Can you control what ChatGPT says about my brand?

No — and anyone who says they can is selling you something they can't deliver. What we can do is make sure a verified, machine-readable version of your information exists where these systems look, in the format they expect. You can't force the answer; you can make sure your truth is the best-sourced material available when the answer gets assembled.

How is this different from SEO?

SEO optimizes for a results page a person reads; this prepares your information for systems that assemble an answer and never show the sources. Both matter, and they're not the same discipline — a page that ranks well can still be unusable to a machine trying to verify a claim about you.

Do I need the rest of NSOLVIA for this to work?

No, but it compounds. This works on its own, and it works better on an enriched catalog — the same structured product data that powers feeds and the assistant is what makes products and collections verifiable rather than merely present.

How would I know it's working?

By checking the same way you'd check any claim about your brand: ask the assistants what you sell, what your policies are, which collection fits an occasion — before and after. What we can measure directly is whether your verified record exists, is complete and is published where these systems look. What any given assistant says on any given day is not ours to promise, and we don't.

When is it available?

Now. Start with the free Agentic Catalog Readiness Audit™ — it shows how your brand and catalog read to a machine today. Activation is a one-time setup sized to your catalog, with optional Care to keep the four surfaces current as your catalog changes.

AI Commerce Discoverability™

One verified source of truth. Four discovery surfaces.

Your store, readable by every AI assistant and search engine.

Four surfaces, one source. Brand, Products, Collections and Agent Discovery (agents.md, llms.txt, llms-full.txt) are published on your own store.
What shoppers see is what machines read. Every fact appears on the page and in structured data, both coming from the same verified record, so nothing is hidden or contradicts itself.
Answers before they’re asked. Returns, shipping, materials, fit and Q&A are laid out so AI assistants can quote your store instead of guessing.
Your design stays yours. No changes to your layout, prices or checkout.
Zero-risk launch. We install on a copy of your theme. You preview it and publish with one click, and you can undo with one click.
Proof included. You get a before/after reading of every surface, layer by layer, on the day we start and the day we deliver.

Setup: the same private app as the Optimizer (if you already have one, there’s nothing new to do). You complete your return policy and press Publish. That’s it.

Agentic Catalog Readiness Audit™ — Surfaces

pontebellastore.com · Audited October 15, 2026

Surface — before / after

What an AI agent finds on your public storefront, read without cookies. Before column reconstructed from archived readings.

Layer	Before	After
Product page: product schema	✓	✓
Product page: FAQ schema	✗	✓
Product page: visible semantic block	✗	✓
Collection page: collection schema	✗	✓
Collection page: FAQ schema	✗	✓
Home: store schema	✓	✓
Home: valid return policy	✗	✓
Home: visible brand block	✓	✓
agents.md	Shopify default	Written for your brand
llms.txt	Shopify default	Written for your brand
llms-full.txt	Shopify default	Written for your brand
Agentic checkout endpoint (UCP)	✓	✓
Product feed responds	✓	✓

Before: 5 of 13 layers in place · Today: 13 of 13.

Open full report →

AI Commerce Discoverability™

One verified source of truth. Four discovery surfaces.

When someone asks an AI system about your brand, your products or your collections, the answer comes from somewhere. This makes sure it comes from you.

Start with a free audit See pricing

AI systems already describe your brand. Nobody checked with you.

Ask an assistant what a brand sells, whether it's legitimate, what its return policy is, or which of its collections fits an occasion — and it answers. It assembles that answer from whatever it found: an old page, a marketplace listing, a review, a competitor's comparison.

Some of it is right. Some of it is outdated. Some of it was never true. And unlike a search result, the shopper doesn't see the source — just the answer.

The fix is to publish the truth in a form machines can verify and reuse, across every surface where they look.

Built for brands that AI systems already talk about.

Brands whose name, claims or policies get described inaccurately by AI assistants
Merchants whose products are discovered through assistants, not just search
Businesses with collections, categories or seasonal edits worth surfacing correctly
Teams that want one verified source of truth instead of scattered pages

Four surfaces, one truth: Brand · Products · Collections · Agent Discovery.

What we need from you.

1.Your site and catalog.
2.The facts you want to be the record: what you sell, who you are, your policies, your claims.
3.Approval before anything is published as verified.

What it does — four surfaces.

Brand — establishes who you are in a form machines can verify and cite: what you sell, where you operate, what you stand behind.

Products — makes individual products discoverable and interpretable, grounded in verified attributes.

Collections — makes groupings discoverable the way people actually ask for them: by occasion, constraint or need, not just by category name.

Agent Discovery — publishes your information where AI agents look for it, in the formats they expect, so the answer they assemble starts from your source.

Rule we don't break: Verified, never invented. What gets published as truth is what you approved.

What you get.

A verified, machine-readable record of your brand
Products and collections discoverable in terms of how people ask
Your information published where AI agents look for it
One source of truth, reused across all four surfaces

Three steps.

Step 1 — Measure

A free audit shows how your brand and catalog currently read to a machine.

Step 2 — Establish

The verified record is built from what you approve.

Step 3 — Publish

It goes where machines look, in the formats they expect.

The same question, two answers.

Question: “is this brand legitimate, and what do they sell?”
Without: an answer assembled from whatever was found — partly outdated, partly wrong
With: an answer grounded in a verified record you approved

What we claim: a verified, machine-readable source of truth published where AI systems look.

What we don't claim: we don't control what any AI system ultimately says. No one can. What we control is whether your version exists, verified, where they look for it.

Live example

See it on a real store: PonteBella.

What an AI reads

An excerpt of PonteBella's llms.txt, exactly as published — written for the brand instead of the platform default.

# PonteBella

> PonteBella was founded in 2003 by Colombian doctors with a conviction: shapewear should be designed for real bodies.

## Collections
- [Butt Lifter](https://pontebellastore.com/collections/butt-lifter): 4 products, mostly shapewear, for under dress, everyday and postpartum.
- [Post Surgery](https://pontebellastore.com/collections/post-surgery): 9 products, mostly shapewear, for everyday, postpartum and under dress.
…

## Policies
- Returns: accepted within 30 days (store credit only).
- Shipping: free on orders over $40.
…

Questions & answers

What brands ask.

Can you control what ChatGPT says about my brand?: No — and anyone who says they can is selling you something they can't deliver. What we can do is make sure a verified, machine-readable version of your information exists where these systems look, in the format they expect. You can't force the answer; you can make sure your truth is the best-sourced material available when the answer gets assembled.
How is this different from SEO?: SEO optimizes for a results page a person reads; this prepares your information for systems that assemble an answer and never show the sources. Both matter, and they're not the same discipline — a page that ranks well can still be unusable to a machine trying to verify a claim about you.
What are the four surfaces?: Brand, Products, Collections and Agent Discovery. Brand establishes who you are; Products makes individual items interpretable; Collections makes groupings discoverable the way people actually ask; Agent Discovery publishes it all where AI agents look. One verified source of truth, reused across all four.
Do I need the rest of NSOLVIA for this to work?: No, but it compounds. This works on its own, and it works better on an enriched catalog — the same structured product data that powers feeds and the assistant is what makes products and collections verifiable rather than merely present.
How would I know it's working?: By checking the same way you'd check any claim about your brand: ask the assistants what you sell, what your policies are, which collection fits an occasion — before and after. What we can measure directly is whether your verified record exists, is complete and is published where these systems look. What any given assistant says on any given day is not ours to promise, and we don't.
When is it available?: Now. Start with the free Agentic Catalog Readiness Audit™ — it shows how your brand and catalog read to a machine today. Activation is a one-time setup sized to your catalog, with optional Care to keep the four surfaces current as your catalog changes.

Be the source of the answer.

Start with a free audit See pricing

Where this sits

Part ofthe Semantic Commerce Layer™NSOLVIA's framework for practising IEO on commerce data — the interpretability layer between catalogs and the systems that read them.
Goes deeper
- NSOLVIA AI Commerce Transformation Program™ — The programme that turns a brand's verified facts into a living source of truth across every destination.
Alongside it
- the free catalog readiness audit — The free instrument: reads a real product the way machine systems do and reports its interpretability baseline.
- the Agentic Catalog Optimizer™ for Shopify — Writes your verified product data into Shopify's native category attributes.
- AI-Ready Commerce Feeds™ — Enrich the catalog once and deliver it in the format each destination expects.

AI Commerce Discoverability™ sits inside NSOLVIA's interpretability stack — an open discipline, the framework that implements it, and the instruments that apply it.