Sarvam AI is an Indian AI company building language models, text-to-speech, and speech-to-text specifically for Indian languages — Hindi, Tamil, Telugu, Kannada, Bengali, Marathi, Gujarati, Odia, Malayalam, and Punjabi. Where global AI tools struggle with Indian language nuance, accents, and code-switching, Sarvam is purpose-built for them.
Sarvam AI builds AI for Indian languages. Founded in 2023 by Pratyush Kumar and Vivek Raghavan (former researchers at IIT Madras and Microsoft Research India), the company's mission is to make AI work as well in Indian languages as it does in English. The practical problem they solve: most global AI models were trained primarily on English-language data. When they encounter Hindi, Tamil, Telugu, or other Indian languages — especially in spoken form with regional accents and code-switching (mixing English and Hindi in the same sentence) — quality degrades significantly.
Sarvam's models are trained specifically on Indian language data, making them significantly more accurate than global models for Indian language speech recognition and text-to-speech that actually sounds natural to Indian ears.
Why this matters in practice: A voice AI built for a clinic in Chennai or a call centre in Mumbai will serve callers far better using Sarvam's Indian-language TTS than using a US-trained TTS model attempting Tamil or Telugu. The difference in user experience is substantial — patients who call and hear natural-sounding Tamil are more comfortable and more likely to engage.
Hindi, Tamil, Telugu, Kannada, Malayalam, Bengali, Marathi, Gujarati, Odia, and Punjabi — all official Indian languages with substantial speaker populations. Sarvam continues to expand language support based on demand and data availability.
Use Sarvam when: your users primarily speak an Indian language, you need TTS that sounds natural to Indian ears, you are building voice agents for Indian audiences (customer service, healthcare, education), or you need high-accuracy STT for Indian-accented speech. Use global tools (ElevenLabs, Whisper, OpenAI TTS) when: English is the primary language, you need the widest range of voice styles, or you need capabilities beyond Indian language coverage.
For many Indian-market products, the right approach is to use Sarvam for Indian language handling and a global tool like Whisper or ElevenLabs for English interactions — routing based on the detected language.
Sarvam AI was founded by Pratyush Kumar (previously IIT Madras, Microsoft Research India) and Vivek Raghavan (previously AI4Bharat, EkStep Foundation) — researchers with deep backgrounds in Indian language NLP. The company's work builds on the AI4Bharat initiative, which created open-source datasets and models for Indian languages and is considered the foundational research base for Indian language AI.
The Sarvam-2B language model (released 2024) is a 2-billion parameter model trained on Indian language data and fine-tuned for instruction-following in Indian languages. At 2B parameters, it is designed for on-device inference and low-latency applications — a different design point from the large cloud-based models (GPT-4, Claude) which prioritise quality over speed and size.
AI4Bharat is an open-source project (funded by the Indian government's National Language Translation Mission among others) that created: IndicTrans2 (translation model for all 22 scheduled Indian languages), IndicWav2Vec (speech model), and large Indian language datasets. Sarvam's founders were key contributors to AI4Bharat before founding Sarvam. This means Sarvam's commercial products are built on a deep foundation of publicly funded Indian language AI research.
Code-switching (switching between languages in the same sentence — "Mujhe kal 3 baje ka appointment book karna hai" mixing Hindi and English) is extremely common in Indian speech and text. Standard STT and TTS models handle it poorly because they are trained on monolingual data. Sarvam's models are specifically trained on code-switched Indian language data, which is the primary technical differentiation from global models attempting Indian language support.
Sarvam has disclosed deployments in: government service delivery (state government chatbots and helplines), healthcare (patient-facing voice interfaces at Indian hospitals), education (vernacular language learning applications), and financial services (vernacular customer onboarding for digital banking). The company has received funding from Lightspeed India and Peak XV Partners (formerly Sequoia Capital India).
Source note: Company and technical information from sarvam.ai, AI4Bharat public documentation, and Sarvam AI press releases. Funding from public announcements. Pricing indicative from sarvam.ai/pricing — verify directly as Indian market pricing evolves rapidly. All verified April 2026.