Introducing AI Brain 4.0: Hybrid RAG Search and Extended Thinking
Sophia Lin
Our biggest AI engine upgrade ever. AI Brain 4.0 combines vector search, keyword matching, and graph-based retrieval for dramatically more accurate responses. In this article, we dive deep into the technical decisions, architectural patterns, and practical implications behind this topic.
Background
The landscape of AI-powered customer engagement has evolved dramatically over the past year. Businesses are demanding more accurate, context-aware responses that go beyond simple FAQ matching. Traditional retrieval-augmented generation (RAG) approaches, while effective for many use cases, have shown limitations when dealing with complex multi-hop queries and nuanced domain knowledge.
At Kleif AI, we have been working on solving these challenges since the platform launched. Our research into hybrid search, graph-based knowledge representations, and extended reasoning has culminated in major improvements.
Getting Started
This feature is available to all Pro and Business plan users. You can learn more about our plans on the pricing page.
Sophia Lin
Head of AI at Kleif AI. PhD in NLP from Stanford.