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Early access — DACH region

Describe your product once. Sell it everywhere.

PIE (Product Information Exchange) is a product-data platform for the food and agriculture industry. Producers manage one structured, regulation-ready catalogue. Buyers read exactly what they have been granted — through an API, a feed, or a file in the shape their system already expects.

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The same product, described five different ways

Most food product data still moves as spreadsheets and PDFs. A producer keeps one version for the webshop, another for the retailer's supplier portal, a third for the wholesaler's import template, a fourth in the specification document sent to a co-packer, and a fifth in the file someone emailed last spring. When a recipe changes, four of them quietly become wrong.

That is expensive in an ordinary week and dangerous in a regulated one. Allergen declarations, nutrition values, country of origin, organic certification and deforestation evidence are not marketing copy — they are statements a food business is answerable for. They should live in one place, be checked automatically, and be readable by every system that needs them.

PIE is that one place. A product is described once, validated against the rules that actually apply to it, and made available to the buyers its owner chooses — no re-typing, no stale export, and nothing shared that was not deliberately granted.

What the platform does

One structured catalogue, checked against real regulation, delivered wherever your buyers are.

One structured catalogue

Define the fields your category actually needs, in every language you sell in. Every change is versioned, so you can always see what a product looked like when a buyer received it.

Compliance checked as you work

Food labelling, organic, deforestation, HACCP, IFS/BRC, health claims and packaging rules are evaluated against your data — per market and per language — so a gap surfaces while you can still fix it.

You choose who sees what

Products are private by default. You grant a specific buyer access to specific products, and you can withdraw it at any time. Every access is logged.

Delivered in the shape they expect

A REST API, signed webhooks, a Shopify listing, a marketplace feed, an SFTP file, a print catalogue or a public brand portal — all projections of the same record.

GS1-ready from the first day

GTIN and GLN validation, a Global Data Model projection and a readiness score are available on every plan, including the free one — so you can see exactly how close you are to retail-grade data before you pay for anything.

Passports and public pages

Publish a Digital Product Passport behind a QR code, or a public brand portal, built from the same catalogue and snapshotted at publish so what a shopper scans never drifts.

How it works

Three steps, and the third one keeps happening on its own.

  1. 01
    Producer

    Build the catalogue once

    Import from a spreadsheet or a supplier document, or create products by hand. Define your own category fields, add images and certificates, and translate the values that need translating.

  2. 02
    Producer

    Check it, then grant it

    Quality scoring shows what is incomplete; compliance validation shows what is wrong. When it is right, grant a buyer access to exactly the products they should see.

  3. 03
    Buyer

    Read it — and keep reading it

    Buyers pull the catalogue through the API, subscribe to a webhook, or receive a file. When the producer changes something, the buyer's copy is already current. Nobody sends a corrected spreadsheet.

What PIE is for

Eight situations we built this for. These are illustrative scenarios, not customer stories — we will publish real ones when we have permission to.

For producers and suppliers

Example scenario

The regional dairy co-op that just got a retail listing

180 products, and the retailer wants published data with complete food-labelling fields — allergens, nutrition per 100 g, net quantity, country of origin — plus images to a specification. Today that is one spreadsheet per retailer, re-keyed every time a recipe changes. In PIE it is one catalogue: compliance validation tells you which of the 180 are missing a mandatory field before the retailer rejects them, the GS1 Global Data Model projection shows your readiness score, and the data pool connector publishes when you are ready. Change the recipe once.

Example scenario

The organic importer selling direct and wholesale at once

24 products, a Shopify store, and four wholesale buyers who each want a different file. The product is described once. Shopify is a channel — publish and the storefront updates. The wholesale buyers get a grant, so they read the live catalogue through the API instead of a file you email. The brand portal and the print catalogue are projections of the same data, so the PDF can never disagree with the webshop.

Example scenario

The processor preparing for the deforestation regulation

Coffee, cocoa, soy, cattle and palm are in scope, and the obligation arrives on a fixed date. What is needed is per-lot geolocation evidence, or a link to it, attached to the product and produceable on demand. PIE validates exactly that, alongside food labelling, organic, HACCP, IFS/BRC, health claims and packaging — so the evidence is a property of the product record rather than a folder someone assembles under deadline.

Example scenario

The producer whose buyers are not in a data pool

A regional wholesaler, a foodservice distributor, an organic specialist chain, a marketplace, an export buyer. None of them subscribes to a GDSN data pool; all of them want current, structured, allergen-complete data. Today they get a spreadsheet by email, someone re-keys it, and it goes stale the moment a recipe changes. PIE serves them directly — a grant, an API feed, a webhook, a file drop or a channel publish — using the same record, structured to the GS1 Global Data Model. Nothing is wasted if a retail listing arrives later: the data is already in the shape a data pool asks for, so publishing becomes a connector rather than a project.

Example scenario

The co-packer and the ingredient buyer

A processor buying a base cheese, a co-packer filling for three brands, a co-operative aggregating twelve member farms. What moves between them is the product specification — ingredients, allergens, nutrition, shelf life, packaging, origin, microbiological limits. It is the central document in food B2B and there is no standard for it: it travels as a PDF or a spreadsheet and every recipient rebuilds it by hand. PIE treats the specification as structured data, with the same validation, versioning and per-language handling as a retail product, and lets the buying party read it directly instead of asking for it again.

For buyers

Example scenario

The distributor onboarding forty suppliers

Each supplier gets a scoped link. They fill in what you asked for, in their own language, with their own column names — your field mapping translates it. A quality profile you author decides what “complete enough” means, and a submission that fails it never reaches your catalogue. No logins to provision, no spreadsheets to reconcile, no supplier waiting on your IT team.

Example scenario

The restaurant group that needs allergen data it can defend

Fourteen allergens, several hundred bought-in items, and a legal obligation to be right. Grant-scoped access means you see your suppliers' current data, not last quarter's export. A webhook fires when a supplier changes a recipe, so your menu system learns about it the same day rather than at the next audit.

Example scenario

The retailer pulling a supplier feed straight into ERP

A documented REST API, cursor pagination, a stable error contract, signed webhooks, and API keys your team manages itself. Data arrives structured and per-language, so the German and French descriptions land in the right fields without a transformation script only one person understands.

Start with twenty products, free

No card, no sales call. Build a real catalogue, check it against real regulation, and see your GS1 readiness score before you decide anything.

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