Embeddings, Chunking, and Retrieval Design

Retrieval Quality Starts Before Search

Embeddings and chunking determine what the system can retrieve. Poor chunk boundaries, missing metadata, stale indexes, and weak evaluation can make even a strong model produce weak answers.

Retrieval Design Decisions

• Choose chunk size based on document structure and user questions.
• Use overlap carefully to preserve context without bloating retrieval.
• Attach metadata for source, date, owner, permissions, version, topic, and document type.
• Use filters to respect tenancy, access rules, freshness, and workflow scope.
• Evaluate retrieval with known questions and expected supporting sources.

Chunk for Meaning, Not Just Tokens

Semantic boundaries often matter more than fixed token counts. Headings, sections, tables, code blocks, and policy clauses may need different chunking strategies.