Cameron Duncan founded Answer Intent to close the AI search visibility gap.
Cameron Duncan is the founder of Answer Intent, a productised AEO and GEO agency on the KwaZulu-Natal South Coast. He has 15 years of marketing and operations experience across founder-led businesses in tourism, B2B services, and digital. Answer Intent was built to close the AI search visibility gap for South African founder-led businesses.
The market gap that became Answer Intent
Cameron noticed something specific while running marketing for founder-led businesses across South African tourism and B2B services. Generative AI tools like ChatGPT and Perplexity were citing competitors that were structurally well-organised but objectively inferior on every other measure. Better businesses were invisible. Answer Intent was built to close that gap.
The observation was concrete. In the tourism sector, a luxury operator with a well-structured website - clean service listings, consistent entity naming, a readable sitemap - was appearing in AI-generated answers about South African travel options. Adjacent operators with stronger track records, better reviews, and more experienced guides were absent from those same answers. The difference was not quality of service. It was structural: the cited operator had given AI engines a clear signal of what they were and what they offered. The invisible operators had not.
The technical reasons are specific. AI engines extract citations from structured data first and unstructured text second. A site with validated JSON-LD schema tells the AI engine: this is an Organisation, it offers these Services, it is located here, it is run by this Person. A site without schema forces the AI to infer all of that from marketing copy written for humans - copy that hedges, uses jargon, and buries the factual claims between brand language. The inference is less reliable. Unreliable inference means lower citation confidence. Lower confidence means the business does not get cited.
The market reason was equally clear. By late 2024, most South African digital agencies had added "AEO" or "GEO" to their service lists. Almost none had rebuilt their delivery model to match. The typical offering was a month of additional SEO work with a new keyword cluster - structured data added as an afterthought, LLMS.txt not mentioned, content not rewritten to AI-extraction standards. The clients were paying for a label, not a deliverable. The gap was not between businesses; it was between what agencies were offering and what AI citation visibility actually required.
The founding decision followed directly: productise the actual work, price it in ZAR at a level South African founder-led businesses can access without a multi-month retainer commitment, deliver as files rather than access, and build measurement into every engagement so results are verifiable. Answer Intent is the implementation layer. Not a strategy consultancy. Not an SEO agency under a new name. The deliverables produce the citations.
Why Answer Intent is built as it is
Fixed prices were not a compromise. They are a deliberate signal. In a market where agency pricing is opaque - month-to-month retainers with vague scope, hourly rates with ambiguous deliverables, and change-request charges that accumulate quietly - a fixed price communicates something specific: here is exactly what you get and exactly what it costs. For founder-led businesses that do not have procurement departments or contract lawyers, that transparency removes the friction that kills engagements before they begin.
The deliverables-only model is not an operational shortcut. It is a structural decision about trust. Founder-led businesses have often had bad experiences with agencies that held their CMS logins, their domain credentials, or their ad accounts. The dependency that creates is uncomfortable and sometimes exploited. Answer Intent never holds any of it. The deliverable is a file. Your developer pastes it. Answer Intent never touches your live environment. If the relationship ends tomorrow, you have everything you paid for and nothing is locked away.
The ZAR pricing reflects the market, not an inability to compete globally. Global AEO agencies start at USD 2,000 to 8,000 per month. South African founder-led businesses are not the buyers for that pricing tier - not because the work is not worth it, but because the cash flow structure of a founder-led SA business does not accommodate that entry point. R4,900 to confirm the gap, R14,900 to close it. That is the right ratio for the market. The work is identical to what a global agency produces; the pricing reflects where the clients are.
Cameron handles every engagement personally through the current phase. That is not a capacity constraint presented as a premium. It is a practical reality: AEO deliverables require judgment at every step - which schema types apply to this business, what the LLMS.txt summary says about this service, whether the content rewrite is actually AI-extractable or just sounds like it is. Delegating that judgment to junior staff or white-labelling it produces inferior deliverables and, eventually, a guarantee claim that should not have been made. The model scales through content production support and process automation, not through diluting the deliverable.
How Cameron actually works
Cameron runs the prompt batteries himself. The current library maintains 30 prompts per engagement across five structural blocks - direct brand, category discovery, problem-led, comparison, and partner pathway - tested across ChatGPT, Perplexity, and Google AI Mode using a private-window protocol that removes personalisation from the results. The same prompt set that runs on Day 0 runs on Day 30, so the comparison is a controlled measurement rather than an impression.
Schema is built by hand, one block at a time. Cameron constructs the @graph structure directly and validates every block against the schema.org specification before delivery. The deliverable that reaches your developer has been through Google's Rich Results Test and returned no errors. This is not a script-generated schema dump; it is a structured entity map built for a specific business's actual service structure and page architecture.
Content drafts are written personally. The AEO content rules - definition layers, answer-first paragraphs, named entities, structured FAQ clusters - require judgment about which claims are extractable, which comparisons are appropriate, and which framing will survive the AI engine's inference process. That is not template work. Every draft is reviewed before delivery. The implementation guide is checked against the client's actual platform before it goes out.
The Day 30 retest is run by Cameron with the same protocol as the Day 0 audit. The report compares verbatim AI responses side by side. There is no AI-generated summary in the report. Every result is a manually captured response.
- Not a developer Schema and JSON-LD are content production work, not engineering. The schema blocks Cameron produces are HTML - your developer pastes them. Cameron is the content and structure layer. Your developer is the deployment layer. The distinction matters because it defines who owns what when something goes wrong.
- Not an SEO agency under a new name AEO and SEO share some infrastructure - schema has SEO value, and LLMS.txt may influence crawler behaviour - but the deliverables, the measurement method, and the citation paths are different categories. The Day 30 retest measures AI citation rate, not search ranking position. The two are related but not the same.
- Not promising rankings The product is AI citation visibility, measured against a Day 0 baseline and guaranteed against a Day 60 outcome. Nothing in the engagement promises search engine position changes, traffic increases, or lead volume. Those outcomes may follow from AI visibility, but they are not the contracted deliverable.
How to work with Answer Intent
Three ways in, depending on where you are in the decision.
Start with the Visibility Audit
If you want to confirm the gap before committing. 30 AI queries, 5 business days, R4,900. The audit credit applies if you move to Foundation Sprint.
See Tier 1 details 02Read the framework first
If you want to understand the methodology before deciding. The Answer Intent AEO Framework explains how AI citation visibility is built and measured.
Read the framework 03Talk it through
If you have a specific question before committing to the audit. Fill out the contact form or email Cameron directly at answered@answerintent.com.
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