The AI Visibility Platform · GEO & AEO for Agencies
When shoppers ask AI what to buy — is your client the answer?
The GEO audit agencies bill for, built into the brand kit. Fifty real shopper questions asked live across ChatGPT, Perplexity, Gemini, Claude and Google's AI Overview — mention rates, share of voice against the competitors your client names, reputation signals with receipts, a white-label report, and the corrective llms.txt written against the exact questions they're losing. Re-run monthly: the deltas are the evidence.
The monthly loop
An audit tells you where you stand — the loop moves it
Ask, score, correct — then ask again. The pack is locked, so every re-run is a fair comparison: the deltas are real movement, not noise — and the deltas are the story you show the client, month after month.
THE ANSWERS
Trackers hand you a score and stop. The correct-and-re-measure arc is the retainer — and no one else owns the whole loop.
Ask · Measure
Fifty real questions, five AI engines — one answer shelf
When shoppers ask AI what to buy, somebody gets recommended. The pulse asks the questions your client's buyers actually type — live, across all five engines — and measures whether your client is the answer, and who is when they're not.
The question pack · 50
you edit every one · locked for comparison
Five engines
250 live answers per pulse
The AI shelf
Questions you approve
Drafted from the brand kit or uploaded from the sheet your media buyer signed off — every question is reviewed before a single answer is bought.
Asked the way buyers ask
Live web search on, locale pinned — the same answering mode shoppers see, not a lab shortcut.
Evidence, always
Two hundred verbatim answers with every cited source — so the score is backed by receipts, not a black-box number.
The Query Fan-Out · Observed, Never Guessed
Before an engine answers, it decides: search the web — or not
Ask an assistant a buying question and it quietly fans out — running its own searches, reading what they surface, then answering. Or it doesn't: no searches, no sources, an answer from wherever it already stood. The pulse records which one actually happened, on every answer — from the engines' own disclosed telemetry, never inferred. We observe; your team decides what it means.
The fan-out, captured
The exact searches each engine ran — provider-disclosed on every answer, never reconstructed. Including the searches that name your competitors, and the ones dated years stale.
The fork made visible
Every answer says whether the engine searched at all. Retrieved answers have a source path you can audit and win; unretrieved ones are tracked honestly as reputation signals — no invented remedies.
Observation, not opinion
We report what the response payload exposed — floors, not estimates; silence, never guesses. What it means for the brand stays your team's call. The pulse just gives you the optics.
The audit, end to end
From the question pack your client approves to the report they keep — every step with evidence attached.
The question pack
Fifty questions you control
Real shopper questions across five lanes — buying-intent, brand, comparisons, use cases, reputation. Draft them with AI from the brand kit, upload the spreadsheet your media buyer approved, or type them in — you review every question before anything runs.
Asked live
The five engines, as buyers see them
Every question is asked with live web search on — the mode shoppers actually use — across ChatGPT, Perplexity, Gemini and Claude, plus Google's AI Overview on the live search page, pinned to your market's locale. Two hundred and fifty answers per pulse, captured verbatim with every source they cited.
The shelf
Share of voice you define
The competitor set is yours — the brands your client actually cares about, never picked for you. On every unbranded question, the pulse counts who the engines put on the shelf and ranks the whole set, your client highlighted.
Reputation
What shoppers hear at the moment of doubt
“Is it legit?” “Common complaints?” “Worth the money?” The reputation lane captures how the engines answer purchase-doubt questions — including the complaint themes they repeat — so the narrative gets managed instead of discovered.
The evidence
Every answer, verbatim
Browse all two hundred and fifty answers by lane — what each engine said, word for word, which brands it named, and exactly who it cited. The cited-domain rollup becomes the map of where AI recommendations are earned.
The citation audit
Open the sources behind the answers
Buy the audit lane by lane — competitor gap, news & listicles, Reddit threads, YouTube videos, reputation sources — and every selected page is opened and read: byline, date, brands named, your client's exact placement, and a realistic path to inclusion. An AI analysis then reads all of it and writes the strategy.
The query fan-out
The searches behind every answer
Every answer records the searches the engine actually ran — provider-disclosed, never reconstructed — and whether it searched at all. “No web retrieval observed” is a first-class finding: those answers have no live source path, and the pulse says so instead of inventing one. Recurring searches, competitor-named searches, and stale-dated searches roll up per run.
Inside the videos
Transcripts, timestamped and lit
Audited videos are read in full — the whole transcript, never a skim. Your client lights up in amber, every competitor in its own colour, and each mention carries the second it was spoken: click the timestamp and the video opens at that moment. Auto-caption misspellings of the brand are caught and lit too.
The attribution read
Both ends of the bridge, measured
Nobody can trace a single AI answer to a single sale — so this measures both ends instead. Connect the client's Google Analytics (optional, one click) and every pulse pairs how often each engine names the brand with the visitors who measurably arrived from that engine and what they did. Directional evidence, engine by engine.
The deliverable
A client report built to bill
White-labeled with the brand kit's logo: executive verdict, five-engine scoreboard, share of voice, verbatim exhibits, reputation chapter, the full citation audit, and every-question appendices — including full video transcripts as a switch-on appendix. Prints to PDF with an agency-ready filename — and the recommended-actions page detaches for findings-only delivery.
The Citation Audit · Inside the Sources
Every answer showed its sources — the audit opens them
A page the engines leaned on can name five rivals and never mention your client — or name them, and still pass them over. Nothing about a link tells you which. The audit opens each cited page and reads it: who wrote it, when, which brands it names, where your client places, and what it would take to be included.
You choose what gets opened
The audit is bought lane by lane with exact counts shown up front — and a page that refuses to open is never part of what you pay for. You keep its link either way.
Evidence, not vibes
Verbatim quotes, real bylines, publish dates and exact list positions — every claim in the audit carries its receipt, ready to be read aloud in the client meeting.
Built to bill
Findings land in the white-label report as work orders — placement and outreach for the agency, product and operations signals for the client. The audit is the scope document.
Five kinds of source, five kinds of read
Each lane is audited on its own terms — a news round-up, a community thread and a review video hold different intelligence, and each is bought separately with its exact count shown before anything runs.
The pages recommending rivals instead. Some already name your client — buried low in a round-up; the rest never mention them at all. One is a repositioning job, the other is outreach, and the audit says which, page by page, with a realistic path in.
The round-ups and press the answers came from: who wrote each piece, when it published, and exactly where your client places on it. First of five is a win to protect; twelfth of twenty-five is work — and the byline is the outreach list.
Full threads with their comment trees, upvotes and dates — which rooms answer for the category, how the community actually talks about the brand, and the years-old threads the engines keep returning to.
The channels behind the answers: audience, publish dates and length — and with the watch option, what each video actually concluded about the brand, in its own words.
What the web says when someone asks about your client directly — including when the sources the engines rely on contradict each other. A contradiction is an opening: the authoritative answer doesn't exist yet.
Inside the Videos · The Transcript, Illuminated
The engine watched a video. Now you can too — at the exact second it matters
When a cited video is audited at the transcript tier, the whole transcript is read — not skimmed: your client lit in amber, every competitor in its own colour, each mention stamped with the second it was spoken. Click a timestamp and the video opens at that moment. Even auto-caption misspellings of the brand are caught and lit.
After the reads · The AI Analysis
Then the AI reads everything it read — and writes the strategy
A human skimming hundreds of sources sees pages. The deep analysis sees what repeats: the themes that agree with each other, the sites that keep supplying the answers, the surfaces that have fed results for years — and it splits the work plainly between what the agency can place and what the client has to fix.
The corrective action
The analysis doesn't stop at a score — it writes the fix
Trackers hand you a number. The pulse hands your client a corrected llms.txt — the machine-readable brand file AI engines read — authored from the live website and the client's existing file, aimed at the exact questions they're losing, with every change documented.
The gap map
from the last pulse — automatically
The corrected llms.txt
Ready to deployImproves — never replaces
If the client's site already has an llms.txt, it's fetched and treated as the incumbent: its true content carries forward with the new layers woven around it.
Written against the gaps
The lost questions from the pulse steer what the file covers — the client's real answers, placed exactly where the engines look.
Receipts, not a diff
Every corrective action is listed — what was preserved, what was added, what was fixed — so the value is visible without comparing files line by line.
Prove it moved
Same fifty questions next month — the deltas are the evidence
The pack is locked, so every re-run is a fair comparison. Deploy the corrections, run the pulse again, and the report shows the movement — the number the retainer bills against.
This pulse vs the last
same locked packmovement reported at pack and lane level — where it's statistically honest
Run the whole loop from Claude
Draft the pack, run the pulse, read the gaps, generate the report and the corrected llms.txt — the same audit, driven from a conversation.
Run the audit
“Run an AI visibility pulse for Acme — how do the AI engines recommend us?”
Read the results
“Where is Acme losing on the AI shelf — which questions, on which engines?”
Deliver the fix
“Write Acme's corrected llms.txt against the gaps and give me the client report link.”
Ask an engine the same question twice and the wording can change. That's why movement is only ever reported at pack and lane level, where the aggregate is stable — and why single answers are shown as evidence, never tracked as metrics.
Month-over-month comparison only runs against the same locked question set — editing the pack starts a new version and a new baseline. That's the fence that keeps the comparison honest.
When an engine answers without any visible web search, the pulse says so — “no web retrieval observed” — instead of inventing sources. Those answers have no live source path to audit; they're tracked as reputation signals and re-measured every run.
It's written only from what the materials support — the live site, the existing file, the brand kit — and every corrective action is listed. You review it before it ships to the client's site; nothing deploys itself.
The citation audit is built from every source the engines disclosed — including Gemini's, resolved from its own grounding data, and the references behind Google's AI Overviews. Most disclosed sources still come from Perplexity. Part of the web refuses automated readers; those pages are never part of what you pay for, and you always keep the links.
Visits from AI engines that arrive without a referrer hide inside Direct traffic — so every measured count in the attribution read is a floor that can only rise. An engine with nothing measured shows “watching”, never a number we invented.