Precigeon

There is no page two in a ChatGPT answer. A store is either in it, or it doesn't exist.

B2B SaaS · Web2026 · ongoingProduct & design, end to endMVP live · 10-store pilot
The live Precigeon landing: 'Be the answer when customers talk to AI. Be visible.' A ChatGPT window naming three running shoes, and one row for your store: not found

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ProductPrecigeon

AI visibility for Shopify stores. Paste a store URL and Precigeon asks the four big assistants the questions customers actually ask, then shows where the store stands, receipt by receipt, and what to fix first.

Details
Product & design, end to endrole
Side project · small founding teamteam
2026 · landing → MVP → live pilot, ongoingtimeline
Web app · ChatGPT, Gemini, Claude & Perplexityplatform
ProblemThe Blind Spot

Shopping advice is moving into chat windows, and merchants can't see any of it. An AI answer names three to five brands. No ranking to climb, no console to check. Every owner I interviewed watched Google daily; none had ever seen an AI answer about their store.

SolutionValue Before Permission

A free scan with zero setup: paste a URL, install nothing. Fifteen minutes later there's a real report: linked, mentioned or missing, with the actual answers behind every number.

ResultAn Open File

The MVP is live at precigeon.com and ten Shopify store owners are running it on real catalogues right now. The only file here still being written while it happens.

Impact
10
Shopify Stores
In the Live Pilot
Real catalogues, real answers, recruited with one question
4
AI Engines
Queried Live
ChatGPT, Gemini, Claude and Perplexity, asked the questions customers actually ask
~15
Minutes To
First Report
From pasted URL to receipts, nothing installed, nothing granted
The Problem

Ask ChatGPT for the best running shoes under $150. It names three. It may not name you.

The public numbers sketch the shift: roughly a third of shoppers already research products with AI tools, and an AI answer names three to five brands, not a results page. What the numbers don't say is whether merchants can see any of it. So I asked:

  • Every store owner I interviewed was watching their Google rankings daily, and not one had ever checked what an AI says about their products
  • Not because they didn't care. There was no way to check, because the tooling for merchants simply doesn't exist yet
  • The surface is winner-take-most: three to five seats per answer, and no page two to climb back from
a customer asks the answer names three there is no page two your seat, empty

The whole problem in one window: an AI answer has a handful of seats and no page two. You hold one, or you don't exist.

"Honestly, no idea if I show up at all. I know my Google position for twenty keywords. For the AI stuff I'm blind."

The Wedge

A no-name side project can't open with an install prompt. The wedge gives value before it asks for anything.

The spine is the free scan: paste a URL, get a real answer in about fifteen minutes, install nothing, grant nothing. It runs live queries against the four assistants, asking the same questions a customer would ask, and shows where the store is linked, where it's only mentioned, and where it doesn't exist.

The scan isn't a teaser, it's the proof, and the report has to hurt a little. Competitors named in an answer where your store is missing does more selling than any feature list. What's held back is the ongoing part: monitoring, rewrites, tracking.

paste a store URL four engines, asked live three honest states a report in ~15 minutes

The wedge, drawn: nothing installed, nothing granted. Live questions in, receipts out, about fifteen minutes end to end.

How does a merchant meet the product?

Shopify app, installed from the store

An install and permissions before any value, from a brand nobody knows. Dead top of funnel.

Manual audits, sold as a service

Proves the value but scales like an agency, which is to say it doesn't.

Zero-setup scan from a public URL

Paste a URL, wait fifteen minutes, see the truth. The report becomes the sales pitch.

Why: everything a scan needs is public: the catalogue, the descriptions, the answers the AIs give. Asking for nothing removes the excuse to bounce. The app install can come later, where it unlocks something real: one-click fixes need write access, seeing the truth doesn't.

The System

One rule set the whole design system: no number without the receipt behind it.

The report is the product, so the design work went into making a strange new metric feel concrete instead of mystical. The score breaks down per engine, each engine per product, and every product opens into the actual prompts and answers it appeared in, or missed.

Visibility gets three states, linked, mentioned and not found, because being talked about and being bought from are different things. One green, spent on exactly one meaning: found. Amber for mentioned. Red reserved for the empty seat where the store should be.

The live report header: 83 out of 100, then four per-engine bars: ChatGPT 90, Perplexity 75, Claude 60, Gemini 95
The live report: one score, then the argument for it: per-engine bars first, receipts one click deeper.

What does the score actually claim?

One global score, keep it simple

A single number hides exactly the thing a merchant needs: where they lose.

Raw answer transcripts, no score

Honest but unreadable. Nobody diffs transcripts every week.

Per-engine scores that unfold into receipts

The number covers the Monday glance; the prompts and answers behind it cover the doubt.

Why: a score gets glanced at, receipts get believed. When the number drops you can open the exact prompt and answer that moved it, so the tool never asks to be trusted on faith. AI answers also shift on their own, and a score you can interrogate survives that better than one you can't.

Design 1 / 5

The Landing That Earns a URL

live at precigeon.com, the whole funnel is one field

Paste your store URL. Everything on the page exists to make that one action feel safe (no install, no permissions, no card) next to a ChatGPT window with the one seat your store isn't in. The landing and the scan are live; they're the wedge doing its job today.

The live scan section: 'Fifteen minutes. Zero setup.' Enter your store URL, we scan 4 AI engines, get your visibility report
The live promise, in the product's own words: fifteen minutes, zero setup, a URL in and a report out.
Design 2 / 5

Overview, the Monday Glance

everything you need at one place

One score, then the argument for it: per-engine bars, the trend since last week, the alert when something drops, and a do-next list sorted by leverage. Built for a thirty-second Monday check, not a data dive.

The Precigeon overview dashboard: visibility score 83, four engine cards, an eight-week trend and a do-next list
Design 3 / 5

The Product Matrix

the screen that hurts and helps

Products down, engines across, three states in the cells: exactly which products are invisible, and where. Sorted by not-found, it stops being a chart and reads as a to-do list, with the fix one click to the right.

The product × engine matrix: twelve products against four engines, cells reading linked, mention or not found
Design 4 / 5

Rewrite, With Receipts

engines match specifics, not vibes

The fix half. The rewrite sits next to what's live now, with the reason it should work spelled out: engines quote material, process and use case, so the rewrite adds exactly that, phrased the way buyers ask. One click pushes to Shopify, and nothing publishes silently: you review, it ships.

The rewrite screen: the live description next to the proposed rewrite with specifics highlighted, receipts underneath, push to Shopify below
Design 5 / 5

The Tracker

the screen that turns an audit into a habit

Prompts and competitors, week over week: your position per engine per query, and who holds the seat you want. This is the screen the platform bets on, the one that turns a one-off audit into a Monday ritual, and the pilot's job is to prove that turn happens.

The prompt tracker: tracked prompts with per-engine positions and empty seats, next to a competitor radar
The competitor radar: allbirds.com at 34%, nike.com at 27%, you at 12% and climbing
A tracked prompt row: 'best wool running shoes' holding #1 on ChatGPT with a rising twelve-week line
A tracked prompt row for 'waterproof wool sneakers', one engine seat reads SEAT EMPTY
The Pilot

The MVP is the wedge end to end, live at precigeon.com, ten real stores scanning right now.

Recruiting ten store owners was its own small validation: the pitch that worked wasn't a feature list, it was one question. The pilot they joined is built to answer three things:

Do merchants read the report, or glance at the score and move on? The receipts exist for the doubters; the pilot shows if doubters open them.

Does anyone apply a fix? The rewrite is one click, but one click is still a decision made on a new kind of number.

Do the answers move, within weeks, not quarters. The loop the whole platform bets on. Moved answers land in this file first, when they're real.

"Do you know what ChatGPT says about your store?"

Reflections

01

Sell with receipts, not adjectives

The report has to hurt a little. Competitors named in an answer where your store is missing did more selling than any feature list, and every number that could be doubted opens into the prompt and answer behind it.

02

Ask for nothing before you give something

Everything the scan needs is public: the catalogue, the descriptions, the answers. Zero setup removed every excuse to bounce, and made a no-name side project worth fifteen minutes of a stranger's trust.

03

A score you can interrogate survives volatility

AI answers shift under your feet, so a visibility score has to be read like weather, not geology. A number that unfolds into receipts survives that. A black-box number wouldn't.

What Ships Next

Ten stores can see it now. Proving a fix is what moved it comes next.

Cause, not just movement: the tracker shows a seat changing hands. It can't yet say your rewrite is why. Answers drift on their own, which the score is built to admit, so the next thing has to hold a prompt steady around a change and read the before and after as one story instead of two.

Every store, not just Shopify: the scan only ever needed a public URL, so the half that tells the truth already works anywhere. It's the half that ships the fix that is Shopify-shaped. Splitting those apart is what turns a Shopify tool into an AI visibility tool.

The answer that moved: the one number that would prove the whole thesis, and the one I don't have yet. A merchant ships a fix, the engines re-answer, the seat changes hands. It goes in this file the week it happens, and not a week before.

Ten store owners can now see a thing that was invisible a month ago. The file stays open, and the next entry is an answer that moved.