Building Production Ready Agentic Systems with Graph RAG
A Talk by Anthony Alcaraz (Senior AI/ML BD/Strategist Manager EMEA, AWS)
About this Talk
Graph RAG: A Comprehensive System Design for Production-Ready Agentic GenAI Products
Workshop Overview
Introduction (15 minutes)
- The limitations of traditional RAG in enterprise settings
- The critical role of graph-native architectures
- Why autonomous agents are essential for next-gen AI systems
Graph-Native Knowledge Architecture (20 minutes)
- Beyond traditional knowledge graphs
- Graph RAG fundamentals
- Neural-symbolic reasoning engines
- Agentic memory systems
Architectural Patterns (30 minutes)
- Graph-native planning systems
- Tool orchestration frameworks
- Agent coordination patterns
- Knowledge graph-based evaluation
Implementation Strategies (25 minutes)
- Building enterprise knowledge graphs with agent support
- Graph foundation model integration
- Hybrid neural-symbolic systems
- Performance optimization at scale
Case Studies (35 minutes)
- Public service transformation
- Scientific discovery applications
- Enterprise support systems
Getting Started (15 minutes)
- Assessing organizational readiness
- Building a Graph RAG roadmap
- Key success factors and pitfalls
Q&A and Discussion (20 minutes)
Format
- Interactive workshop
- 2.5 hours running time
- Mix of presentations, demonstrations, and group discussions
Level
Intermediate to Advanced
- Focus on practical implementation
- Real-world examples
- Step-by-step guidance
Target Audience
Primary:
- Software Engineers working with AI
- ML Engineers
- Data Engineers
- Technical Product Managers
Secondary:
- AI Researchers
- Technical Team Leads
- Enterprise Architects
Goals
Learn to:
- Build Graph RAG systems from scratch
- Design effective agent architectures
- Implement knowledge-based AI systems
- Scale solutions for production use
- Evaluate system performance
Understand:
- Core Graph RAG concepts
- Agent system fundamentals
- Knowledge graph basics
- Production deployment patterns
Prerequisites
Required:
- Basic programming experience
- Familiarity with AI/ML concepts
- Understanding of RAG systems
Helpful:
- Graph database experience
- System design knowledge
- AI deployment experience
About The Speaker
Senior AI/ML BD/Strategist Manager EMEA, AWS
I am deeply involved in the AI community, where my expertise in decision science, particularly at the intersection of Large Language Models (LLM), Natural Language Processing (NLP), Knowledge Graphs, and Graph Theory, is applied to foster innovation and strategic development.
We’re a cloud tech company that provides organisations around the world with computing infrastructure and software to help them innovate, unlock efficiencies and become more effective. We also created the world’s first – and only – autonomous database to help organise and secure our customers’ data.
