Language Translation

Real-time AI translation for Indian languages

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Overview

Language shouldn’t limit how far your business can go. Language Translation service helps you speak to your customers in their own language - literally. Powered by AI and trained for Indian diversity, it delivers real-time, accurate translations across 12+ regional languages. From e-commerce and banking to citizen services and entertainment, this solution ensures your content is culturally relevant, context-aware, and consistent with your brand. Whether it’s a chatbot response, a document, or an app UI - just plug it in and speak their language.

Pricing

To know more about the SKUs and pricing click below.

Core Features at a Glance 

Neural Machine Translation (NMT)
Utilizing deep learning models trained on real-world data, it produces natural, fluent output.
Indic languages
Translates between English and 12+ Indic languages, including Hindi, Tamil, Bengali, Marathi, etc.
Supports code-mixed text
Translates code-mixed text like "Kya aap login kar chuke ho?".
Domain-specific
Fine-tuned for e-commerce/banking/finance/legal/health for better contextual relevance.
Transliteration
Handles brand names and other proper nouns by transliterating them when there is no suitable translation.
Real-time translation
Perfect for live chat, content updates, or when multilingual customers require immediate assistance.
Batch mode
Translate millions of characters or documents at once - designed for scale.

What You Get

Still have questions?

We support English, 12+ Indian languages including Hindi, Marathi, Tamil, Telugu, Kannada, Bengali, Malayalam, Punjabi, and Assamese. More are being added regularly.
Yes. It’s tuned to understand and translate mixed-language and informal inputs often seen in chat, comments, or social content.
Yes. You can customize it with domain specific glossaries and examples - as good for banks, law firms, or healthcare content.
It’s integration-ready with APIs, SDKs, and connectors for CMS, apps, and internal tools.
With proper tuning, it can achieve 85 - 95% accuracy across most domains - and in many use cases, it is very close to human level performance.

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