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.
Best for
Teams searching across fragmented internal knowledge
Business impact
Answers grounded in company data
01 · The problem
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.
02 · The solution
What Orkestra built
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.
Key capabilities
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
03 · The results
Business impact
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instead of minutes, and the system stays current through automated document re-ingestion — eliminating the risk of outdated information being shared.
04 · Stack used
The stack supports the workflow, reliability, and future maintenance requirements of the system.
05 · Inside the build
Explore the product, workflow, and operational details behind MiniSport Internal RAG Assistant.
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Start a conversation
One focused conversation about the operation, the friction, and what a useful first release should change.
Direct founder access
No generic sales deck
A clear next step
