Get discovered with AEO — when your customers ask AI.

SEO helps a page rank in a search results list. AEO (Answer Engine Optimization) helps an AI system understand, trust and cite a company when it generates a direct answer or recommendation. Dala Forge treats them as connected, not competing: strong technical SEO is part of what makes a company legible to AI systems in the first place.

Both. Technical SEO, structured data, crawlability and content architecture form the foundation. AI recommendation visibility is built on top of that foundation, not instead of it.

It is the practice of understanding how AI systems currently represent a company, where that representation is weak or missing, and what evidence would close the gap. It combines research, entity mapping and competitive analysis.

By testing how a company is represented across AI systems on relevant category and comparison queries, tracking which sources those systems cite, and monitoring how that representation changes as we implement work.

Monitoring tools tell you what is happening. SEO agencies typically stop at rankings. Dala Forge combines the research with implementation — we work alongside a client's team to actually make the changes, not just report on the gap.

Both. The Dala Forge system ends with measurement, not implementation — we track whether representation and visibility actually improved after the work is done.

AI recommendation behaviour is global, but the starting point is not. Most Nigerian businesses have inconsistent Google Business Profiles, thin or outdated directory listings, and a digital footprint that under-represents how established they actually are. Dala Forge's initial research and client work is centred on Abuja and the wider Nigerian market, built around those specific gaps rather than adapted from a US or UK playbook.

It matters more, not less. Word of mouth and WhatsApp activity are real signals of trust, but they mostly don't leave a public trail — nothing an AI system can read, index or cite. A well-regarded business can still be invisible to AI simply because its reputation lives in conversations, not on the open web.

Early, not irrelevant — which is the opportunity. AI-assisted search is already part of how Nigerians research products and services, and adoption is moving faster than most local businesses' digital presence is keeping up with. Because so few Nigerian companies have deliberately shaped how AI systems represent them, the businesses that address this now are more likely to be the ones AI defaults to citing later.

Nigeria has a growing pool of SEO and digital marketing agencies, alongside globally standard tools like Semrush, Ahrefs and Google Search Console that any of them — including Dala Forge — might use to diagnose a site. What most of that landscape stops at is traditional search ranking. Dala Forge starts from the same technical SEO foundation but is built specifically around AI recommendation visibility: how AI systems represent, cite and recommend a company, not just where a page ranks in a results list. The tools inform the work; they aren't the work.

Indirectly, yes. A public, verifiable CAC registration is one of the clearest signals that a business legitimately exists, and it's the kind of structured, citable fact that strengthens entity clarity — the difference between a company an AI system can confidently name and describe versus one it has to guess about.

Mostly because their real digital footprint doesn't match their real-world reputation. Many established Nigerian businesses run on WhatsApp, Instagram and word of mouth — channels that build customer trust but leave nothing for an AI system to read, index or cite. Inconsistent business names, addresses and phone numbers across the few listings that do exist make it worse.

Real estate, healthcare, finance, hospitality, professional services and education, starting in Abuja. These are categories where the purchase is high-value enough that customers are already asking AI systems comparison and trust questions before they commit to a business.

The methodology scales down, but Dala Forge is deliberately starting with categories where the purchase decision is high-value enough that customers already research before committing — real estate, healthcare, finance, hospitality, professional services and education. A small local business in one of those categories is a better early fit than a large company in a low-consideration category, because that's where AI-assisted research is already shaping the decision.

Yes, meaningfully. Each system draws on different sources, weighs recency and citation quality differently, and can represent the same company inconsistently. That's why Dala Forge's measurement approach tests a company across multiple AI systems rather than one, and tracks each separately — a company can be well represented on one system and effectively invisible on another.

We test how the company is currently represented across AI systems on relevant category and comparison questions, map its entity clarity and digital footprint, review technical SEO and structured data, and identify what a competitor benchmark shows about the gap. The output is a clear picture of what AI systems currently know, get wrong, or don't know at all about the company — not a generic checklist.

No. The audit works with information that is already public — your website, business listings, published content and how AI systems respond to public queries about your company. It does not require access to internal systems, customer records or private data, and none of that is shared with OpenAI, Google, Anthropic or any other AI provider.