Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) enhances LLMs by grounding responses in external data, improving accuracy and reducing hallucinations. However, this introduces challenges in data governance, source reliability, and transparency. Effective governance is key to building responsible RAG systems. Ready to learn how? Read our articles on RAG to learn more.
February 11, 2025
CAG vs RAG: Which One Drives Better AI Performance?
Explore the differences between CAG and RAG. Find the best AI approach for your company's needs: speed, simplicity, or adaptability. Learn more today!
February 4, 2025
CAG: What Is Cache-Augmented Generation and How to Use It
Discover what is Cache-Augmented Generation (CAG) & how it boosts AI speed, reliability, and security. Learn how it can transform your business. Read now!
December 17, 2024
AI in Finance: The Promise and Risks of RAG
AI in Finance: Learn how to safely implement RAG in finance by ensuring data privacy, compliance, and accurate AI outputs for better decision-making.
August 1, 2024
What is Retrieval-Augmented Generation (RAG)?
Discover how Retrieval-Augmented Generation (RAG) can enhance Large Language Models and add real value to your business.