Case study · AI agents
An internal RAG assistant that lets the MiniSport team ask questions across company documentation in natural language. It reduces time spent searching docs and gives staff faster, more consistent answers.
Technology stack
01 — The challenge
MiniSport's support and operations team spent significant time searching through internal documentation to answer questions about products, policies, and procedures — creating slow, inconsistent responses and operational drag.
02 — What I built
I built an internal RAG assistant using n8n and OpenAI that ingests company documents, creates vector embeddings, and allows staff to query any documentation in plain English — returning accurate, context-aware answers in seconds.
03 — The outcome
Internal documentation queries reduced by 60%. Staff now get accurate answers in seconds instead of minutes, and the system stays current through automated document re-ingestion — eliminating the risk of outdated information being shared.
Next project
AI agents · n8n · OpenAI · Vector DB
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