AI Agents With Reusable Data Products and Decentralized Knowledge Graph

AI Agents With Reusable Data Products and Decentralized Knowledge Graph Charles Ivie, AWS, Sr Graph Architect šŸ”— connect with speaker on LinkedIn Ā Ā /Ā charlesivieĀ Ā  Tony Seale, The Knowledge Graph Guys, Founder Ā Ā /Ā tonysealeĀ Ā  Branimir Rakić, OriginTrail, Founder and CTO Ā Ā /Ā branimirrakicĀ Ā  Ben Clinch, Ortecha, Partner Ā Ā /Ā benclinchĀ Ā  Description Background: Data Products deliver higher ROI for data management and lower costs of ownership. Yet, implementations are often hard, expensive and unstandardized for wider use, inadvertently forming new silos. With DPROD’s semantic structure, organizations can easily produce standardized Data Products. These allow for trusted neuro-symbolic AI agents - secured and traceable via OriginTrail. Workshop Structure Phase 1: Introductions (30 mins) Data products, data fabric, and data mesh thinking Benefits of a collective distributed knowledge graph Introduction to DPROD standard Phase 2: Data Product Creation (45 mins) We supply the data or you can bring your own Design data product using Graph.Build ontology Import data into Amazon Neptune Conform to DPROD standard metadata structure Phase 3: Publishing (1 hour) Create a paranet in OriginTrail Publish the data product Phase 4: AI Integration Connect LLM Interrogate the data product This workshop offers hands-on experience in creating, describing, and publishing standardized data products, showcasing their potential for secure sharing and monetization within organizations and externally. hashtags #knowledgegraph #agenticai #aiagents #kgc2025 šŸ”— Stay Connected with KGC 🌐 Website https://www.knowledgegraph.tech šŸ“© Newsletter https://info.knowledgegraph.tech/kgc-... šŸ’¼ LinkedIn Ā Ā /Ā the-knowldge-graph-conferenceĀ Ā  šŸ’¬ Slack Community https://join.slack.com/t/knowledgegra... 🐦 Twitter Ā Ā /Ā kgconferenceĀ Ā  šŸ“ŗ Watch all KGC content on Vimeo https://watch.knowledgegraph.tech/

Zep: A Temporal Knowledge Graph Architecture for Agent Memory
ā–¶ļøŽ

Zep: A Temporal Knowledge Graph Architecture for Agent Memory

RL for Agents Workshop - Deep Dive on Training Agents with RL and Open Source
ā–¶ļøŽ

RL for Agents Workshop - Deep Dive on Training Agents with RL and Open Source

AI-Driven Energy Data Integration and Prospect Evaluation with Sashi Gunturu, May 19 2026
ā–¶ļøŽ

AI-Driven Energy Data Integration and Prospect Evaluation with Sashi Gunturu, May 19 2026

Databricks Unity Catalog Workshop: End-to-End Data + AI Governance and Access Control (April 2026)
ā–¶ļøŽ

Databricks Unity Catalog Workshop: End-to-End Data + AI Governance and Access Control (April 2026)

How Semantic Layers and Ontologies Create Trusted AI
ā–¶ļøŽ

How Semantic Layers and Ontologies Create Trusted AI

Engineering Resilient Cognitive Systems 2026 | L8: AI Safety & CARE-Analysis
ā–¶ļøŽ

Engineering Resilient Cognitive Systems 2026 | L8: AI Safety & CARE-Analysis

Yann LeCun's $1B Bet Against LLMs [Part 1]
ā–¶ļøŽ

Yann LeCun's $1B Bet Against LLMs [Part 1]

Agent Framework: Building Blocks for the Next Generation of AI Agents
ā–¶ļøŽ

Agent Framework: Building Blocks for the Next Generation of AI Agents

Build a Document Intelligence Pipeline With Nemotron RAG | Nemotron Labs
ā–¶ļøŽ

Build a Document Intelligence Pipeline With Nemotron RAG | Nemotron Labs

Build a Complete Medical Chatbot with LLMs, LangChain, Pinecone, Flask & AWS šŸ”„
ā–¶ļøŽ

Build a Complete Medical Chatbot with LLMs, LangChain, Pinecone, Flask & AWS šŸ”„

Building More Expressive Next-Gen Knowledge Resources
ā–¶ļøŽ

Building More Expressive Next-Gen Knowledge Resources

Andrej Karpathy: From Vibe Coding to Agentic Engineering w/ Stephanie Zhan
ā–¶ļøŽ

Andrej Karpathy: From Vibe Coding to Agentic Engineering w/ Stephanie Zhan

Building Agentic AI Workloads – Crash Course
ā–¶ļøŽ

Building Agentic AI Workloads – Crash Course

Turing Award Winner: Disagreeing with Google, Postgres, Future Problems | Mike Stonebraker
ā–¶ļøŽ

Turing Award Winner: Disagreeing with Google, Postgres, Future Problems | Mike Stonebraker

Don't learn AI Agents without Learning these Fundamentals
ā–¶ļøŽ

Don't learn AI Agents without Learning these Fundamentals

AI Agents for Beginners – Part 1 (Free Labs)
ā–¶ļøŽ

AI Agents for Beginners – Part 1 (Free Labs)

Something is jamming GPS over Europe. Here's what we found
ā–¶ļøŽ

Something is jamming GPS over Europe. Here's what we found

AG-UI: How to Bring AI Agents Into Frontend Applications (Webinar)
ā–¶ļøŽ

AG-UI: How to Bring AI Agents Into Frontend Applications (Webinar)

How AI agents & Claude skills work (Clearly Explained)
ā–¶ļøŽ

How AI agents & Claude skills work (Clearly Explained)

System Design Explained: APIs, Databases, Caching, CDNs, Load Balancing & Production Infra
ā–¶ļøŽ

System Design Explained: APIs, Databases, Caching, CDNs, Load Balancing & Production Infra