AI SEO services that get your brand cited by the models people actually ask.
Traditional SEO gets you to page one. AI SEO gets you inside the answer. Noble Growth builds structured data, llms.txt files, and entity-first content that makes you discoverable by ChatGPT, Claude, Perplexity, and Google's AI Overviews.
Book Intro →The surface is shrinking, and most brands haven't noticed
When a user asks ChatGPT, Claude, Perplexity, or Google's AI Overviews to recommend a product, an agency, or a framework, the model returns one or two answers, not ten blue links. The game has changed from "rank on page one" to "be the answer the model cites." Most SEO agencies are still operating in the old game.
AI SEO is the practice of making your brand discoverable, recommendable, and citable by large language models. That requires a different set of signals than traditional SEO: structured data that models parse reliably, llms.txt files that give models a clean canonical view of your site, entity-aware content that builds the knowledge graph around your brand, and schema that clearly answers the questions your customers actually ask.
We were early to this. Noble Growth was one of the first agencies to ship production-grade llms.txt infrastructure and entity-focused schema. We run AI SEO for our own site and our clients, and we publish what we learn in How to Make Your Website Discoverable by AI.
What's included in an AI SEO retainer
llms.txt and llms-full.txt
A canonical machine-readable summary of your site, hand-tuned to the topics and entities you want models to associate with your brand. Updated as content grows.
Comprehensive schema markup
Article, Product, Service, Organization, Person, FAQPage, HowTo, BreadcrumbList, VideoObject, and more - structured data models can actually parse and use.
robots.txt for AI crawlers
Explicit access for GPTBot, ClaudeBot, PerplexityBot, CCBot, Google-Extended, Amazonbot, AppleBot, YouBot, Cohere-AI, Meta-ExternalAgent, and Bytespider.
Entity-first content strategy
Topical clusters built around the entities (people, companies, frameworks) you want models to link with your brand. Not keyword stuffing, structural authority.
Citation monitoring
Weekly checks of whether ChatGPT, Claude, Perplexity, and Gemini cite your brand for target queries. Trend data over time so you know if the work is moving the needle.
Traditional SEO baseline
AI SEO doesn't replace traditional SEO - it extends it. We also handle the fundamentals: site architecture, internal linking, page speed, image optimization, sitemaps.
How AI SEO work actually unfolds
The first month is setup: auditing the current schema coverage, drafting llms.txt and llms-full.txt, expanding robots.txt for all major AI crawlers, and mapping the entity graph we want your brand to sit inside. This is mostly structural work that compounds - once the foundation is right, every new page of content amplifies it.
From month two, the work shifts to content and signals. We publish entity-rich content around your core topics, monitor citation patterns, update structured data as the entity map evolves, and track crawl logs to verify AI bots are actually reaching the pages we want them to.
A useful mental model: traditional SEO optimizes for the crawler. AI SEO optimizes for the reasoning model that cites what the crawler found. That means the content needs to be not just discoverable, but easy for a model to summarize, cite, and trust.
Signals we prioritize
- Schema density. Every page gets relevant structured data, not just the homepage.
- Entity linking. Internal links treat named entities as anchors, building a graph models can follow.
- Answer-shaped content. Questions phrased as people search them, followed by direct answers at the top of the section.
- Author and organizational authority. Person schema, sameAs linking to LinkedIn and published work, Organization founder data.
- llms.txt hygiene. Updated with every new post so models see the latest site state.
Who hires Noble Growth for AI SEO
AI SEO is highest leverage for brands where:
- Your category is being researched via AI assistants (any B2B, most professional services, many DTC verticals)
- You have published expertise - a founder with a POV, real case studies, a body of work - that models can cite
- You're willing to treat content and structured data as long-term infrastructure, not a one-off campaign
- You want to be the brand that gets recommended when a prospect types "best [your category] for [their situation]" into ChatGPT
If your brand has no content surface and no POV, AI SEO is premature - there's nothing for models to cite. If you're running pure direct response with a commoditized product, traditional paid acquisition will outperform AI SEO for at least the first year. We'll tell you honestly which bucket you fall into.
One flat monthly retainer. Every channel included.
No hidden fees, no percentage-of-spend markup, no long-term contracts. Month to month with 30-day cancellation.
Less than most agencies charge for a single channel. We share the number on the intro call.
Book a Free Intro Call →Common questions
What is AI SEO and how is it different from traditional SEO?
AI SEO is the practice of making your brand discoverable and citable by large language models (ChatGPT, Claude, Perplexity, Gemini) and AI search features (Google's AI Overviews). Traditional SEO targets the ten blue links. AI SEO targets the one-paragraph answer the model generates. The work overlaps - structured data, content quality, site architecture - but the measurement and strategy differ. AI SEO rewards entity authority and answer-shaped content over backlinks and keyword density.
How quickly does AI SEO produce results?
AI models update their knowledge on different cadences. ChatGPT and Claude refresh less frequently but reward structural authority. Perplexity and Google's AI Overviews pull live search results and can reflect changes within days to weeks. A realistic expectation is: structural wins in weeks (schema updates, llms.txt deployment), citation lift in 2-6 months, and meaningful traffic from AI citations in 6-12 months.
What is an llms.txt file and do I need one?
llms.txt is a plain-text file at the root of your site that gives language models a clean, canonical view of your content. It's analogous to robots.txt but for AI consumption. Our llms.txt and llms-full.txt files at noblegrowth.co/llms.txt and /llms-full.txt are references you can study. If your site has any content you want cited by AI, yes - you want an llms.txt.
Do you allow AI crawlers in robots.txt?
Yes, aggressively. Our robots.txt explicitly allows GPTBot, ClaudeBot, PerplexityBot, CCBot, Google-Extended, Amazonbot, AppleBot, Meta-ExternalAgent, Cohere-AI, YouBot, and Bytespider. Every client gets the same treatment. Blocking AI crawlers to 'protect content' means forfeiting citation surface - the opposite of what brands should want in 2026.
Can AI SEO work for a brand new site with no content?
Partially. The structural work (schema, llms.txt, robots.txt, site architecture) is valuable from day one. But citation requires substance - models need something worth citing. For a brand new site, we'd recommend pairing AI SEO setup with a committed content program (daily or weekly publishing) so the structure has something to amplify. Noble Growth runs automated daily content publishing for its own site; we can set up similar for clients.
How do you measure AI SEO results?
Three ways. (1) Citation monitoring: weekly queries to ChatGPT, Claude, Perplexity, and Gemini for agency-buyer intent searches, logged over time. (2) Crawl logs: AI bot hit counts per page. (3) Referral traffic: visitors arriving from chat.openai.com, perplexity.ai, etc., tracked in GA4. Together these give you a real signal on whether AI SEO is moving the needle.
Ready to turn AI search visibility into revenue?
Book a free intro call with Mattimore Cronin. Share your goals, your current numbers, and where you feel stuck. You'll leave with a clear view of where the biggest growth opportunities are - whether you hire Noble Growth or not.
Book Intro →