Chunking is the necessary process of breaking down long documents or large datasets into smaller, manageable pieces (or “chunks”) so that an AI can process them effectively. This step is crucial for modern AI architectures like RAG, as it ensures that the model can focus on precise, context-rich segments of information.
Spiral Scout applies chunking to enable agents to efficiently analyze massive knowledge bases without suffering from context overflow.
