AI doesn't just decide who to recommend. It decides what to say about you. Struxa builds the systems that shape how it represents you.
A structured assessment of how AI engines currently see your brand, what they're saying, and where the gaps are. Every audit produces a documented before state and a remediation plan.
Entry pointAbout the AEO Audit →AEO can't work on a broken site. Before strategy, the technical foundation has to be structurally readable by search engines and AI crawlers. Schema, metadata, crawlability, llms.txt.
Building the content architecture and citation signals that move a brand from invisible to recommended. Documented methodology. Measured before and after. Published case studies.
AEO is a narrative governance problem. For organizations where what AI says about you carries reputational, legal, or equity stakes, governance frameworks apply to every layer of the work. This is the thread that runs through everything Struxa builds.
A privacy-first iOS app that helps users understand Terms and Conditions in plain language. No accounts. No tracking. 5.0 App Store rating.
View on App Store →Carolina Gold Exchange launched with no website, no SEO, and no digital presence. Seven months later, ChatGPT cites them in 9 of 11 queries, including three times at position one, outpacing a competitor that has been open for over a decade. Here's what actually happened.
Read on LinkedIn →AEO is the practice of building the structured foundation and citation signals that shape how a brand appears in AI-generated answers from ChatGPT, Gemini, Perplexity, and Google AI Overviews. As AI engines continue to evolve in how they surface and represent brands, AEO is the discipline of building the conditions that make favorable, accurate representation more likely.
They overlap more than most people expect. Google says a page needs the same foundation to appear in AI Overviews as in regular search: crawlable, indexed, and readable as text. SEO focuses on ranking pages. AEO goes further, into what AI engines say about a brand and which outside sources they trust to back it up, such as directories, curated lists, reviews, press, and professional profiles.
AI engines build recommendations from sources they can find and cross-check: directories, curated lists, review sites, press, and professional profiles, alongside the brand's own website. Brands with consistent, corroborated information across the right sources are more likely to be named. Which sources matter depends on the industry and the type of business, so AEO starts by finding them.
The methodology is the same but the trust signals are different. A local business needs location-based signals such as directories and review platforms. A consulting firm needs expertise-based signals such as publications, credentials, and documented methodology. AEO starts with identifying which sources AI engines use to verify your type of business, then building presence in those sources.
AI visibility is how often, and how accurately, a brand appears in AI-generated answers. Struxa measures it by asking a fixed set of real buyer questions across major AI engines and recording whether the brand is named, described correctly, and cited. Answers change from one run to the next, so the same questions are repeated on different days and run again after changes are made.
An AEO audit establishes a documented baseline of how AI engines currently see a brand, what they are saying, and where the gaps are, including whether AI crawlers can actually read the website. It produces a before state and a prioritized plan for addressing what is missing.
Start with two things: a website AI crawlers can read, and consistent information about your business across the trusted sources for your industry. An AEO audit shows which of those is missing and works to shape the conditions that make citation more likely. No one can guarantee a citation, and anyone who promises one is overselling.
An AEO consultant audits current AI visibility, identifies the structural and citation gaps contributing to invisibility, and builds the technical foundation and external signal network that works to shape how AI engines represent the brand.
It depends. Site health, the platforms being targeted, the current state of your entity recognition, and the competitive landscape all affect the timeline. AEO is not a one-cycle effort. Results compound over time and the first re-audit is a checkpoint, not a finish line.
When people ask AI engines for podcast recommendations, the answers often draw on podcast directories and curated lists of shows, plus whatever the engine can read about the show itself. Shows go unmentioned when they are missing from those lists, or when their show pages, episode descriptions, and host details are thin or inconsistent. Fixing it starts with finding which lists and directories AI engines rely on for your topic.