AI Search & GEO — getting cited by ChatGPT, Perplexity, Gemini, and AIO
Eleven guides on Generative Engine Optimization (GEO) — how AI search systems pick sources, what differentiates a citable page from an ignored one, and the specific schema, content, and entity-linking moves that Indian SMEs should make in 2026.
Search is changing. Google's AI Overviews answer ~25% of queries inline without a click. ChatGPT, Perplexity, Gemini, and Bing Copilot return synthesised answers backed by 3–8 source citations rather than ten blue links. The companies that get cited in those answers earn the attention; the rest become invisible regardless of where they ranked on traditional SERPs. This is the reality GEO (Generative Engine Optimization) addresses.
This cluster of eleven guides covers the full GEO stack: what's actually different about how AI engines pick sources versus how Google ranks blue links, why structured data and llms.txt matter more than they did 18 months ago, what kind of content gets quoted (specific numbers + clear definitions + named entities, not generic advice), why brand entity recognition through Wikipedia/Wikidata sameAs is becoming the dominant authority signal, and how Indian SMEs can adapt without enterprise budgets.
Several posts in the cluster also examine the AI tooling landscape itself — what are the actually-useful AI tools for Indian small businesses, which ones have meaningful Indian-language support, what AI chatbots make sense for which use-cases, and where the "AI-first website builder" claims are real versus marketing.
The framing is practical, not speculative. Every claim in the cluster is verifiable against Google's published documentation, NPCI data on Indian search behaviour, or Redpulse Software's own implementation work for clients. For our broader perspective on building for the Indian market, see the India services pillar.
11 guides in this topic
Sorted by most recently updated.
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