Convex is a powerful backend-as-a-service tailored for full-stack TypeScript development. It combines a curated array of backend services - including database management, serverless functions, and state management - into a seamless, all-in-one platform. Designed with rapid development and scalability in mind, Convex helps developers streamline their workflows and build sophisticated applications without wrestling with complex backend infrastructure.

Graph_RAG is a Python-based framework designed to build and query knowledge graphs for retrieval-augmented generation (RAG). It supports ingestion of unstructured documents, automated extraction of entities and relationships using LLMs or NLP tools, and storage in graph databases such as Neo4j. With Graph_RAG, developers can construct connected knowledge graphs, execute semantic graph queries to identify relevant nodes and paths, and feed the retrieved context into LLM prompts. The framework provides modular pipelines, configurable components, and integration examples to facilitate end-to-end RAG applications, improving answer accuracy and interpretability through structured knowledge representation.