AI SEO Services
Structured content and entity signals that get your brand cited by ChatGPT, Perplexity, and Google AI Overviews.
Who this is for
If any of this sounds like you, we should talk.
Your prospects ask ChatGPT before Google
Buying behavior shifted. If you are not in the AI answer, you are not in the consideration set. You want to be the source the model trusts.
Your SEO traffic is flattening
AI Overviews are eating zero-click queries. You need a strategy that captures intent inside the assistant, not just below the fold.
Your competitors keep getting cited
You see their name in Perplexity answers and ChatGPT summaries. You do not see yours. You want to know exactly why and fix it.
You sell something an LLM should recommend
SaaS, B2B services, considered consumer products. Anything where a user asks an AI for a recommendation. That is where AISO compounds.
What changes for you
Outcomes you can point to, not features you can ignore.
- Citation share inside ChatGPT, Perplexity, Gemini, and Google AI Overviews for your priority queries.
- Content structured so LLMs can extract, summarize, and cite without ambiguity.
- A measurement system that tracks AI referral traffic in GA4, not guesses.
- A content engine that compounds, every new article reinforces the entity model the assistants already have of your brand. The same entity work lifts your technical SEO, content, and landing pages.
- Internal links, schema, and llms.txt that signal authority on your topic, not just relevance.
What is included
Scope, organized by phase.
Discovery (Phase 1 of 5)
Phase 1
Discovery
What we lock down in this phase before moving on.
- Baseline AI citation audit across ChatGPT, Perplexity, Gemini, Claude, Copilot
- Query inventory (informational, comparison, recommendation)
- Competitor citation share analysis
- Brand entity audit (Wikipedia, Wikidata, structured citations)
How an engagement works
From hello to handoff, step by step.
AI citation baseline
We run your top 50 commercial and informational queries through ChatGPT, Perplexity, Gemini, and Google AI Overviews. You get a citation share scorecard against three competitors.
Query and content map
We map every query to the content that should win it. Some need new pillars. Some need rewrites. Some need schema and internal links. You approve the plan.
Production sprints
We write, structure, and ship content built for LLM extraction. Clear answers, citation-worthy data, FAQ schema, entity reinforcement. You review each batch.
Measurement setup
We instrument GA4 with referral tracking for ChatGPT, Perplexity, and Claude. You see AI traffic in your dashboards, not folklore.
Re-test and iterate
Every 30 days we re-run the citation tests on tracked queries. We double down on what is winning and rework what is not.

Case study
WitsCode (our own brand)
Verified in Search Console on 2026-08-26: 206,000+ impressions in the last 90 days, 487 pages earning impressions, and 3,794 distinct queries ranking, including competitive SaaS GTM and AI search terms.
Three months ago, our site had near-zero visibility in AI answer engines despite a strong technical foundation. We were not cited on the SaaS GTM and AI search queries we built our service around.
We applied the same AISO playbook we sell to clients. Built 30+ deeply researched pillar articles, restructured for LLM extractability, added Article and FAQ schema across the content library, and reinforced the WitsCode entity through consistent citations and structured data.
Why us
What you get with WitsCode that you don't get elsewhere.
We do this for our own brand, in public
Our site ships llms.txt, publishes the Open Knowledge Format spec, runs the free AI Visibility Checker, and feeds a 300+ article content engine. We are not theorizing, we are running the same playbook on ourselves where you can inspect it.
Engineering plus content, in one team
Schema, entity markup, internal linking, and content production live under one roof. No handoffs between an SEO consultant and a content shop.
Measurable, not magical
Every engagement starts with a citation baseline and ends with a tracked citation lift. You see exactly what changed and why.
WitsCode rebuilt our Shopify store so it finally converts the traffic we were already getting. They understand speed and storytelling in equal measure, and the store has been a real growth lever since launch.
Free download
Free AI Visibility Checker
See how your brand shows up in AI answers today. Run our free checker and get a scored report with a ranked action list in minutes.
Frequently asked
Questions before you reach out.
AI SEO is the practice of optimizing your website, content, and brand signals so AI systems such as ChatGPT, Perplexity, Gemini, and Google AI Overviews cite you as a source when they answer your prospects' questions, combining classic search fundamentals with structure built for machine extraction. It is the umbrella term for GEO and AEO, and it is where buying research is moving.
Generative engine optimization (GEO) is the discipline of making your content easy for generative AI engines to retrieve, extract, and cite, using answer-first structure, verifiable data, consistent entity signals, and schema markup so models like ChatGPT and Perplexity choose your pages over competitors when generating answers. In practice, GEO and AI SEO describe the same work. GEO is the term the research community uses.
Answer engine optimization (AEO) targets direct-answer surfaces like featured snippets, voice assistants, and AI Overviews, while GEO targets generated responses from large language models, and AI SEO is the umbrella covering both plus the entity and technical work underneath, so the three overlap heavily and share one playbook. You do not need three vendors. You need one system that structures answers, reinforces your entity, and measures citations.
To get cited, publish content that answers specific questions directly in the first sentence, back claims with verifiable data, mark pages up with schema, keep your brand entity consistent across the web, and make your site crawlable to AI user agents, then track which queries actually cite you. That is the core of our engagement. We run the baseline, fix extraction, and re-test every 30 days.
llms.txt is a plain-text file at your site root that gives AI crawlers a curated, machine-readable map of your most important pages and what they cover, helping language models find, understand, and cite the right content instead of guessing from raw HTML. We maintain one on our own site and ship one with every AI SEO engagement.
AI SEO does not replace traditional SEO; it builds on it, because AI answer engines still rely on crawlable sites, fast pages, clean architecture, and authoritative content, which means your existing rankings and technical foundation accelerate citation wins rather than becoming a sunk cost. We layer citation structure, entity reinforcement, and llms.txt on top of the SEO you already have.
We measure AI visibility with a citation baseline: your priority queries run through ChatGPT, Perplexity, Gemini, and Google AI Overviews, scored for citation share against competitors, plus GA4 referral tracking for AI assistant traffic, then re-tested every 30 days so you see movement, not folklore. You can get a first read yourself in minutes with our free AI Visibility Checker at /ai-visibility-checker.
Most sites see their first citation lifts within 30 to 60 days of shipping structured, answer-first content, with compounding gains from 90 days onward as assistants re-index your pages and your entity model strengthens, though timelines vary with your existing authority and how competitive your queries are. No one can guarantee a specific citation. We guarantee a measured baseline and a tracked lift on the queries that matter.
Ready to be the answer instead of the footnote?
Start a project. We will show you exactly where your brand stands in AI search today, and what it takes to win.