Onboard supplier products faster, with less back and forth

Suppliers submit product data in their own format. AI maps it to your schema, normalizes it to your standards, and checks it against your benchmark before it reaches your catalog. Your team reviews and approves in bulk.
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You work with a long list of suppliers, and each one sends product data in its own format, with its own field names, its own color and size conventions, and its own idea of what counts as complete. The gaps get filled by hand and the rest gets chased over email, while products sit in a backlog and the season moves on.

But clean data is not a finished listing. It still needs descriptions, complete attributes, and images before a product can go on sale.

One portal, from raw supplier data to catalog-ready

A portal for supplier onboarding

Suppliers submit their own products in the format they already use, or your merchandising team onboards on their behalf. Suppliers work in their own space and never touch your live catalog.

AI mapping and normalization

AI matches supplier fields to your schema, standardizes values to your conventions, groups sizes and colors into the right product variants, and categorizes everything into your taxonomy. Your team keeps override control on every value.

Completion and quality checks

Every product is scored against your standards before it reaches your catalog, including whether its images and data agree. Whatever falls short is flagged with the reason, and the supplier fixes it in the portal.

Get sellable listings, not just clean data

The portal runs on the same platform that enriches data and writes product content, so submissions move from intake to finished listing without leaving Hypotenuse.

The same submission becomes a finished listing: descriptions in your brand voice, filled-in attributes, and images edited to your channel specs.

Supplier images are matched to the right products automatically as they are uploaded.

Onboard suppliers faster

Suppliers submit in the format they already use, without reformatting their data to match your system first.

Mapping, normalization, and categorization run automatically as products arrive.

Products that clear your thresholds publish automatically, so your team only reviews the exceptions.

Control what reaches your catalog

Suppliers submit; your team decides what goes live.

AI-suggested values come with confidence scores. Anything below your threshold is flagged for review, and every suggestion stays editable.

An audit trail traces every value back to the input it came from, including vendor data.

Use cases of our AI supplier data management

Rivenditori

Onboarding products from a long list of brands and vendors across categories, each arriving in a different format.

Distributors

Technical, spec-heavy catalogs from many manufacturers, where accuracy and completeness carry real cost.

Brands

Managing inbound product data from suppliers and manufacturers before it goes out to every channel.

Marketplaces

Onboarding product data from a large network of third-party sellers into one consistent catalog.

Frequently asked questions about AI supplier data management

Do we need a PIM as well?

The portal is the onboarding layer of Hypotenuse, which is itself a full AI-first PIM, so you do not need a separate one. If you already have a PIM you want to keep, the portal onboards and enriches the data that feeds it.

What formats can suppliers submit?

Suppliers submit in the format they already use. AI agents map it to your schema, so they are not asked to rebuild their data to your template before they can send it.

Do suppliers need training?

Only light familiarization. The portal is intuitive, so suppliers learn it quickly and start submitting without intensive training. They upload their files, and are notified when something fails a check so they can fix it and resubmit.

How do we stay in control of what vendors send us?

Vendors submit, they do not publish. Every product is scored against your standards, anything that falls short is flagged with the reason, and your team approves what moves forward. AI-suggested values are clearly marked and remain editable before publishing.

Is our data secure?

Hypotenuse is SOC 2 Type II certified, and your data is not used to train models for anyone else. Access is controlled by role across your teams, your vendors, and your agencies, and the bespoke AI model trained for your brand is not shared with any other customer.

Can it handle a lot of suppliers at once?

Yes. The platform is built for bulk operations rather than per-product editing. Products are scored as they arrive and your team approves in bulk, so adding suppliers does not add proportional review work.

What happens after a product is approved?

It flows into the workflows you choose: enrichment fills what is missing, content is generated to your brand guidelines, images are edited to your standards, and it publishes to your channels. You decide which steps each product goes through.

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Onboard suppliers and get sellable listings, faster

Every supplier file comes back enriched, structured, and channel-ready, not just clean.