Editorial illustration for IndQA Launches AI Platform to Serve India's Billion Non-English Speakers
IndQA Brings AI to Billion Non-English Users in India
IndQA Targets India's Billion Non-English Users, 2nd-Largest ChatGPT Market
OpenAI’s latest benchmark reads like a memo to its own engineering team: we are missing India. It’s a tacit admission that their models, trained on a global corpus, fail in specific, local ways. The response is a sprawling new test called IndQA, built to probe AI on the stuff of Indian daily life.
It’s a recognition of pure market force. India is ChatGPT’s second biggest user base, but English is a minority language there. About a billion people operate primarily in one of the country's 22 official tongues.
Current AI benchmarks are lousy at measuring this gap. They test general knowledge or math, not whether a model understands a local festival, a regional dish, or the legal nuance of a state law.
India has about a billion people who don't use English as their primary language, 22 official languages (including at least seven with over 50 million speakers), and is ChatGPT's second largest market. This work is part of our ongoing commitment to improve our products and tools for Indian users, and to make our technology more accessible throughout the country. IndQA evaluates knowledge and reasoning about Indian culture and everyday life in Indian languages.
It spans 2,278 questions across 12 languages and 10 cultural domains, created in partnership with 261 domain experts from across India. Unlike existing benchmarks like MMMLU and MGSM, it is designed to probe culturally nuanced, reasoning-heavy tasks that existing evaluations struggle to capture. IndQA covers a broad range of culturally relevant topics, such as Architecture & Design, Arts & Culture, Everyday Life, Food & Cuisine, History, Law & Ethics, Literature & Linguistics, Media & Entertainment, Religion & Spirituality, and Sports & Recreation--with items written natively in Bengali, English, Hindi, Hinglish, Kannada, Marathi, Odia, Telugu, Gujarati, Malayalam, Punjabi, and Tamil.
Note: We specifically added Hinglish given the prevalence of code-switching in conversations. Each datapoint includes a culturally grounded prompt in an Indian language, an English translation for auditability, rubric criteria for grading, and an ideal answer that reflects expert expectations.
This is not translation. It’s contextualization. The benchmark includes Hinglish, the fluid mix of Hindi and English common in conversation, because real speech is messy. It grades models on their grasp of history, law, food, and sport from a specifically Indian viewpoint.
The scale of the task is its own argument. Twelve languages. Over two thousand questions.
Ten domains of culture. This is the paperwork of ambition. OpenAI is methodically mapping the terrain it needs to conquer.
For local startups, this benchmark is a double-edged sword. It validates the problem they’re solving while also raising the bar. If OpenAI starts building for Bengaluru and Mumbai with the same focus it built for San Francisco, the competitive landscape tightens.
The real test is whether a large, generalized model can ever be as good at the nuances of Punjab as a smaller, native one. IndQA will give us the score, but the market will decide the winner.
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Common Questions Answered
How many languages does IndQA's AI platform currently support?
IndQA's platform currently spans 12 languages, targeting the linguistic diversity of India's non-English speaking population. This approach allows the AI to evaluate knowledge and reasoning across multiple Indian languages, making technology more accessible to billions of users.
Why is IndQA's approach significant for technology access in India?
India has approximately a billion people who do not use English as their primary language, with 22 official languages and at least seven languages with over 50 million speakers. IndQA's platform goes beyond simple translation, creating a nuanced technological interface that evaluates cultural knowledge and reasoning in native languages.
What makes IndQA different from global AI platforms?
Unlike global AI giants that have focused on English-first experiences, IndQA specifically targets the linguistic barriers that have traditionally excluded non-English speakers from advanced technology. The startup is developing an AI platform that understands and responds in multiple Indian languages, addressing the unique communication needs of India's diverse population.
Further Reading
- Introducing IndQA — OpenAI
- Can Homegrown Indic Language AI Models Scale in 2025? — Techquity India
- Google AI Mode Rolls Out In 7 New Indian Languages — NDTV
- India Indigenous AI Model: Rise of Homegrown LLMs in 2025 — TechMitra
- India's internet users to exceed 900 mn in 2025, driven by Indic languages — Business Standard
