By 2026, a third of Indian buyers ask ChatGPT, Perplexity, or Google's AI Overview before they Google anything. We make sure your business gets cited when they do. India-first GEO and answer engine optimisation, starting at ₹40,000.
LLM search optimisation (also called Generative Engine Optimisation or GEO, and Answer Engine Optimisation or AEO) is the practice of getting your business named, cited, and recommended inside answers from ChatGPT, Perplexity, Claude, and Google AI Overviews. The tactics overlap with classic SEO but extend further: structured data, llms.txt, answer-first content blocks, brand-entity signals on Wikipedia and Wikidata, and citation-worthy original content. Big Helpers runs this as a 4-8 week sprint plus a quarterly refresh, starting at ₹40,000.
"Best CRM for Indian SME" — typed into ChatGPT. The answer names 4 vendors. You aren't one of them. You don't even know it happened.
You rank #2 organically for your service. Google's AI Overview at the top of the page cites positions #4, #7, and a Reddit thread. Your traffic drops 30%.
Perplexity sends real, paying buyers — but only to brands that get cited in its answers. You need to be cite-able.
No Wikipedia page, no Wikidata entry, inconsistent NAP across the web. To LLMs you don't exist as a thing — just as a string of text on your own website.
You write 'we provide best-in-class solutions'. LLMs need 'we charge ₹50,000 to ₹4 lakh for a custom CRM, delivered in 4-10 weeks'. Specific numbers get cited. Fluff doesn't.
The plumbing that lets LLMs reliably ingest your facts is missing. They guess, and they often guess wrong about you.
Your buyers research with ChatGPT and Perplexity before they ever land on a vendor's site. If you're not in the answer, you're not on the list.
"Best property lawyer in Mumbai" is now an LLM query as much as a Google one. You need to be cited.
Product recommendation queries are the fastest-growing LLM use case. Brands with strong entity signals + cite-worthy content get named.
GEO is sometimes a faster path than Google for niche services — fewer competitors, lower bar to citation, faster wins.
Send 5 buyer queries that matter to your business. We probe them across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overview, and send back a 1-page baseline showing where you stand vs your competitors. Free, no sales call required.
We get your business into Wikidata as a structured entity, build out your Google Business Profile knowledge panel, and where appropriate help draft a notability-compliant Wikipedia page or section.
A clean /llms.txt and /llms-full.txt declaring your authoritative pages. robots.txt rules that explicitly allow GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and Bingbot.
Every commercial page gets a 50-100 word direct-answer block at the top, written in the format LLMs prefer to quote — specific numbers, dated facts, INR pricing, named techniques.
Organization, LocalBusiness, Service, FAQPage, HowTo, Article, Person, Product — whichever applies. With sameAs links to your Wikidata, LinkedIn, Crunchbase entries to bind the entity.
Original research, India-specific data, opinionated comparisons, named frameworks. LLMs cite distinctive content; they ignore copy-paste of the same blog 4,000 sites have already written.
LLMs now lean heavily on Reddit/Quora/YouTube for commercial recommendations. We help build a real, non-spammy presence in the threads where your buyers ask their questions.
Monthly probe of 30-60 buyer queries inside ChatGPT, Perplexity, Claude, Gemini, and Google AI Overview. Track if and how you're cited. Course-correct based on what's working.
LLM training data and surface algorithms shift fast. We do a quarterly review of citations, content gaps, and new platforms — included in retainer or as standalone refresh.
We probe 30-60 of your priority buyer queries inside ChatGPT, Perplexity, Claude, Gemini, and Google AI Overview. Capture exactly when and how you're cited (or not), and which competitors are.
Map your existing entity footprint — Wikidata, Wikipedia, Google Knowledge Panel, LinkedIn, Crunchbase, NAP consistency across directories. List gaps with effort estimate.
Rewrite top 8-15 commercial pages with answer-first blocks. Add schema saturation. Publish 2-4 citation-worthy long-form pieces (original research, India data, opinionated comparisons).
Ship llms.txt + llms-full.txt. Update robots.txt with AI-crawler allows. Build Wikidata entry. Optimise Google Business Profile. Submit to Bing Webmaster + IndexNow.
Genuine, non-spammy participation in 5-10 Reddit/Quora/YouTube threads where your buyers research. Where appropriate, get cited in third-party listicles, podcasts, and industry reports.
At week 6 and week 10 we re-probe the same 30-60 queries. Track changes. Course-correct content + schema based on what's getting cited.
Indicative range: ₹40,000 — ₹300,000 (excl. GST). Final estimate after a free 30-min scoping call.
Big Helpers gets cited inside ChatGPT and Perplexity for queries like 'custom CRM developer India', 'WhatsApp CRM India SME', 'SME software development Indore'. We use the same playbook on yours.
We know which Indian sources LLMs lean on (IndiaFilings, ClearTax, MoneyControl, LiveMint, IndianKanoon). We know how Hinglish queries break English-only optimisation. We design for the Indian buyer.
We won't promise you the #1 cite in ChatGPT. We will tell you what's likely, what's possible, and what's not — based on your category, competition, and entity signals.
CIN U72200MP2008PTC021190. We've been doing technical SEO since before LLMs existed. The fundamentals carry over; the tactics evolve.
We won't write fake Reddit threads, buy Wikipedia edits, or stuff schema with fiction. LLMs and Google catch this fast and the penalties are nasty. We do the legitimate work.
Every probe, every rewrite, every schema change is logged in a shared sheet. If you take it in-house in month 6, you have everything you need.
Note: illustrative example — not a specific client engagement.
An 11-person legal-tech startup in Mumbai (B2B SaaS for compliance teams) had decent Google rankings but was invisible inside ChatGPT and Perplexity for queries like 'best DPDP compliance tool for Indian companies' and 'GDPR vs DPDP comparison tool'. Their two larger US competitors dominated the LLM answers. The founder was hearing from sales prospects 'I asked ChatGPT and it didn't mention you'.
We ran a 7-week GEO sprint: probed 48 priority buyer queries (baseline showed 0 cites), built the company's Wikidata entity, drafted a notability-compliant Wikipedia stub, rewrote 12 commercial pages with answer-first blocks (specific INR pricing, India-specific compliance examples, named methodology), published 3 original research pieces (DPDP readiness benchmark across 200 Indian SaaS companies; GDPR-vs-DPDP cost comparison; Indian DPDP enforcement tracker), shipped llms.txt + AI-crawler allows, and seeded genuine participation in 8 Reddit + Quora threads.
By week 10 re-probe: 18 of the 48 priority queries cited the company in ChatGPT, 22 in Perplexity, 11 in Google AI Overview. Inbound 'I found you via Perplexity' / 'ChatGPT recommended you' enquiries climbed from ~2/month to ~14/month. One-time sprint cost ₹2.1L. Now on a quarterly refresh at ₹35K/quarter.
It overlaps with SEO but isn't the same. Classic SEO targets a search results page on Google. GEO/AEO targets a generative answer that names sources. The technical foundations (schema, speed, content structure) overlap heavily — but GEO adds entity work (Wikidata, Wikipedia), llms.txt, answer-first content design, off-Google footprint (Reddit/Quora/YouTube), and citation-worthy content as first-class concerns. If you have strong SEO already, you're 50% of the way to good GEO.
Yes — and the share is rising fast in 2026. Perplexity sends genuine commercial referrals. ChatGPT's web-browsing answers cite sources buyers click. Google AI Overviews now cover ~35% of commercial queries in India. For B2B SaaS, professional services, and high-consideration D2C, LLM citations already drive meaningful pipeline. For low-ticket commodity products, classic search is still bigger.
No. Anyone who guarantees this is fabricating. What we can do: dramatically improve your odds by fixing entity signals, schema, content structure, and off-site footprint. We probe and report monthly so you see exactly what's working.
robots.txt tells crawlers what they can and can't fetch. llms.txt is a positive signal — a hand-curated index of your authoritative pages, in a clean Markdown format, that LLM training and retrieval systems can ingest cleanly. They serve different purposes; you want both.
AI Overviews lean heavily on classic search authority — pages that already rank well, plus Reddit threads, plus structured FAQ/How-To content. Optimising for AI Overviews is ~70% classic SEO + 30% answer-first content design + schema saturation.
It can — but the entity-building stage takes longer (8-12 weeks vs 4-6) and Wikipedia notability is a real bar. For brand-new businesses we usually recommend a hybrid: classic SEO foundation + GEO-ready content from day one + entity work spread over 2-3 quarters.
Hindi and Hinglish queries are growing fast. We design content to handle both — answer-first blocks in English (LLMs translate well from English to Indic) plus Hindi versions of the most important commercial pages with proper hreflang. Tamil, Marathi, Bengali coverage on request.
LLM landscapes shift quarterly — new platforms, new ranking signals, new training cycles. We recommend a quarterly refresh (1-2 weeks of work) to re-probe queries, fill new content gaps, and keep schema/llms.txt current. Some clients self-manage after 2 quarters; others stay on retainer.
Talk to a senior engineer in 24 hours — no juniors, no sales reps, no jargon. Just a clear scope, an honest estimate, and a build plan.