AI-powered document chunking pipeline for RAG systems with quality guardrails
Solves document preprocessing for RAG by structuring unstructured text into semantic chunks with dynamic sizing and real-time quality checks. Uses LangGraph for workflow automation and gpt-5.4-nano for cost-effective parsing. Targets enterprises needing reliable RAG data pipelines.
View on GitHub →kdwmeet/document-chunking-pipeline