01
Map the surface
Identify which AI assistants, generative SERPs, and answer engines matter for your customers. Different audiences use different tools, and the strategy starts with knowing where to play.
AEO – Answer Engine Optimisation
Show up where your customers ask first.
Answer Engine Optimisation for ChatGPT, Perplexity, Gemini, and Google AI Overviews. We make sure your brand shows up when customers ask the AI first, with content engineered for citation, not clicks.
The next decade of search is being rewritten. Position now.
Buyers are increasingly skipping search engines and asking AI directly. ChatGPT, Perplexity, Gemini, and Google’s own AI Overviews are becoming the first stop, not the last. The brands cited in those answers will own the next decade of attention. The ones invisible to AI will quietly disappear.
We build AEO programs for established businesses across Singapore, Indonesia, and Australia. Content engineered for citation, entities mapped for recognition, and prompt testing that proves you show up when your customers ask the AI first.
AI assistant ranking
Showing up inside the answers ChatGPT, Perplexity, Claude, and Gemini give to your customers. Different from web search, different optimisation, and different metrics that matter.
Where AI ranking happens
ChatGPT visibility
Showing up inside ChatGPT’s responses. Whether that’s through training data signals, real-time browsing, or being a cited source in custom GPTs and search.
Perplexity ranking
Perplexity is the most search-like of the AI assistants. We optimise for the citations and inline references that bring traffic and authority back to your site.
Claude & Gemini
Claude and Gemini draw from different sources and reward different signals. We adapt the AEO strategy for each surface rather than treating them as one channel.
Prompt-based ranking tests
We test how your brand surfaces against the prompts your customers actually use. Then we work backwards from what AI assistants reward to what we need to build.
Generative SERP optimisation
Google AI Overviews, Bing Copilot, and the generative results that increasingly sit above traditional search results. Same Google, very different optimisation.
What generative SERPs need
Google AI Overviews
Show up inside the AI-generated summary that’s now appearing on most informational searches. Different from featured snippets, with its own optimisation rules.
Bing Copilot & Copilot Search
Microsoft’s integration of Copilot into Bing changes how results are ranked and presented. We optimise for the new surface, not just the old one.
Featured snippets & rich results
Still relevant, especially for AI assistants that pull from them. Schema, on-page structure, and answer-friendly formatting earn this real estate.
Click-earning content design
Generative SERPs are designed to keep users in the search experience. We design content that earns the click anyway, by making the on-page version genuinely better than the summary.
Brand entity & authority
AI assistants reward entities they recognise as authoritative. We build the entity profile, citations, and structured data that signals credibility to both search engines and language models.
Building entity authority
Wikipedia & Wikidata
Where genuinely warranted, we work to establish a Wikipedia presence and Wikidata entry. AI assistants treat these as authoritative sources, and they compound over time.
Citations across major publications
Earned media in publications AI models recognise. The citation in the right outlet matters more for AEO than ten in irrelevant ones.
Schema & structured data
Organisation schema, person schema, product schema, and the structured data that helps AI assistants understand who you are and what you do.
Brand mention strategy
Brand mentions in the right contexts, even without backlinks, contribute to the entity profile AI models build. We treat brand mentions as a signal worth working for.
AI-readable content
Content built so AI assistants can find it, parse it, summarise it cleanly, and cite it. Different from traditional SEO content in subtle but important ways.
What AI-readable content looks like
Question-led structure
AI assistants are answering questions. Content structured around real questions, with clear, direct answers near the top, gets cited more often than content that buries the lead.
Quotable, specific claims
AI models cite specific facts, numbers, and claims. Vague marketing copy gets ignored. Concrete, citable statements with sources earn references.
Clear authorship & expertise
AI assistants increasingly weight content with named, credentialed authors. We build out author profiles, link them to expertise, and make the authority of the source legible.
Updated frequently
Stale content gets deprioritised by both search engines and AI assistants. Regular updates, with clear last-modified dates, signal that the source is being maintained.
Our approach
The new search needs a new playbook.
AEO isn’t a tactic, it’s a discipline. The signals that earn visibility inside AI answers are different from the signals that rank in traditional search, and they’re still being figured out by the entire industry.
Our process is built to test, learn, and adapt as the surface itself changes month to month.
02
Build the inputs
AI-readable content, structured data, entity signals, and the on-page work that makes you a citable source. The slow, foundational work that earns visibility downstream.
03
Earn the signals
Citations in publications AI models recognise. Wikipedia and Wikidata where warranted. Brand mentions, third-party validation, and the authority signals that compound.
04
Test the prompts
We test how your brand surfaces against real customer prompts across each AI assistant, then work backwards from what we see to what we need to change.
05
Iterate
AEO changes monthly. Models update, surfaces change, and what worked last quarter may not work this one. We test, measure, and adapt continuously.
What we can do for you.
AEO is a new discipline and engagements scope to where the opportunity is biggest. Some clients want an entity build-out and content rework first. Others come for ongoing testing and prompt tracking. Here’s the full set of capabilities we bring to AEO work.
AEO strategy & roadmap
Surface mapping, prompt research, and a written strategy for showing up where your customers actually ask.
Brand entity development
Wikipedia, Wikidata, schema, and the structured signals that AI assistants use to understand who you are.
AI-readable content
Content briefs, drafts, and on-page work designed for the way AI models parse and cite information.
Citation strategy
Earned media in publications AI models recognise, plus the brand mention strategy that builds entity authority over time.
Prompt ranking testing
Structured testing of how your brand surfaces across AI assistants, against the prompts your customers actually use.
Reporting
Monthly reviews tied to AI assistant visibility, citation tracking, and the traffic and conversion that flows from generative search.
Recent work
Brands surfacing where it matters.
Get a free
AEO audit.
Request a free AEO audit ↗
The audit covers:
- Brand visibility audit across ChatGPT, Perplexity, Claude, and Gemini
- Google AI Overview presence for target queries
- Entity profile and structured data review
- Citation footprint across recognised publications
- Content readability for AI parsing and citation
- A written brief on the highest-impact opportunities to address first
Frequently asked questions about AEO.
SEO optimises for traditional search results: ten blue links on Google. AEO optimises for AI-generated answers inside ChatGPT, Perplexity, Claude, Gemini, and the AI Overviews increasingly appearing on Google itself. The signals overlap but they’re not the same. AI assistants weight different sources, surface answers differently, and rank credibility through different mechanisms.
ChatGPT, Perplexity, Claude, and Gemini are the four we track and optimise across. Bing Copilot and Google AI Overviews sit alongside as generative SERP surfaces. The mix of where to focus depends on your customer base and category, which is what the audit determines.
Not yet. Traditional search still drives the majority of acquisition for most businesses. AEO is the channel to be early on, not the only channel to be on. The strongest programs run both alongside each other since the underlying content and authority work compounds across both surfaces.
Visibility across major AI assistants for priority queries, share of voice against competitors in those answers, citation growth in trusted sources, and downstream traffic and conversions where attribution allows. The reporting is more qualitative than SEO at this stage because the platforms themselves are less measurable. We’re upfront about that.
Faster than SEO in some ways, slower in others. Schema and structured data changes can show up in AI answers within days of being indexed. Brand entity work and citation building takes 3 to 6 months to compound meaningfully. Expect early signs of movement in the first 60 days, real shift over a longer horizon.
It’s emerging. The signals are real, the surfaces are real, and the businesses already showing up inside AI answers are pulling away from the businesses that aren’t. Whether you call it AEO, GEO, LLMO, or AI search optimisation, the work is the same and the early advantage is real. Anyone claiming to have it perfectly figured out is overselling.
No, and anyone who does is lying. AI assistants don’t have transparent ranking algorithms. We optimise the inputs known to influence surfacing and we test continuously, but we won’t pretend to control surfaces nobody fully controls.
It compounds. Strong SEO foundations (clean technical SEO, authoritative content, brand mentions) feed directly into AEO performance. We run them as a single integrated program rather than two separate workstreams when both are in scope.