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Advanced Embeddings & Chunking - Production RAG Engineering
Today’s Build
We’re building an advanced embeddings and chunking laboratory that transforms how your VAIA handles document processing:
Multi-model embedding comparison engine testing Sentence Transformers, Gemini embeddings, and lightweight models with real-time performance metrics
Semantic chunking system that preserves meaning boundaries rather than arbitrary character counts
Recursive chunking pipeline with configurable hierarchies for multi-level document understanding
Chunking strategy analyzer providing visual comparison of chunk quality, overlap, and retrieval effectiveness
Building on L20’s ChromaDB foundation, we extend vector storage with intelligent preprocessing that dramatically improves retrieval quality. This creates the optimized document representations that L22’s reranking models will refine further.
