MiniSport Internal RAG Assistant
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.
n8n
OpenAI APIThe challenge
Client 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.
The build
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.
- Automated document ingestion and re-indexing pipeline
- Vector database for semantic document search
- Conversational query interface for the full team
- n8n orchestration with webhook-based triggers
- OpenAI-powered natural language response generation
The outcome
Measured outcomes
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instead of minutes, and the system stays current through automated document re-ingestion — eliminating the risk of outdated information being shared.
Inside the build
See the system, not just the summary.
Primary workflow view
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