Hook
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autoretrieval is the autonomous AI agent that optimizes document search pipelines without human intervention. Most retrieval systems are static and brittle, requiring manual tuning to work well with your specific data. This tool changes that by letting an AI agent experiment on its own. You point it at your documents, and it iteratively tweaks chunk sizes, embedding models, and keyword filters. The agent runs evaluations, checks if accuracy improved and keeps only the successful changes. It repeats this loop overnight working up to a significantly better search setup. You get a tailored retrieval system that actually works for your content, built through trial and error rather than guess work.