Document Databases

Databases are the heart of our Retrieval-Augmented Generation (RAG) system.

Document Databases store and serve the source materials that knowledge workflows rely on: files, email contents, and structured documents. In this stack, documents are linked to conversations (data rooms) and Insights via short-lived references, enabling retrieval, processing, and indexing while preserving provenance and access controls.

When to use a Document Database

• You need durable storage for artifacts used by Knowledge Bots and Insights.´

• You require provenance linking documents to the conversations and notes that cited them.

• You plan to index content for search/RAG, analytics, or compliance review.

• You integrate enterprise sources (e.g., SharePoint, email) and need a unified handling model.

Typical lifecycle

1. A conversation or connector ingests a file/email into the document store.

2. The system generates a short-lived ref for safe access.

3. Tools process the document (text extraction, splitting, metadata enrichment, embeddings).

4. Insights cite the document via provenance links and store ref values for follow-up processing.

5. Indexers ingest normalized content and metadata into search/RAG systems.