RAG (Retrieval Augmented Generation) is revolutionizing how companies personalize AI with their own data.

The Problem RAG Solves

ChatGPT, Claude and other LLMs are generic. They don't know your specific products, internal procedures, customer history, technical manuals, or company policies.

How RAG Works

Indexing (once)

1. Collect company documents

2. Split into chunks

3. Generate embeddings

4. Store in vector database

Query (real-time)

1. User asks question

2. System embeds question

3. Searches similar chunks

4. Sends to LLM with context

5. LLM responds based on context

**Want to implement RAG?** Talk to our specialists.