The catalog you always meant to have. Delivered as a file you own.
Every product resolved, enriched and machine-readable — the dataset your PIM, your search index or your integrator was going to have to build by hand. Yours to keep, with no subscription attached.
Powered by the Semantic Commerce Engine — part of the Semantic Commerce Layer™
What one product looks like — resolved and machine-readable.
A real product from a delivered catalog — a home fragrance brand, name and brand withheld. Every value traces to the store’s own published evidence.
One record per product — resolved category, structured attributes, a machine-readable description. What the catalog doesn’t support stays empty. Verified, never invented.
Some teams don't want a pipe. They want the asset.
Feeds are perfect when a destination pulls from you on a schedule. But some businesses need the data itself: to load into a PIM, to power an internal search index, to hand to a systems integrator, or to keep as a permanent record of what their catalog looked like when it was finally complete.
Rebuilding that dataset in-house means resolving categories, extracting attributes and writing machine-readable descriptions for every product — the work, not the export.
Built for teams that own their data stack.
- Merchants and brands with a PIM, ERP or internal search to feed
- Systems integrators and agencies delivering a catalog to a client's stack
- Teams that need a one-time enrichment rather than a live subscription
- Businesses that want the enriched dataset as an asset they keep
Not a fit if you want destinations to stay current automatically — that's AI-Ready Commerce Feeds™.
What we need from you.
- 1.Your store or catalog source.
- 2.Read access, only if your platform requires it.
- 3.The delivery format your stack expects.
How we handle your data
- Read-only relationship with your store — we don't write to your catalog
- Credentials encrypted, never logged, revocable at any time
- The delivered dataset is yours to keep, with no dependency on us to use it
What the enrichment does.
Reads your published catalog, including content that lives in tabs, accordions or apps.
Resolves what each product is — category, product type, and the attributes that matter for that category.
Extracts machine-readable evidence from your own published information: material, capacity, compatibility, fit, use case.
Packages the result as a structured dataset in the format your systems expect.
Rule we don't break: Verified, never invented. No evidence, no value — the field stays empty.
What you get.
- The complete enriched dataset of your catalog
- Resolved category and product type per product
- Structured attributes and machine-readable descriptions
- Delivered in the format your stack expects
- Optional sync, if you want the asset refreshed over time
It's a deliverable, not a dependency. You can use it with or without us.
Three steps.
Catalog size, source and target format.
Your catalog is resolved and enriched from your own evidence.
The dataset lands in your stack, in your format.
From published pages to a structured asset.
- Before
- product pages written for people; attributes scattered across tabs and prose
- After
- one structured record per product — category, attributes, machine-readable description
What we claim: a complete, structured, machine-readable version of your catalog, delivered.
What we don't claim: we don't promise what your downstream systems do with it.
What teams ask.
- Why buy an export instead of a feed?
- Because you want the dataset itself, not a live pipe. A feed keeps a destination current on our infrastructure; an export hands you the enriched catalog to load into your own systems — a PIM, a search index, a client's stack — and keep as an asset that doesn't depend on a subscription.
- What exactly is in the delivered dataset?
- One structured record per product: resolved category and product type, the attributes that matter for that category, and a machine-readable description built from your published evidence. It's your catalog, completed — not a re-formatted copy of what you already had.
- Where does the enriched information come from?
- From your own published product information — titles, descriptions, specs, variants, materials, warnings. If a fact isn't supported by evidence in your catalog, the field stays empty rather than being invented, and warnings are preserved word for word.
- Do you write anything to my store?
- No. This product reads your catalog and delivers a dataset to you. Writing into a store is a different product (the Optimizer, for Shopify), and it only happens with permissions you grant explicitly.
- What format does it come in?
- The one your stack expects — we agree it before we start, rather than handing you a format you then have to convert. What stays constant is the structure: one record per product, with resolved category, structured attributes and a machine-readable description.
- How large a catalog can you handle, and how long does it take?
- Catalog size and timeline are scoped before we start, which is why this is a conversation and not a checkout. What we can say up front: the work is one enrichment pass, not a per-product project, so size affects the timeline far less than the state of your source content does.
- Can I get it refreshed later?
- Yes — an optional sync keeps the asset current as your catalog changes. Without it, the export is a snapshot of your catalog at delivery, which is exactly what some teams want.
Get your catalog as an asset you own.
Where this sits
- Part ofNSOLVIA's Semantic Commerce Layer™NSOLVIA's framework for practising IEO on commerce data — the interpretability layer between catalogs and the systems that read them.
- Alongside it
- the Agentic Catalog Readiness Audit™ — The free instrument: reads a real product the way machine systems do and reports its interpretability baseline.
- the 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.
Catalog Export™sits inside NSOLVIA's interpretability stack — an open discipline, the framework that implements it, and the instruments that apply it.