From Knowledge Graph Assistant to Agentic AI with LangGraph https://WebToolTip.com Published 8/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 4h 51m | Size: 3.19 GB
Build enterprise-grade multi-agent AI systems using LangGraph, Knowledge Graphs, RAG, Neo4j, Human-in-the-Loop, Memory,
What you'll learn
Build a multi-agent AI Assistant using LangGraph with Planner, Ontology, Retrieval, Insight, and Response agents.
Integrate Knowledge Graphs, GraphRAG, and LLMs to deliver accurate, explainable, and context-aware AI responses.
Implement agent orchestration, memory, tool calling, and human-in-the-loop workflows for enterprise AI assistants.
Monitor, trace, and evaluate AI agents using LangSmith to debug, optimize, and improve production-ready AI systems.
Requirements
Prior knowledge of Semantic Web or Knowledge Graphs is required.
A willingness to learn Ontology Engineering and Semantic Web technologies based Agentic AI system
A computer with at least 8 GB RAM (16 GB recommended)
Advanced programming language in Python.