Canlah AI is a GEO agency in Singapore. We record how ChatGPT, Gemini, Google AI Overviews and AI Mode answer the questions your buyers ask, show you who gets named instead of you, then fix the causes on your site and in the sources those engines cite. Same questions re-measured every month; the raw answers are yours.
Each month we deliver answer pages, site fixes and a map of the sources AI cites most with what to publish there, plus a re-test. We are not selling tools; we sell solutions.
Singapore and regional brands whose buyers ask an AI assistant for a shortlist before they ever send an enquiry. When the first question is "who should I look at?", the answer decides whether you are in the running.
Founders and procurement leads ask ChatGPT or Gemini which vendors to shortlist, then visit two or three of them.
Parents ask AI which centres to compare, and the answer narrows the list before a trial class is booked.
Diners ask for a place by occasion, price band and neighbourhood, and AI answers draw on food media and review sites.
Overseas buyers research Singapore and regional suppliers through AI assistants before the first call.
We deliver in English and Chinese. Where your tier includes Chinese, buyer questions asked in Chinese are tested on the same AI platforms (ChatGPT, Gemini and Google's AI) and in the same way as English ones, so bilingual buying committees get the same evidence in their own language.
Three tiers, priced per AI platform from $1,500 a month each. Starter covers ChatGPT, from $1,500 a month; Growth adds Google AI Overviews, from $3,000 a month; Full covers ChatGPT, Google AI Overviews, Google AI Mode and Gemini as a customised plan: contact us. Each platform carries 4 buyer questions (4 buyer intents, each asked 5–10 real ways), re-tested monthly against your baseline.
Monthly starting prices. Full is scoped with you.
One product · one market
From $1,500 a month
1 platform · from $1,500 a month · 4 buyer questions
Several product lines · two markets
From $3,000 a month
2 platforms · from $3,000 a month · 8 buyer questions
A group · a category leader
4 platforms · customised, contact us · 16 buyer questions
Every tier in full: what's included and what's billed separately
Behind every tier, every engagement runs through four stages. Each stage produces named deliverables, and each deliverable is tied back to the measurement protocol, so progress is something you verify, not something you take on faith.
We lock your buyer questions, ask them in full on the AI platforms in your tier, and deliver a baseline report: which engines cite you, which cite competitors, at what frequency, sourced from which pages — with the complete evidence archive attached. This baseline is the fixed point every later report compares against.
We map your buyer roles to query clusters and set the channel mix according to citation physics rather than habit. Industry citation studies indicate roughly 82% of AI citations come from earned media — third-party listicles, review platforms, community discussions — so we weight off-site authority accordingly instead of over-investing in your own domain.
We make your site quotable by machines: 40–60-word answer capsules in the first lines of every key page, structured data (Organization, Service and FAQ schema), an AI-facts page and llms.txt, honest comparison pages, and indexation plumbing. AI engines frequently compose answers from titles, descriptions and first-screen text without opening the page — so the first screen is engineered as the primary asset, not an afterthought.
We build presence in the sources AI engines actually cite: review platforms such as G2, Capterra and Clutch; inclusion in authoritative "best of" roundups; original research other publications cite; and community participation on platforms like Reddit — always under a disclosed, affiliated identity. We treat disclosure as a feature, not a constraint: undisclosed accounts are a compliance and reputation liability that eventually lands on the client, and we will not create one.
Every month: the identical re-test, a citation-frequency comparison against baseline, and AI-referral attribution from your own analytics — assistant-referred sessions and sign-ups you can verify without us in the room.
About 90 days to the first reliable read. On-site foundations ship in the first 30 days, the first before/after comparison lands at day 60, and by day 90 there are enough repeated samples to decide on. Nobody can guarantee AI answers — engines are non-deterministic and their retrieval changes without notice — so the timeline is written as checkpoints you can confirm yourself, not as outcomes we do not control.
Buyer questions locked, a full check on your tier's AI platforms complete, baseline report and evidence archive delivered. On-site foundation shipped: answer capsules, structured data, AI-facts page, llms.txt.
Checkpoint: you hold the raw records and can re-run any check yourself.
Second full re-test under the identical protocol; first citation-frequency movement report, presented as ranges against baseline. First off-site placements live — every one disclosed and listed.
Checkpoint: a before/after table where both sides were produced the same way.
Third re-test; enough repeated samples for the trend to mean something. Quarterly question review with your team, plus AI-referral attribution from your own analytics.
Checkpoint: a decision-grade report on what moved, what did not, and what the data says to do next.
GEO is compounding work. The honest expectation — which we set in writing — is that roughly 90 days produces the first reliable before/after, and momentum builds from there. Any vendor promising cited answers in week two is describing luck, not a method.
The same way every month, so this month's numbers can be compared with last month's and checked by someone other than us:
The buyer questions in your tier — 4, 8 or 16 — agreed with you and locked for the measurement period.
Each question asked several times on every AI platform in your tier, in rotated phrasings: ChatGPT, plus Google AI Overviews, Google AI Mode and Gemini on the higher tiers.
Results reported as ranges against your baseline, never as one screenshot or a rank position.
Raw answers, citations and timestamps kept for you, so anyone can re-run the set and check our numbers.
DeepAudit, our person-checked diagnostic, sets the baseline every engagement is measured against
Behind the service
DeepAudit sets your baseline and Canlah All-Stars does the work. Canlah GEO, in early access, lets you check the answers yourself.
Diagnostics, not before/after claims: these are measurements from the first weeks of client work, each traceable to answer records, screenshots and timestamps the client can re-check.
A comparable peer in the same price band was named in 11 of 32 non-branded AI answers; the client in 1. In Google AI Mode the peer was named 4 of 4 times, the client 0 of 4. Google had indexed 2 of the site's 7 pages, and the site carried no restaurant structured data.
3,452 genuine reviews across restaurants each rated 4.5★ or higher, yet zero recommendations across 49 non-branded questions asked on three AI engines. Mobile first-screen load time: 16.8 seconds against a healthy threshold of 2.5.
Named with permission: TAFA Education Group — its parent platform and four sub-brands, including Futurum Academy and TreeArt, plus the Magi product line.
canlah.ai is enrolled in the exact program we sell. Our July 2026 self-audit baseline, run under the protocol below, showed our brand cited in zero of our own commercial-intent queries — a blunt starting point we chose to publish rather than bury, because it is the "before" photo every client engagement also begins with. We re-test our own questions on the same monthly cadence we apply to clients.
We also ran our own category. The figures below come from instrumented runs on a GPT-5.5 class model with web search, Singapore, 30 rounds across six buyer questions, 30 August 2026 — plus a separate 15-round set on Google AI Overviews in September. One vendor's measurements of its own category, stated with their limits so you can weigh them.
On "best SEO agency Singapore" and "top SEO agencies in Singapore 2026", our brand was named in zero of five runs each. We rank on questions that use the words GEO or generative engine optimisation, and not on the words most buyers actually type. We publish this because a vendor who will not show you their own weak numbers will not show you yours.
On "generative engine optimization agency singapore" we were named and cited in three of five runs, and on "best GEO agency" in two of five. That is a narrow win on category-specific vocabulary, not a general one.
One agency directory was cited in 18 of 30 rounds on that engine — more than any agency's own website. On a different engine, in a separate 15-round set, the same directory appeared zero times while Singapore agencies' own sites made up eleven of the fifty-five cited domains. Which sources matter depends on which engine you are asking about.
Issuing one identical prompt three times in fresh sessions returned three different vendor sets. This is the single most important thing to understand before buying: any claim resting on one screenshot describes one roll of the dice.
These describe two engines on two question sets in one market, over two dates. They are not a ranking of Singapore agencies.
Clients we've served include Baidu AI Cloud, Google Cross-Border Accelerator, ByteDance International Strategy and a Singapore-listed group. The founding team has served Haleon, Starbucks, ByteDance, Alibaba Cloud, Publicis and McCann, all before Canlah AI. Canlah was Global Runner-up at MWC Pitch2Pitch 2025 from a field of over 3,000 startups.
We do not guarantee citations, placements or rankings — our commitments are to deliverables, cadence, reproducible measurement and one written acceptance bar. We do not report vanity metrics; only frequency data you can re-verify and referral traffic you can see in your own analytics. We do not operate undisclosed community accounts under any circumstances.
What we do commit to, in writing:
Every claim on this page is checkable. That is the point of the page, and it is the point of the agency.
Hold every vendor, including us, to the same tests. These are the guides we would read first.
The buyer framework: what to ask every vendor for in writing, with eight providers' public claims checked side by side.
Ten Singapore GEO agencies, ourselves included, ranked on the same public criteria, with a count of how often AI answers cited providers' sites.
How GEO retainers are structured, what moves a quote, published market ranges, and the grant change from MRA to the EDGE Grant.
The self-test protocol: buyer questions, repeated runs, per-engine scorecards — and the traps that invalidate most self-tests.
Where the two disciplines overlap, where they diverge, and why rankings no longer guarantee citations.
Comparing terms rather than vendors?
Generative engine optimization (GEO) is the discipline of making a brand visible, cited and recommended inside AI-generated answers — in ChatGPT, Gemini, Google AI Overviews and Google AI Mode — rather than only ranked in classic search results. A GEO agency does for AI answers what an SEO agency does for the search results page: it engineers the signals those systems retrieve, trust and quote.
The reason this matters now is a change in buyer behaviour, not a change in fashion. When a procurement lead in Singapore asks an AI assistant "which vendor should we shortlist for this," the assistant composes a direct answer from the sources it can retrieve and verify. If your brand is absent from those sources, you are absent from the answer — and the buyer may never reach a results page where your rankings could have saved you. Peer-reviewed research on generative engine optimization (the Princeton GEO study, Aggarwal et al., KDD 2024) found that the strongest interventions — adding statistics and adding quotations — lifted visibility by up to 41% on its position-adjusted word count metric, evidence that these systems respond to deliberate, well-engineered signals rather than luck. The paper is explicit that effect sizes vary by domain, so we treat it as a directional ranking of techniques, not a number to promise you.
For companies evaluating generative engine optimization in Singapore, the practical question has shifted. Shortlisting the best SEO agency in Singapore used to mean comparing keyword rankings and backlink counts. Today it means asking a harder question: can this agency show me, with evidence I can independently verify, whether AI engines cite my brand — and whether that changed after their work?
That question is the entire premise of this page. Canlah AI is a premium SEO + GEO agency headquartered in Singapore, founded in 2026, delivered by an AI agent workforce under human strategy oversight. We make you the answer — and prove it.
GEO does not replace SEO — it extends it. Crawlability, site health and content quality remain the foundation; AI engines cannot cite what they cannot retrieve. What changes is the unit of success, the shape of the work, and how honestly it can be measured.
| Traditional SEO | Generative engine optimization (GEO) | |
|---|---|---|
| Goal | Rank on the results page | Be cited and recommended inside the AI answer |
| Unit of success | Position for a keyword | Citation frequency across repeated, controlled runs |
| Where the battle happens | Your pages vs. competitors' pages | The source pool engines retrieve from — listicles, review platforms, communities, plus your site |
| Content shape | Long-form, keyword-targeted | Direct answer capsules, extractable facts, structured data |
| Off-site signal | Backlinks | Earned citations — third-party mentions engines retrieve and trust (~82% of AI citations, per industry studies) |
| Volatility | Rankings shift gradually | Answers drift 40–60% month to month; single snapshots mislead |
| Honest measurement | Rank trackers, established | Requires a measurement protocol: locked questions, phrasing rotation, frequency KPIs, evidence archives |
| Relationship | The foundation | Built on top of SEO — never instead of it |
If an agency proposes GEO while your site still has broken indexation or thin service pages, sequence matters: foundation first. Our baseline audit covers both layers precisely so that the plan starts from what is actually broken, not from what is fashionable to sell.
Each AI engine retrieves and cites differently, so a result on one engine says little about another. Our protocol covers all four; your tier sets which ones we measure and work on, and the work is tailored to how each one behaves.
| Engine | How it retrieves | What tends to get cited | Our corresponding play |
|---|---|---|---|
| ChatGPT (with search) | Live web search; frequently composes from titles, descriptions and snippets without opening pages | Earned listicles, review platforms, pages whose first screen answers the query outright | First-screen answer engineering; presence in the roundups and review sites it retrieves |
| Google AI Overviews | Google's index plus grounding | Pages answering directly in the first lines, carrying structured data, corroborated by independent sources | Answer capsules, FAQ/Service/Organization schema, third-party corroboration of the same facts |
| Gemini | Google grounding with strong entity resolution | Consistent, machine-readable entity facts across your site and third-party profiles | Entity hygiene: consistent naming, structured data, an authoritative AI-facts page |
| Google AI Mode | Google's index, splitting one question into several related searches before composing a conversational answer | Pages that already rank in Google, plus forum and community threads — in our September 2026 Singapore checks, 89 of 219 AI Mode citations were in the same question's Google top 10, against 22 of 307 for ChatGPT | Organic strength on the follow-up questions buyers ask, plus disclosed community presence |
The pattern across all four: engines reward brands that are consistently described, independently corroborated, and directly quotable. The differences decide where each month's effort goes — and that allocation is set by your baseline data, not by a template.
Measurable means you can check it without us. Below are the three things we suggest asking every GEO agency for in writing, ourselves included, and the protocol we answer them with.
Nearly every agency now selling AI SEO services in Singapore claims to "track AI citations" or "monitor your brand in ChatGPT." Very few publish how. Fewer still show a single row of real measurement data on their own websites. The claim of measurement has become table stakes; the practice of measurement remains rare — because a real measurement pipeline is expensive to build and impossible to fake once a client asks to see the raw records.
We think buyers should force the issue. Before engaging any GEO agency — including us — ask for three things in writing:
Which engines are tested, how many phrasings of each query, and how many repeated runs? An AI answer changes with wording and with repetition; a methodology that cannot name these numbers is a screenshot, not a measurement.
How is "AI visibility" actually computed? If the answer is a rank position or a one-off appearance, be skeptical — independent studies of AI answer volatility show cited sources can shift 40–60% month to month, which makes single-snapshot "rankings" close to meaningless. The defensible unit is frequency: how often you appear across repeated, controlled runs.
Can you receive the raw records — full prompts, full responses, timestamps — so that you, or a rival agency, could re-run the same pool and check the numbers?
Any agency doing this work honestly can answer all three without hesitation. Take this checklist into every evaluation you run. Our answers to all three are published in full below.
This is the section our competitors do not have, because it requires a working measurement pipeline rather than a paragraph of claims. Every Canlah engagement runs on the same six-part protocol:
We agree the 4, 8 or 16 buyer questions in your tier with you — from brand verification and branded comparisons up to scenario, subcategory and non-branded "best/top" category questions — and lock them into the contract for the measurement period. No swapping questions mid-stream to flatter the numbers.
AI engines answer the same intent differently depending on wording. Every question in the set is asked in at least three phrasings per engine, with repeated samples across the reporting period, so the result reflects the intent — not one lucky sentence.
Checks run on the AI platforms in your tier: ChatGPT, plus Google AI Overviews, Google AI Mode and Gemini on the higher tiers. Engines retrieve differently and cite differently, so each platform is reported on its own; one engine's number is never presented as the whole picture.
Every answer is stored as a raw JSON record — the exact prompt, the full response, the citations returned, the timestamp. The archive is yours. A skeptical stakeholder, an auditor, or a competing agency can take the question set and re-run it.
We report citation frequency — the share of controlled runs in which your brand is cited or recommended, per query, per engine — as ranges, not single points. This is the only KPI design that survives the documented month-to-month drift in AI answers.
The same pool, the same phrasings, the same engines, re-run on a fixed cadence. Before/after comparisons are only honest when both sides of the comparison were produced the same way.
Two disclosures we make that most vendors will not. First, tracked questions are re-run monthly — we do not claim real-time monitoring, because no honest vendor can. Second, a measured answer is a controlled proxy for what a buyer is likely to see, not a literal recording of every user's screen. We label it as such in every report, and we anchor client-facing conclusions to what a client can reproduce in their own browser.
Ask us for a sample evidence pack and we will send one: real answer records, redacted, exactly as a client receives them. Prefer to run the instruments yourself first? Try our tested AI marketing skills — the same class of tooling this protocol is built from.
The GEO service has three tiers, priced per AI platform: Starter from $1,500 a month (ChatGPT), Growth from $3,000 a month (adds Google AI Overviews) and Full, a customised plan covering ChatGPT, Google AI Overviews, Google AI Mode and Gemini (contact us), with 4 buyer questions per platform. DeepAudit costs $99 for One read or $189 for Month read. The DeepAudit fee can be credited toward our agency services, but not toward a Canlah All-Stars subscription. After three months of the GEO service, you can run it yourself with Canlah All-Stars.
Plan on roughly 90 days for the first credible before/after reading, with on-site foundations shipped inside the first 30 days and the first re-test comparison at day 60. AI answers are volatile — independent research shows cited sources can drift 40–60% month to month — so a trustworthy trend requires repeated measurement under an identical protocol, which takes several cycles to accumulate. Some clients see earlier movement on individual queries; we report it when it happens but never project it. Any agency promising AI citations in the first fortnight is selling a screenshot, not a method.
Four things, every month. First, the re-test: your locked question set re-run on the AI platforms in your tier under the identical protocol. Second, the citation-frequency report: how often you were cited per query per engine, as ranges compared against your baseline. Third, the evidence archive update: raw records — prompts, full responses, timestamps — for every answer, owned by you. Fourth, the work log: on-site changes shipped, off-site placements secured (each one disclosed and listed), and AI-referral attribution pulled from your own analytics. Quarterly, we add a question review with your team.
Four stages. Measure: we lock the 4, 8 or 16 buyer questions in your tier into the contract and ask them on the AI platforms in your tier to establish your baseline, with every record archived. Strategy: we map your buyer roles to query clusters and set the channel mix by citation physics — industry studies indicate roughly 82% of AI citations come from earned media, so off-site authority is weighted accordingly. On-site foundation: answer capsules, structured data, an AI-facts page and llms.txt make your site quotable by machines. Off-site authority: review platforms, authoritative roundups, original research, and disclosed community participation. The monthly re-test then closes the loop against baseline.
Neither — it is the next layer on the same foundation. Your existing SEO assets (crawlable site, healthy indexation, quality content) are prerequisites: AI engines cannot cite what they cannot retrieve. GEO adds what classic SEO does not cover — answer-shaped content and structured data engineered for machine extraction, presence in the third-party sources AI engines actually cite, and a measurement protocol built for volatile AI answers rather than stable rankings. In practice we run both layers together, and our baseline audit covers both, so budget flows to whichever layer your data shows is the binding constraint.
With a protocol you can independently re-run. Your question set is locked at the start, so we cannot swap questions to flatter results. Every question is asked in at least three phrasings per engine, and every answer is archived as a raw record with prompt, full response and timestamp. The KPI is citation frequency across repeated controlled runs — reported as ranges, never a single magic number. Each month's re-test uses the identical protocol, so before/after comparisons are like-for-like. If you doubt a number, take the archive and re-run the questions yourself — the report is designed to survive exactly that test.
No — and you should walk away from anyone who says yes. AI engines are non-deterministic: the same question can return different answers on different runs, and retrieval behaviour changes without notice. No agency controls that, so no honest agency guarantees placement. We commit in writing to a +30% relative lift in how often AI names you versus your own starting baseline (for example, from 12 to 16 of 100 asks on the same questions), re-tested every month; we never guarantee rankings or a #1 position. The contract also names the deliverables, the measurement cadence and a locked, reproducible reporting protocol — so you always know exactly what changed and whether the trend is moving. Peer-reviewed research shows citation-oriented optimization measurably improves AI visibility; our job is to apply it systematically and show you the evidence either way.
It depends on your tier: Starter covers ChatGPT, Growth adds Google AI Overviews, and Full covers ChatGPT, Google AI Overviews, Google AI Mode and Gemini — engines with genuinely different retrieval and citation behaviour, so each one is reported on its own. The full locked question set is re-run monthly under the identical protocol for before/after comparison. We deliberately do not claim real-time monitoring: no vendor can honestly offer it, and a disciplined cadence with archived evidence is worth more than a live dashboard with none. We also treat these checks as a controlled proxy for what buyers likely see — and label them as such in every report.
Request a free AI visibility report, sent within 48 hours. We ask a starter set of your real buyer questions on ChatGPT, Gemini, Google AI Overviews and Google AI Mode and send you the findings — including the raw records, so you can check every claim yourself. No obligation, no template report.
Or email admin@canlah.ai or call +65 8110 0234.
Prefer a quick look on your own? Start the self-serve website deep scan (about 5–8 minutes) →
Canlah AI · 2026
Marketing in the Agent Era
When AI becomes the first reader and the first buyer
FREE WHITEPAPER
Didn't work — read it free or email admin@canlah.ai
Or read it free first →Ask Canlah
