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How LLM agents solve the table merging problem
Traditional fuzzy matching fails when joining tables with typos, missing columns, or dynamic data. I show how combining string similarity, LLM reasoning, and web search achieves near 100% accuracy at a reasonable cost, and share the results in the everyrow sdk.
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