Privately query documents via self-hosted RAG connected to MCP

Privately query documents via self-hosted RAG connected to MCP targets a $6.0B = 2M businesses × $3K ACV total addressable market with high saturation and a year-over-year growth rate of 25% YoY — estimated growth for AI knowledge-management and RAG adoption driven by vendor reports and analyst commentary (IDC/Gartner estimates for AI app adoption).

Key trends driving demand: Privacy-first AI — increasing demand for on-prem or self-hosted AI solutions creates an opening for RAG stacks that do not send documents to third-party vector stores.; Protocol standardization — protocols like MCP lower integration friction between LLM controllers and data connectors, making packaged products more feasible.; Open-source model improvements — more capable and efficient open-source embeddings and LLMs reduce running costs and make local inference more practical for smaller teams.; Enterprise interest in verifiable answers — organizations increasingly require sourced/cited answers for legal and compliance reasons, favoring tools that provide citations and audit trails..