What is Agentic RAG? Building Agents with Qdrant
Agents are a new paradigm in AI, and they are changing how we build RAG systems. Learn how to build agents with Qdrant and which framework to choose.
Kacper Łukawski
·November 22, 2024
RAG & GenAI
Leverage Qdrant for Retrieval-Augmented Generation (RAG) and build AI Agents
Optimizing RAG Through an Evaluation-Based Methodology
Learn how Qdrant-powered RAG applications can be tested and iteratively improved using LLM evaluation tools like Quotient.
Atita Arora
·June 12, 2024
Semantic Cache: Accelerating AI with Lightning-Fast Data Retrieval
Semantic cache is reshaping AI applications by enabling rapid data retrieval. Discover how its implementation benefits your RAG setup.
Daniel Romero, David Myriel
·May 07, 2024
What is RAG: Understanding Retrieval-Augmented Generation
Explore how RAG enables LLMs to retrieve and utilize relevant external data when generating responses, rather than being limited to their original training data alone.
Sabrina Aquino
·March 19, 2024
Is RAG Dead? The Role of Vector Databases in Vector Search | Qdrant
Uncover the necessity of vector databases for RAG and learn how Qdrant's vector database empowers enterprise AI with unmatched accuracy and cost-effectiveness.
David Myriel
·February 27, 2024