# Retrieval-Augmented Generation (RAG) Architecture
Generic AI models hallucinate pricing and details. RAG connects LLMs to your exact business documents and PostgreSQL vector database.
## How RAG Works:
1. **Document Embeddings**: Convert PDF files and website text into mathematical vector embeddings.
2. **Similarity Search**: When a customer asks a question, retrieve the top 3 relevant text chunks in 15ms.
3. **Grounded AI Response**: OpenAI generates an answer strictly constrained by your retrieved text.
Artificial Intelligence
Retrieval-Augmented Generation (RAG): Powering Contextual Business AI
How Vector Databases (pgvector, Pinecone) allow AI Agents to answer complex questions using proprietary company data.
Lalit Kumar
Author
Jul 26, 2026
6 min read
#RAG#Vector DB#PostgreSQL#LLM#AI Engineering
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