Technical articles, case studies, and industry insights from the MabTech Pro team.
Artificial Intelligence has evolved rapidly over the past few years, but one challenge remains consistent: ensuring AI systems provide accurate, relevant, and context-aware responses. While Large Language Models (LLMs) are incredibly powerful, they are limited by the data they were trained on and can sometimes generate outdated or inaccurate information. To address these limitations, I have been working extensively with Retrieval-Augmented Generation (RAG) and LangGraph to build intelligent AI applications that combine the reasoning capabilities of LLMs with real-time access to organizational knowledge.
