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http://purl.org/dc/terms/description <span><p><strong>An example of the benefits of creating ‘data structure’ in the Food and Beverage Industry</strong></p><p><strong>Context</strong></p><ul><li>Food is a domain where <em>meaning</em> is genuinely contested.</li><li>The models you adopt decide: <ul><li>What the data <em>says.</em></li><li>What the business does next.</li></ul></li><li>Alon Chen has spent seven years building the semantic layer that lets AI agents read food and beverage the way the industry actually thinks about them (now running inside Nestlé, PepsiCo and Kraft Heinz).</li></ul><p><strong>Describing, using a single product (frozen broccoli):</strong></p><ul><li>The web of claims, formats, occasions and packaging that an ontology must hold.</li><li>How that structure moves evidence safely through a large enterprise.</li><li>That predicting a trend is the easy part.</li><li>Proving the value of the approach to business decision makers.</li></ul></span> 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