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Analyses

Le Journal.

Des écrits sur les données du vin, les systèmes sur lesquels repose le négoce, et les limites du logiciel générique. Pas d'articles de tendance.

AI4 min read

Why does AI struggle with wine data specifically, compared to other product categories?

A wine is producer, vintage, appellation, classification, format and provenance combined. Most AI systems assume a far flatter product model.

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AI4 min read

How is AI for wine catalogs and pricing different from AI in winemaking or the vineyard?

Production AI reads sensor data in the cellar and vineyard. Commercial AI works on catalog, pricing and inventory data. Different problems, different tools.

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AI4 min read

What should a wine business look for in an AI tool before buying one?

Four checks: structured data grounding, uncertainty flagging, a built in human review step, and real understanding of appellation, vintage and provenance.

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AI4 min read

Is AI content accurate for wine descriptions, or does it make things up?

Ungrounded models invent appellations and vintages. AI generated against a structured wine record, with a review step, is materially more accurate.

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Données8 min de lecture

Pourquoi les données du vin mettent en échec les logiciels génériques

Producteur, millésime, appellation, format, provenance. Cinq champs que les modèles produit génériques réduisent à un seul — et ce que cela coûte en aval.

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AI4 min read

What can AI actually automate in a wine business today?

Catalog data enrichment, multilingual content generation and pricing anomaly detection are reliable today. Final pricing calls and relationship judgment are not.

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AI4 min read

Does AI actually work for wine businesses, or is it still marketing hype?

AI works today for narrow, data grounded tasks: content generation, catalog enrichment and pricing anomaly detection. It does not replace human judgment.

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Infrastructure7 min read

What a modern wine tech stack looks like in 2026

One source of truth, bottle level tracking, AI as a working layer, continuous pricing and integration by default. An architecture, not a product.

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Commerce6 min read

Multilingual wine ecommerce: DE and FR and EN done right

Register, terminology consistency and market specific search behaviour are what separate real localization from machine translation.

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Connect6 min read

API-first vs monolithic wine platforms: why it matters for merchants

Closed all in one platforms ask you to migrate. API-first systems connect to the ERP, CRM and accounting tools you already run.

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Connect5 min read

Wine CRM vs generic CRM: the missing fields

Holdings, allocation tier and drinking window are the fields a generic CRM has no place for, and the reason outreach reads as generic.

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AI5 min read

AI product descriptions for wine catalogs: what actually works

Generating catalog copy against structured wine data, flagging what cannot be grounded, and keeping a human review step in the loop.

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Commerce6 min read

Building an allocation system for en primeur

En primeur sells entitlement before stock exists. What an allocation system needs that a standard shopping cart does not have.

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Infrastructure5 min read

Bonded warehouse integration: what to ask vendors

Bond status, documentation, VAT at the point of release and multi warehouse visibility. The questions to ask before you commit to a system.

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Pricing6 min read

Wine pricing software for fine wine merchants: what to look for

The questions that separate pricing tools built for fine wine from distribution markup tools and generic ecommerce pricing software.

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Infrastructure5 min read

What provenance data actually means for a wine business

Provenance is a documented chain of custody for a specific bottle, not a marketing story, and it is part of what a buyer pays for.

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Infrastructure5 min read

How wine inventory software differs from generic retail inventory

Generic inventory counts SKUs and units. Wine needs bottle level records, because provenance and condition change what a single bottle is worth.

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