This video from RelationalAI demonstrates the integration between RelationalAI’s Knowledge Graph (KG)-based semantics and Snowflake’s Semantic Views. The demo shows how to create a Semantic View in Snowflake from a RelationalAI Knowledge Graph, and conversely, how to enrich a Snowflake Semantic View by translating it into RelationalAI semantics.

🚀 You will be able to:

• Understand the value of the RelationalAI Knowledge graph semantics
• Use the RelationalAI semantics and the different reasoning capabilities
• Convert RelationalAI KG semantics to Snowflake Semantics views
• Use the Snowflake Semantics view with Cortex Analyst
• Convert a Semantics view to a RelationalAI KG based semantics

Blue Yonder is building an intelligent, living digital twin of their supply chain using RelationalAI.

🚀 In this demo, you will see:

• A digital twin of a detailed supply chain network with key business elements like Items, Locations, Supply Methods, and Resources, all mapped in a knowledge graph.
• How advanced analytics and decision-making are enabled by enriching Snowflake data into a materialized graph view.
• A two-panel UI: the Integrated Demand and Supply Planning (IDSP) network and the high-level Integrated Business Planning (IBP) network.
• Live zooming into specific nodes, like Finished Goods at factories, and understanding upstream and downstream flows.
• Network simplification using over 400 business rules via RelationalAI’s rule-based reasoner, reducing complexity and enhancing visibility.
• Natural language querying for insights on item impact, resource dependencies, and complexity analysis.

RelationalAI powers smarter supply chain management with advanced data modeling, visualization, and optimization.

🚀 In this demo, you’ll learn:

• Data modeling: How we load and connect parts, BOMs, locations, and routes into the PATHFINDER_SE model — the foundation for powerful analysis and dependency tracing.
• Visualization: Using the Graph class to map part dependencies, spot bottlenecks, and identify critical components through intuitive, color-coded graphs.
• Impact analysis: Quickly assess the downstream impact of defective parts and compare BOMs across products to optimize resources and reduce costs.
• Cost calculation: Accurately compute total production costs using nested aggregates to handle real-world complexities like quantity scaling across assemblies.
• Route optimization: Solve delivery logistics with a solver model to find the most efficient route from warehouse to retailers, minimizing distance and boosting operational efficiency.