Use Case
Ship a RAG system with zero infrastructure
Connect your data sources as MCP servers. Arlet handles retrieval, execution, and scaling — AI answers from your primary sources.
The challenge
Company knowledge is scattered across docs, databases, and SaaS, and AI can't reference it accurately.
Standing up a RAG stack means running vector databases, embeddings, and retrieval pipelines — heavy to operate.
Handing confidential data to external AI raises access-control and audit concerns.
How Arlet solves it
Connect data sources as MCP
Link Google Drive, Notion, internal databases, and SaaS as MCP servers — reusing your existing authentication.
Arlet hosts and runs it
Retrieval logic runs in isolated sandboxes. Vector search and scaling are handled by the platform.
AI answers with sources
Clients like Claude and ChatGPT fetch primary sources over MCP and answer with citations.
Why Arlet
Zero infra to operate
No vector DB or pipeline to build and monitor. Focus on connecting your data.
Grounded and fresh
Retrieval always hits your latest internal data, and every answer is traceable to its source.
Governance built in
Audit who accessed which data, with fine-grained access control.