Original research on how AI answer engines behave in Indian markets
Almost everything published about AI search visibility measures English prompts in Western markets. India asks differently. IndicGEO is our attempt to measure what actually happens here, and to publish enough of the working that anyone can check it.
How we work
Design fixed before data. Prompts are frozen and statistical tests chosen before collection starts. Anything we change afterwards goes into a public deviations log with the reason.
The engine's own noise is the baseline. AI engines never answer the same question the same way twice. We measure rerun-to-rerun variation first, and only report an effect when it exceeds that floor.
Verified against ourselves. Independent passes recompute the headline numbers from raw data without access to our analysis code. When they find defects in our instrument, and they have, we fix and re-run before publishing.
Everything published. Raw responses, prompts, lexicons, seeds, scripts and logs. We sell AI-visibility tracking, which gives us an interest in what these studies conclude. Publishing the whole corpus is how we make that interest checkable rather than something you have to trust.
In progress
Planned next waves, none of them collected yet: Devanagari Hindi against romanized Hinglish on the same prompts, to separate script from language; more categories beyond skincare and fashion; and longitudinal re-runs of the frozen prompt set to measure how much engines drift over months.
If you want to replicate, extend or disagree with any of this, the repository takes issues and pull requests. Reach us at team@depra.ai.