Tuesday, July 14, 2026
ProChunk Strategy Optimizer
A CLI and Python library that analyzes a document corpus to automatically determine the ideal chunk size, overlap, and embedding strategy per document type (contracts, codebases, narrative), reducing hallucinations without the manual trial-and-error tuning that teams currently endure.
Target Audience
ML engineers and full-stack developers building internal knowledge-base Q&A systems who spend days tweaking chunk parameters because 'bigger context windows didn't make RAG smarter,' as they saw firsthand.
Why Now
Dev.to's 'Bigger Context Windows Didn't Make Our RAG Smarter' pinpoints the failure of the naive approach, while the large number of teams adopting RAG post-LLM boom lack systematic tuning tools. Existing solutions are either overly manual or embedded in expensive vector DB platforms.
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