Beacon connects your live catalogue to ChatGPT, Claude and Gemini. Every week it reports what they said about your products.Beacon connects every client’s catalogue to ChatGPT, Claude and Gemini. Every week it reports what they said, under your name.
A shopper asks. The assistant answers from whatever it read last, or from your own catalogue.A shopper asks. The assistant answers from whatever it read last, or from your client’s own catalogue.
Without Beacon
Answered from memory
which running shoes should I get for marathon training?
A few that come up often are the Adidas Adizero range, New Balance’s FuelCell line and the ASICS Gel-Nimbus.
Nike makes running shoes as well. I don’t have current models, sizes or stock.
Based on four review round-ups, last indexed 9 months ago.
ChatGPT can make mistakes. Check important info.
With Beacon
Prototype
which running shoes should I get for marathon training?
Two Nike road shoes cover most of a marathon block: the Pegasus 41 and the Vomero 18.
Pick one to see what the brand publishes about it.
Two things a shopper can do without leaving the answer.
Answered from the brand catalogue feed.
ChatGPT can make mistakes. Check important info.
The competitor list mirrors one real capture, Aug 2026. The branded answer is a prototype.
The assistants describe your products from reviews, retailer pages and whatever your competitors published last. Beacon connects them to your own catalogue.The assistants describe your clients from reviews, retailer pages and whatever their competitors published last. Beacon is the stack you run to fix that, client by client, under your own name.
Your specs, stock levels and pricing become one feed the assistants read, and it updates when you do.
Catalogue, specs, tone, stock and pricing become one source, published over MCP. Every connected surface, from the flagship assistants to the agents your customers run, reads from it.
You connect your product data once, and four different jobs sit on top of it. Pick the one that sounds like yours.A client connects their product data once, and four different jobs sit on top of it. Pick the one that sounds like yours.
A client asks what you are doing about ChatGPT, and wants a number.
Evidence
42 brands are already listed inside ChatGPT, Claude and Gemini. Most categories on the Claim Board are still empty.
CanvaRolling outKlarnaRolling outUberRolling outThe Claim Board
A shopper asks which model to buy, and the assistant answers for your whole range.
Evidence
Lowe's, Peloton and Prada are all listed in the ChatGPT apps directory. Prada is the first luxury house on the board.
A shopper decides what to buy, and what to swap it for, in a chat you never see.
Evidence
Instacart turns a recipe answer into a filled basket in the same session, captured live. Shopee and Etsy are listed in the same directory.
A buyer compares models, running costs and finance over a year, one question at a time.
Evidence
Uber is the only mobility brand in the ledger behind this page, listed under ride hailing. The automotive row of the Claim Board is empty in ChatGPT, Claude and Gemini.
Beacon puts the questions your shoppers ask to the assistants, records what comes back, and counts what people do next.Beacon puts the questions a client’s shoppers ask to the assistants, records what comes back, and counts what people do next.
The questions shoppers put to the assistants about your category, in the words they use.The questions shoppers put to the assistants about a client’s category, in the words they use.
How often the answer names you, and which competitors it names beside you.How often the answer names your client, and which competitors it names beside them.
What the answer says about your product, and whether it reads warm or cold.What the answer says about a client’s product, and whether it reads warm or cold.
Each answer checked against your own catalogue, so a wrong spec or a discontinued product shows up.Each answer checked against the client’s own catalogue, so a wrong spec or a discontinued product shows up.
Find in store, a size guide opened, a booking started, a handoff into your app.Find in store, a size guide opened, a booking started, a handoff into the client’s app.
Illustrative workspace. One real capture (Aug 2026); series are drawn.
Copeland & Ives is invented. The brands are real and none is a customer.
Three tabs we keep open. One operator who ran the playbook in-house, one brand answering inside the session, one public capture of what five models say from memory.
Tally · a form builder, 11 people, no outside funding
They ran the whole playbook in-house, then published what it did.
Tally spent years being worth recommending first. The engineering keeps the answers current.What Tally ran for itself is the stack an agency runs for a book of clients.
Crossed $5M a year on the way.
Self-reported figures, via Jake Ward's public breakdown, August 2026. Tally is a real company, unaffiliated with Beacon, and is not a customer. Read the public breakdown
Three real companies. None is a Beacon customer.
Every figure belongs to the source named on its tab.
Beacon builds and runs the live feed, and captures what the assistants say back. A new deal, an ad campaign or a catalogue change is in the answers the day it ships.
One live feed from your own catalogue, published over MCP and run by Beacon end to end. Put a deal, a campaign line or a price change into it and every client that speaks the protocol reads the same thing the same day.
One source at the centre. Every client that speaks the protocol reads it.
Beacon publishes the feed and captures what the assistants say back, so cause and effect sit in one place. Ship a campaign and the answers show its effect while the flight is still live.
Your systems
PIM, ERP, BI
Beacon
MCP server, console
Into Beacon.
Back to you.
changes in, what the answers said back out
Your answer reaches the people already asking about your category, five times faster than a paid campaign finds them.
5x fasterCTAs built into the answer carry the shopper to your site and catalogue: find in store, add to cart, book.CTAs built into the answer carry every client’s shoppers to their sites and catalogues, under your name.
in the sessionOne file, against a baseline taken before the first surface went live.
weeklyBeacon builds and runs this layer. The marks above name the assistants the reporting covers. Each platform decides what it supports, and Beacon builds against those programmes as they open.
What brands and agencies ask us before they start.
There are two jobs here and Beacon does both. The reporting half is what a tracker does: which questions you appear in, what was said about you, how accurate it was, and where that sits against a baseline taken before you started. The building half is the branded answer itself, your catalogue and your steps running inside the assistant's reply, which is the work a dashboard leaves on your desk.
No, though they share a dashboard. GEO is about being included when a model writes its own answer, which is an earned job much like SEO was. Beacon builds the thing the assistant hands the person once your brand is in play: your catalogue, your steps, your actions, running inside the session. It reports on the earned side too, because both are measured on the same surface, but the two are different pieces of work with different owners.
We ask them. Your list of the questions buyers already put to an assistant is run on each one, and the answers are kept word for word, so a claim can be checked against the text that produced it. Method decides what a number means: an assistant answering from training memory with browsing switched off gives a different answer to the same assistant allowed to go and read the web, and the two are reported separately. One capture is a photograph, so a trend needs a second one.
Weekly. Every prompt on your list is re-run each week on the same wording, which is what makes this week comparable to last week. The baseline is taken before your first surface goes live, so the opening report has something to measure against.
No. Crawlers fetch it like any other text file, and no major AI search surface has been shown to prefer the sites that publish one. It takes minutes and does no harm, so publish it if you like; this site does. The movement comes from your own product pages: specifications, prices and availability, stated once and stated the same way in every market.
For the flagship assistant surfaces, yes. Each one runs its own developer programme, and a surface is a build against that programme rather than a media buy against an auction. Underneath, the brain is published over MCP, so anything else that speaks the protocol, from Perplexity and Copilot to commerce apps like Shopee and Lazada, connects without another approval round. Beacon does the builds and keeps them current as the programmes move.
One surface, one assistant, one market is weeks rather than quarters. The long pole is almost always catalogue readiness on your side rather than the connector on ours, because models are unforgiving about specifications that disagree with each other across markets. The Atlas exists so you can see the finished shape of it before anyone commits budget to it.
Three numbers, and impressions is not one of them. Share of the answers in your category against a baseline taken before you started. Accuracy of what gets said about your products, measured against your own catalogue rather than against sentiment. And installed base, the count of assistants carrying your surface, which is an audience you do not re-buy every quarter. All three sit in the Console and all three export.
Beacon reads what you already publish, meaning catalogue, specifications and support content, and writes back only what your team has approved. Conversation content stays with the platform. What returns to you is aggregate: what was asked, what was answered, and what the answer was checked against. Nothing in the design requires building a profile of the person on the other side of the glass.
They will, and they already have more than once in the time these programmes have existed. That is the argument for the layer rather than against it: when a specification moves, the connector moves, and your catalogue, your approved answers and your reporting history carry across instead of being rebuilt. A layer nobody owns is a layer that quietly stops working.
Agency monitoring is scoped by the prompts and sites being tracked. Confirm available assistant coverage, cadence, access and reporting in a walkthrough. Interactive assistant or plugin implementation for client brands is a separate custom service; its platform support, permissions and maintenance are agreed for each project.
The pricing page lists SaaS monitoring scopes for prompt tracking, share of voice and basic AI visibility reporting. Enterprise and agency interactive assistant or plugin builds are custom-priced work outside those subscriptions. Request a scope that states the supported platforms, data access, delivery and maintenance responsibilities.
A prompt is a question your buyers already put to an assistant, and SaaS monitoring reports where your brand stands in sampled answers.A prompt is a question your clients’ buyers already put to an assistant, and SaaS monitoring reports where each client stands in sampled answers.
SaaS monitoring covers prompt tracking, share of voice and basic AI visibility reporting. Confirm available surfaces, cadence and access in a walkthrough. Interactive plugin builds are scoped separately.
Starter
$49/month
For one site finding its feet in AI answers.
Pro
$99/month
For a brand that tracks its category seriously.
Business
$199/month
For teams working across several markets at once.
Agency monitoring
$399/month
For running client programmes under your own name.
Enterprise and agencies
Custom
Interactive assistant and plugin implementation for enterprises and agencies is a separately scoped service, outside SaaS monitoring prices. We build for supported platforms such as ChatGPT and Claude; availability, permissions, integration work and maintenance are agreed for each project. Request a custom quote.
Talk to usLaunch list prices, in US dollars.
