Document Indexing
Processing and storing documents so they can be searched and retrieved later. When you build an AI that can answer questions about your internal documents, the indexing step is where you read all those documents, split them up, convert them to a searchable format, and store them. It's the setup phase. Every time a user asks a question, the system searches the index to find the relevant pieces before Claude generates an answer.
In practice
Before Claude can search your 10,000-document knowledge base, each document needs to be processed and stored in a way that makes retrieval fast. Document indexing is that setup step — breaking documents into chunks, converting them to embeddings, and storing them in a vector database. You do it once upfront so every future search is instant.
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