The AI Ticket Support System is a full-stack platform that uses artificial intelligence to triage, classify, and respond to customer support tickets automatically. Powered by GPT-4o-mini and a hybrid retrieval-augmented generation (RAG) pipeline, it reduces human agent workload by resolving high-confidence tickets without intervention.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/yocxy2/2a/llms.txt
Use this file to discover all available pages before exploring further.
Quickstart
Get the full stack running locally in under five minutes with Docker Compose.
Architecture
Understand how the backend, database, AI pipeline, and frontend fit together.
API Reference
Explore every REST endpoint — create, list, fetch, and update tickets.
Core Features
Learn how tickets move from submission to AI resolution or human review.
How it works
User submits a ticket
A customer describes their issue in the web UI. The React frontend posts the description to
POST /api/v1/tickets.AI classifies and responds
The backend generates a vector embedding, runs hybrid RAG search against the knowledge base, traverses the GraphRAG entity graph, then asks GPT-4o-mini for a category and response.
Confidence-based routing
Tickets with a confidence score ≥ 0.7 are marked
ai_resolved automatically. Tickets below the threshold are set to pending_agent for human review.Key capabilities
Hybrid RAG
80% vector similarity + 20% recency scoring + importance weighting for precise knowledge retrieval.
GraphRAG
Entity extraction and BFS graph traversal surface related concepts beyond simple keyword matching.
Async Processing
Entity extraction runs in background workers via Redis + BullMQ, keeping the API non-blocking.
You need a valid OpenAI API key and Docker installed before starting. See the Quickstart for step-by-step setup.