NisaarAgharia/Advanced_RAG

This project functions as a pedagogical resource rather than a defensible piece of software. With 466 stars and 85 forks over two years, it has served as a helpful community guide, but its 'velocity' of zero indicates it is a static repository of patterns rather than an evolving library. The techniques demonstrated (Advanced RAG, Agentic Search) are now standard features within the core documentation of LangChain and LlamaIndex, and more critically, are being absorbed into 'RAG-as-a-service' offerings from frontier labs (e.g., OpenAI Assistants API, Anthropic Contextual Retrieval, and Google Vertex AI Search). There is no technical moat; the value lies entirely in the curation of existing methods. A technical investor would view this as 'educational content' rather than a 'product.' The displacement horizon is near-immediate as these manual configurations are being replaced by automated, managed pipelines from cloud providers.