AmirhosseinHonardoust/Designing-Hybrid-AI-Systems
Hybrid AI is the future of explainable intelligence. This article explores how combining vector search, knowledge graphs, and retrieval-augmented generation (RAG) creates AI systems that can reason, cite, and explain their answers with insights learned from building a real Graph-Powered RAG Engine.
This project helps you build AI systems that can explain their answers, similar to a knowledgeable expert who can cite their sources. It takes various documents and processes them into a structured knowledge base with explicit connections. The result is a system that can answer questions, show you exactly where the information came from, and even explain why certain facts were chosen, which is especially useful for professionals who need to trust and verify AI outputs.
Use this if you need an AI system that can not only provide answers but also transparently show its reasoning and cite specific sources, building trust in critical applications.
Not ideal if you're looking for a simple, off-the-shelf chatbot without any need for deep explainability or connecting complex relationships between information.
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Last pushed
Nov 01, 2025
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