Services / AI Search
AI Search
Get named and cited when your customer asks an assistant instead of a search box.
AI search optimization, also called Answer Engine Optimization and Generative Engine Optimization, is the work of getting your business named and cited when someone asks an AI assistant instead of typing a search. CurrentAds builds the entity, schema, and content structure these systems depend on: one consistent set of facts about your business across the web, Organization, LocalBusiness, Service, Product, FAQPage, and Breadcrumb markup, pages rewritten so the direct answer is the first thing a model can quote, an llms.txt file describing your business in plain markdown, crawler access for GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot, Google-Extended, Bingbot, and Applebot, and citation building on the third party sources ChatGPT, Perplexity, Google AI Overviews and AI Mode, Gemini, and Microsoft Copilot actually pull from.
The problem
What this looks like when it is broken
01
The model cannot tell who you are
Your name, category, services, and address say different things on your site, your Google Business Profile, and every directory that scraped you four years ago. Systems resolving conflicting facts tend to resolve them by leaving you out.
02
Your pages bury the answer
The page opens with a brand story and a value proposition, and the actual answer sits in paragraph six. A model extracting a citation takes the site that answered in the first sentence.
03
You are absent from the sources models read
Assistants lean on a narrow set of sources they treat as reliable for a topic. If your business is not present in those, no amount of on-site work gets you named in the answer.
What we do
Everything included in AI Search
Entity foundation
One canonical set of facts about your business, its category, services, locations, hours, and people, made consistent across your site, your profiles, and the major data sources.
Schema and structured data
Organization, LocalBusiness, Service, Product, FAQPage, BreadcrumbList, and Article markup implemented, validated, and kept accurate as the site changes.
Answer-first content
Every key page opens with a direct, factual, quotable answer to the question it targets, with the detail a human needs following underneath it.
Prompt and query mapping
The real prompts buyers type into ChatGPT, Perplexity, Gemini, and Copilot mapped to the specific pages that should be answering them.
llms.txt and crawler access
A clean llms.txt summary of your business, services, pricing, and key URLs, plus robots rules that explicitly allow the AI crawlers you want citations from.
Citation and source building
Presence built on the third party sources assistants cite for your category: industry directories, association listings, publications, and reference pages.
AI visibility monitoring
A fixed set of buyer prompts run on a schedule against the major assistants, recording whether you were mentioned, cited with a link, or absent.
Competitor citation teardown
Who is being named instead of you for the same prompts, and exactly which sources the assistant used to get there.
How it works
Four steps, in this order
01
Baseline visibility
We run your category's real prompts across the major assistants and record who gets named, cited, and linked today, before we change anything.
02
Fix the facts
Entity data reconciled, schema implemented and validated, and conflicting business information cleaned up wherever we can reach it.
03
Rewrite for extraction
Key pages restructured answer-first, FAQ blocks added and marked up, llms.txt published, and crawler access confirmed.
04
Build citations and re-test
Third party presence built on the sources that matter, then the same prompt set is re-run so any change is measured against your own baseline.
What you get reported
The numbers we put in your portal
Live, not a monthly PDF. These are the metrics we commit to reporting for AI Search, whether they moved in the right direction or not.
- Tracked prompt set with mention, citation, and link status per assistant
- Which sources each assistant used when it produced the answer
- Competitors named for the same prompts
- Schema coverage and validation status by template
- Referral sessions from AI assistants where GA4 can attribute them
- Search Console impressions on question style queries
- llms.txt status and AI crawler access status
- Citations earned, with the source and the date
FAQ
AI Search questions
Is AI search optimization real, or a rebranded SEO upsell?
It overlaps heavily with SEO and we do not pretend otherwise. What is genuinely different is the emphasis: entity consistency, structured data, answer-first paragraph structure, and presence on the third party sources assistants cite. If an agency sells it as a separate magic system with no connection to your site or your search presence, be skeptical.
Can you guarantee ChatGPT will recommend us?
No. These systems are non-deterministic, they change without notice, and no agency controls what they say. What we can do is make you the easiest business in your category to identify, verify, and quote, then measure mentions against a baseline on a fixed prompt set.
How do you measure something with no rank tracker?
We run a fixed set of real buyer prompts on a schedule across ChatGPT, Perplexity, Google AI Overviews, and Copilot, and record whether you were mentioned, cited with a link, or absent, along with the sources the answer used. It is a sampled measurement and we label it as one rather than dressing it up as a rank report.
What is llms.txt?
It is a plain markdown file at the root of your site describing your business, services, pricing, and key URLs in a format a language model can read without fighting your navigation. It is a proposed convention rather than an official standard, and it costs very little to publish and maintain.
Should we block AI crawlers instead?
That is a real business decision and for some publishers it makes sense. If you want assistants to recommend you, blocking the crawlers that feed them works against that. We will lay out the tradeoff and implement whichever way you decide.
Works with this
The pieces that compound with it
SEO
Technical, content, and authority, run as one program instead of a monthly blog post.
Analytics and Tracking
Build the measurement layer first. Everything downstream depends on it.
Reputation
Make what people find about you accurate, current, and worth calling.
Or see all ten services and how they fit together.
Put AI Search to work on your account
Thirty minutes, a senior operator, and a written plan you keep either way. Month to month, and you own every account we touch.