Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

February 2025

Understanding LLM Evaluation Metrics for Better RAG Performance

In the evolving landscape of artificial intelligence, Large Language Models (LLMs) have become essential for natural language processing tasks. They power applications such as chatbots, machine translation, and content generation. One of the most impactful implementations of LLMs is in Retrieval-Augmented Generation (RAG), where the model retrieves relevant documents before generating responses.

Securing LLM-Powered Applications: A Comprehensive Approach

Large language models (LLMs) have transformed various industries by enabling advanced natural language processing, understanding, and generation capabilities. From virtual assistants and chatbots to automated content creation and translation services, securing LLM applications is now integral to business operations and customer interactions. However, as adoption grows, so do security risks, necessitating robust LLM application security strategies to safeguard these powerful AI systems.