ShuklaA11/SciRag

SciRag is a recently released project (1 day old, 0 stars) that implements a Retrieval-Augmented Generation (RAG) pipeline for scientific papers. While the '14-week build' description suggests a non-trivial amount of development effort, the project currently lacks any market validation or community adoption. Technically, it focuses on section-aware retrieval and citation-graph expansion—features that are rapidly becoming standard in scholarly search tools like Consensus, Elicit, and Perplexity. Frontier labs and major platforms pose an existential threat; Google's NotebookLM and Gemini 1.5 Pro (with its 2M+ token context window) are natively solving the 'document-as-context' problem, while Semantic Scholar and ResearchGate already own the underlying data graphs. Without a proprietary dataset or a unique algorithmic breakthrough, this remains a high-quality personal project or prototype rather than a defensible product. Its displacement horizon is extremely short given the velocity of the 'AI for Research' vertical.