Building an AI-Powered Smart Guide for Business Planning and Entrepreneurship | by Umair Ali Khan | January, 2025
Advanced LangGraph-based RAG with standard business guidelines, AI-based web search, trusted sources, and composite search offering multiple models
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After the introduction of ChatGPT and the subsequent proliferation of Large-scale Language Models (LLMs), their inherent limitations of objectivity, information expiration date, and inability to provide organization- or person-specific information were quickly recognized and recognized as major problems. To address these issues, Retrieval Augment Generation (RAG) methods have recently gained a tendency to integrate external data into LLMs and direct their behavior to answer queries from a specific knowledge base.
Interestingly, the first RAG paper was published in 2020 by researchers from Facebook AI Research (now Meta AI), but it wasn't until ChatGPT arrived that its potential was fully realized. Since then, there has been no stopping. More advanced and complex RAG frameworks were introduced that not only improved the accuracy of this technology but also enabled them to deal with multimodal data, increasing its potential for a variety of applications. I have written about this topic in detail in the following articles, mainly discussing multimodal RAG, multimodal AI search for business applications, and knowledge…
