AI search optimisation, also called answer engine optimisation, is the practice of making content easy for AI assistants to retrieve, understand and cite. It emphasises direct answers near the top of a page, specific verifiable facts, structured data markup, and clear entity information that models can attribute confidently.
Models quote specifics and ignore adjectives
A page saying 'we are a leading provider of innovative solutions' gives a language model nothing to quote. A page saying 'Digistan Consultant, founded 2019 in Dombivli, builds grievance redressal systems and AI agents' gives it a sentence it can cite with attribution. That difference decides which company gets named.
The practical work is structural: a direct answer in the first paragraph, real questions as headings, facts stated plainly with dates and numbers, schema markup, and an llms.txt file describing the site. None of it harms traditional SEO, and most of it helps.
Process
How we deliver it
Process flow for AI search optimization
01
Baseline your visibility
Test how assistants currently answer your category questions.
02
Restructure for answers
Direct answers first, real questions as headings.
03
Make facts extractable
Specific, dated, attributable claims instead of adjectives.
04
Mark it up
Schema, FAQPage, Organization, llms.txt and clean semantics.
05
Re-test and iterate
Measure citation changes across the major assistants.
Deliverables
What you receive
Baseline report of how AI assistants currently answer your queries
Restructured priority pages with answer blocks and FAQ schema
Entity consistency audit across site, schema and external profiles
llms.txt and crawler configuration for AI bots
Follow-up citation testing at 60 and 90 days
Engagement shape
An initial six to ten week programme on priority pages, then folded into ongoing SEO work.
Stack decisions follow the problem. This is where we usually start, not a fixed menu.
Frequently asked
Questions we get about this
Can you measure results the way you measure SEO rankings?
Not with the same precision. There is no ranking report for AI citations, so measurement means systematically testing a set of queries across assistants and tracking whether you appear. It is less exact than rank tracking and it is the honest state of the discipline right now.
Should we block AI crawlers to protect our content?
That is a real strategic choice. Blocking protects content from training use and guarantees you are never cited. For a services business seeking visibility, being cited is usually worth far more than the content is worth withheld. Publishers with paywalled work reasonably decide differently.
Talk it through before you commit
A discovery call is a working session on your constraint, not a sales pitch.
