Vector Database Infrastructure — Production Deployment & Scaling

I will build a vector database-powered enterprise knowledge management system — covering multi-source document ingestion (SharePoint, Confluence, Google Drive, and internal wikis), automated re-indexing when source documents update, permission-aware retrieval ensuring users only retrieve content they're authorised to access, and a knowledge search interface serving both human search users and AI assistant retrieval. Enterprise knowledge management powered by vector search delivers significantly better search relevance than keyword-based systems — semantic understanding finds conceptually relevant documents that keyword matching misses, and permission-aware retrieval integrates with your existing access control without requiring separate permission management in the knowledge layer.

The system covers multi-source connector configuration, change detection and re-indexing pipeline, permission metadata integration for access-controlled retrieval, a knowledge search interface, and an AI retrieval API for your AI assistants.