A Review Paper on Startup Blueprint Generator using RAG and LLMs

In the evolving landscape of artificial intelligence, the integration of Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) has introduced new possibilities for intelligent business planning and automation. This review paper explores the concept of an AI-driven system designed to generate startup blueprints automatically — transforming a user's raw business idea into a structured business plan using RAG and LLM-based architectures. The paper reviews existing literature on LLM applications, information retrieval methods, and AI-driven business intelligence systems. It also highlights key frameworks, tools, and technologies supporting such systems, including OpenAI GPT models, FAISS, Pinecone, and LangChain. Further, the paper discusses challenges such as data reliability, ethical considerations, and scalability. The review concludes that AI-assisted startup planning tools have the potential to democratize entrepreneurship by reducing the knowledge gap for first-time founders while ensuring data-driven and adaptive business insights.