Benchmark
Run a structured prompt set across major assistants to record where you appear, how you are described and who is cited instead.
Rapid North helps B2B SaaS companies become visible in ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews through generative engine optimization (GEO), answer engine optimization (AEO) and LLM SEO.
THE RAPID NORTH APPROACH
Buyers increasingly ask an AI assistant before they open a search results page. If your product is not in that answer, you are not on the shortlist.
AI search optimization builds on strong SEO, then adds the signals that help language models understand, trust and recommend your product.
We test how ChatGPT, Perplexity, Gemini, Claude and AI Overviews describe your category, your competitors and you.
Content structured as clear, quotable answers with evidence, so generative engines can cite it with confidence.
FAQ, definition and comparison content written for the exact questions buyers ask assistants.
Consistent product, company and author entities, with structured data that removes ambiguity for machines.
Mentions on the review sites, communities, publications and lists that AI models draw on most.
Ongoing monitoring of brand mentions and citations across assistants, reported alongside organic search.
How we work
We treat AI visibility as an extension of your search and authority strategy, not a separate gimmick, and we are clear about what can and cannot be measured.
Run a structured prompt set across major assistants to record where you appear, how you are described and who is cited instead.
Fix technical access, entity clarity and missing answer content on your own site first.
Build presence on the sources models trust: reviews, communities, comparisons and expert publications.
Re-run the benchmark monthly and shift effort toward the prompts and sources moving your share of answers.
AI visibility matters when it puts your product in front of buyers at the moment they ask for a recommendation.
What we measure
AI answers vary from run to run, so we measure across many prompts and over time rather than chasing single screenshots.

Senior context, applied
The working rhythm combines customer context, the practical limits of the funnel, and the next decision the team needs to make. It creates a useful brief for execution instead of another isolated activity plan.
See the engagement modelWhen it fits
We use the available evidence to decide whether this service is the right next move and what it must connect to.
Connected, not isolated
A service page should help you make the next decision, not make every problem sound like the same channel problem. These are the next places to go when you need the surrounding context.
An AI SEO agency improves how often and how accurately your brand appears in AI-generated answers from tools such as ChatGPT, Perplexity, Gemini and Google AI Overviews. The work combines technical SEO, answer-focused content, entity and schema work, and building citations on trusted third-party sources.
Generative engine optimization is the practice of making your content easy for generative AI systems to find, understand and cite. It focuses on clear answers, supporting evidence, consistent entities and presence on the sources those systems rely on.
The terms overlap. Answer engine optimization (AEO) focuses on being the direct answer to a question, generative engine optimization (GEO) on being cited in generated responses, and LLM SEO on how large language models represent your brand overall. In practice we run them as one AI visibility programme.
No. AI systems still draw heavily on well-ranked, well-structured web content. Strong SEO is the foundation, and AI search optimization adds the extra signals that help your brand get cited.
We run a consistent set of buyer prompts across major assistants on a regular schedule, record mentions, citations and descriptions, and combine that with AI-referred traffic in your analytics. Results are reported as trends because individual AI answers vary.