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Multilingual Voice AI for Indian languages · 22+ Languages

One Voice AI Platform.
Every Language
Your Customers Speak.

India does not have one market. It has dozens, separated by language, dialect, and the trust that only comes from being spoken to in your mother tongue. Rootle's Multilingual Voice AI runs natively across Hindi, Tamil, Bengali, Malayalam, Gujarati, and 17 more Indian languages, from a single platform.

No accent bias
Dialect-aware ASR
Sub-500ms latency
Deploy in days
हिंदी Hindi 600M speakers
தமிழ் Tamil 80M speakers
বাংলা Bengali 100M speakers
ગુજરાતી Gujarati 60M speakers
മലയാളം Malayalam 38M speakers
తెలుగు Telugu
ಕನ್ನಡ Kannada
मराठी Marathi
+17 More
22+
Indian Languages Supported
95%+
Intent Accuracy Across Languages
3x
Higher Conversion in Native Language
<500ms
Response Latency Across All Languages
Language Hubs

Explore Rootle's Multilingual Voice AI
by Language

Each language hub covers dialect coverage, use cases, industry fit, and real deployment results for that specific market.

हिंदी
Hindi
Voice AI in Hindi
Hindi is the single largest language opportunity in Indian AI. With 600M+ speakers spread across UP, Bihar, Madhya Pradesh, Rajasthan, and the Hindi belt, no customer-facing AI deployment in India can afford to ignore it. Rootle's Hindi Voice AI handles Hinglish, regional accents, and mid-sentence code-switching natively.
BFSI D2C Logistics Real Estate Telecom
தமிழ்
Tamil
Voice AI in Tamil
Tamil's spoken-written diglossia, where colloquial kodum tamil and formal sentamil are substantially different, is the single biggest failure point for off-the-shelf multilingual models. Rootle is trained on colloquial Tamil across Chennai, Coimbatore, Madurai, and Tirunelveli speech regions, plus Tanglish code-switching.
Tourism NBFC Healthcare Real Estate D2C
বাংলা
Bengali
Voice AI in Bengali
With 100M+ Bengali speakers in India and West Bengal's fast-growing digital economy, the gap between AI capability and native-language customer experience is acute. Rootle handles Kolkata, Tripura, and Dhaka-origin dialect patterns, plus mixed Bengali-English input, all within a single Voice AI agent.
Automotive Banking Education Logistics
മലയാളം
Malayalam
Voice AI in Malayalam
Kerala has one of India's highest literacy rates and smartphone penetration, with a globally dispersed community that still thinks and decides in Malayalam. Rootle's Malayalam Voice AI covers Thiruvananthapuram, Kochi, Thrissur, Kozhikode, and Palakkad dialect variations, plus mixed Malayalam-English input.
Education Insurance Healthcare Banking
ગુજરાતી
Gujarati
Gujarati Voice AI
Gujarat contributes 18% of India's industrial output across diamonds, textiles, pharmaceuticals, and a 3M+ MSME base. Generic models fail here because they are trained only on Ahmedabad standard dialect, not Surat business speech, Saurashtra phonology, or Gujlish, the code-switching pattern that dominates urban Gujarat commerce.
MSME Lending Real Estate Pharma Textiles
తెలుగు · मराठी · ਪੰਜਾਬੀ
and more
More Language Hubs Coming
Telugu, Marathi, Kannada, Punjabi, Odia, Assamese and more are live on the platform today. Dedicated language hubs for each are in progress.
The Case for Native Language AI

Why Language Is Not a Feature.
It Is the Product.

English-first AI tools are not a neutral default in India. They are a market access barrier. Here is why multilingual Voice AI changes the commercial equation.

01
90% of India's Internet Users Prefer Native Language Content
India added its next 500 million internet users in regional languages, not English. These customers browse, buy, and escalate in their mother tongue. An AI that cannot meet them there does not serve them at all.
02
Language Determines Trust, Especially in High-Stakes Decisions
A customer discussing a loan, a medical appointment, or a property investment is not going to trust a system that cannot speak their language fluently. Native-language AI eliminates the friction that English-only support introduces at exactly the wrong moment.
03
Generic Multilingual Models Fail on Dialect, Not Just Script
Adding a language to a multilingual model is not the same as building for it. Surat Gujarati, Tirunelveli Tamil, and Murshidabad Bengali are not covered by models trained on standardised text corpora. Rootle is trained specifically on how each market actually speaks.
04
3x Conversion Uplift Is Consistent Across Every Language We Have Deployed
Whether it is real estate lead qualification in Gujarati, service reminders in Bengali, or tourism bookings in Tamil, native-language outreach consistently delivers three times the conversion of English-first flows to the same demographic.
05
Code-Switching Is the Norm, Not the Exception
Real Indian customers do not stay in one language. Hinglish, Tanglish, Gujlish, and Bengali-English switches happen mid-sentence. Rootle handles these patterns natively across every supported language so calls never stall at a language boundary.
06
One Platform, Any Language Combination, Zero Re-Integration
You do not need a separate AI vendor for each regional market. Rootle's unified platform lets you deploy Hindi in UP, Gujarati in Surat, and Tamil in Chennai from a single integration, one CRM connection, one dashboard.
Platform Architecture

How One Platform Serves
Every Indian Language

Rootle's multilingual stack is not a translation layer. Each language is a first-class citizen with its own ASR, NLU, and TTS training pipeline.

Dialect-Aware ASR Per Language
Each language has its own speech recognition model trained on colloquial spoken data, not transliterated text. Regional dialect variations are handled within the same model, not as edge cases requiring separate configuration.
Cross-Language LLM Reasoning
A single LLM reasoning layer handles intent detection, context retention, and business logic across all languages. The agent maintains full context even when a caller switches language mid-conversation, without losing the thread.
Prosody-Accurate TTS for Each Language
Text-to-speech for each language reproduces the phonemic and tonal patterns of that specific language, not a generic Indian English approximation. The caller hears a voice that sounds native, not translated.
One Integration, All Languages
Connect Rootle once to your CRM, telephony, and WhatsApp stack. Language routing is handled automatically based on caller language detection. No separate integrations, no parallel stacks, no per-language engineering overhead.
Industries

Every Industry That Sells to India
Needs Multilingual Voice AI

Rootle's multilingual Voice AI is deployed across sectors where the customer base is diverse, regional, and cannot be served in English alone.