Indians do not search in one language. The same person asks one question in English and the next in Hindi or a mix of both, often in the same sentence. AI assistants answer in kind, and here is the catch: the brands they cite can change completely depending on the language of the question. A brand that shows up clearly in English answers can be missing from Hindi ones, and the other way round.
Real questions rarely look like clean English search terms. They look like "best budget smartphone under 20000", "kaunsa face wash oily skin ke liye accha hai", or a Hinglish blend that switches mid sentence. People ask the way they speak. If you only ever test your brand in tidy English prompts, you are checking a fraction of how your customers really search.
When the language changes, the sources the engine draws on change too. English answers tend to pull from English pages, global publications and large international platforms. Hindi and Hinglish answers lean more on content written for Indian audiences, regional discussion, and creators who publish in those languages. Different inputs produce different shortlists. So the brand that has built up English coverage can lose its lead the moment the question switches to Hindi.
Imagine a skincare brand, Brand A, that is regularly named when you ask an English question like "best vitamin C serum in India". Ask the same thing in Hinglish and the answer may instead feature a different set of names, perhaps Brand B and a couple of creators who reviewed products in Hindi on YouTube. Same category, same intent, different language, different winners. The brands here are illustrative, not real.
Most AI visibility tools were built for English first, global markets. They check English prompts against English sources, which is fine for a brand in New York and blind for a brand in India. The Hindi and Hinglish half of the picture, where a large share of real buying questions live, simply does not get measured.
The fix is not complicated, it is just work: test your brand in both English and Hindi or Hinglish, for the questions your customers actually ask, and do it more than once because the answers vary. Our guide on how to check if ChatGPT, Gemini and Perplexity cite your brand in India walks through the manual version, and the same rule about different engines citing different sources applies within each language as well.
This bilingual gap is exactly why we built Citedar for Indian brands: it asks your category's questions in both English and Hindi, across ChatGPT, Gemini and Perplexity, and shows where you stand in each. To see your own brand's picture in both languages, get a free audit.
A free audit across ChatGPT, Gemini and Perplexity, built for Indian brands.
Get my free audit