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Overview
A comprehensive AI-driven support agent designed to reduce support ticket volume. It automatically reads client documentation, performs search queries against database resources, and addresses user concerns in real-time.
Technologies Used
Next.jsOpenAITailwindSupabase
The Challenge_
Handling unstructured user queries while preventing LLM hallucinations and keeping API costs low.
The Solution_
Implemented Retrieval-Augmented Generation (RAG) using Supabase pgvector to source matching context blocks, combined with prompt structuring to strictly limit model outputs to verified data.
System Architecture
1
User submits support query in chat UI
2
Query converted into embeddings and compared against pgvector documents
3
Relevant context injected into LLM prompt template
4
Response synthesized and returned to client in real-time