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Learn how to use LangChain with Neo4j to query a multi‑million‑product knowledge graph, extracting counts, brand lists, and active offers from hierarchical categories.
At Fetch, we have a product catalog consisting of millions of products, in extremely granular levels of detail (even more specific than UPCs are!). It can be difficult to easily get summary stats about those products because of the hierarchical structure of the product categories, so I built a knowledge graph on top of the catalog. The cherry on top is a LangChain-driven interface to ask questions like “how many brands do we have in the Red Wine category?” or “what offers are we running right now for snack products?”
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