream interface for interacting with AI systems.

Today’s AI boom has largely been built around text.

People type questions into chatbots, receive written answers and use software interfaces to complete tasks.

Voice changes that interaction.

A user can speak naturally while driving, working or using a service that is difficult to navigate through a screen.

For India, the opportunity may be even larger because language can be a barrier to digital participation.

If AI systems can communicate naturally in a user’s preferred language, the interface itself becomes less intimidating.

That could expand the number of people who can interact with digital services.

The Bigger Picture

ElevenLabs’ plan to reach all 22 Indian languages is ultimately a bet on voice becoming a major interface for India’s next wave of digital adoption. The company is moving beyond text-to-speech toward full conversational infrastructure, while its growing enterprise customer base gives it an immediate commercial reason to invest in local language quality.

The competitive challenge will be substantial. Indian companies such as Sarvam AI have a strong local-language focus, while global AI companies are rapidly improving multilingual speech. ElevenLabs therefore needs to prove that its combination of voice quality, latency, agent infrastructure, enterprise integration and local support can justify its position as Indian businesses move from AI experiments to large-scale deployments.

Looking Ahead

The next milestone will be ElevenLabs’ rollout of the remaining Indian languages and the expansion of its local engineering and research operations. The company will also have to demonstrate that its language coverage works effectively in real conversations, including regional accents, code-switching and noisy telephone environments, rather than simply meeting a language-support checklist.

If ElevenLabs succeeds, India could become one of the company’s most important product-development markets as well as one of its largest revenue markets. The ability to build voice agents that work naturally across India’s linguistic diversity could also give the company technology and deployment experience that can be reused in other multilingual markets around the world.