Building a Custom Knowledge Graph
This tutorial demonstrates how to build custom knowledge graphs from your enterprise data using Corvic AI. Learn how to transform your structured and relational data into a knowledge graph that captures entities, relationships, and context for powerful graph-based insights.What You’ll Learn
- Building custom knowledge graphs from enterprise data
- Defining entities and relationships
- Creating graph structures from relational data
- Generating graph embeddings for knowledge graphs
- Using knowledge graphs in agents and applications
Key Concepts
Knowledge Graphs
Knowledge graphs represent your data as a network of entities (nodes) connected by relationships (edges). Corvic AI enables you to build custom knowledge graphs that capture the structure, relationships, and context of your enterprise data, making it easier to discover insights and answer complex queries.Graph Structure
Knowledge graphs in Corvic AI preserve the relational structure of your data, allowing you to model complex relationships between entities. This enables powerful graph-based queries, relationship traversal, and pattern discovery that wouldn’t be possible with traditional flat data structures.Building Your Knowledge Graph
Step 1: Define Entities and Relationships
Identify the key entities in your data (people, organizations, products, concepts) and define the relationships between them. Use Corvic Tables to specify which entities and relationships should be included in your knowledge graph.Step 2: Configure Graph Structure
Configure how your relational data maps to graph structure. Define entity types, relationship types, and how they connect to create a meaningful knowledge graph representation of your domain.Step 3: Generate Graph Embeddings
Generate graph embeddings using Corvic AI’s graph structural encoding algorithms. These embeddings capture the structural patterns and relationships in your knowledge graph, enabling similarity search and relationship discovery.Step 4: Use in Applications
Use your knowledge graph embeddings in agents and applications to answer complex queries, discover relationships, and generate insights that leverage the graph structure of your data.Benefits
Custom knowledge graphs enable you to model complex relationships in your data, discover hidden connections, and answer sophisticated queries that require understanding entity relationships. Graph embeddings preserve these relationships in a searchable format, enabling powerful graph-based applications.Best Practices
Design your knowledge graph to reflect the important relationships in your domain. Use clear entity and relationship definitions, and ensure your graph structure accurately represents the connections in your data. Test graph queries to validate that your knowledge graph captures the relationships you need.Related Documentation
Corvic Tables
Learn how to define entities and relationships for knowledge graphs.
Spaces
Generate graph embeddings from your knowledge graph.
Agents
Use knowledge graphs in your agents for relationship discovery.
Data Sources
Understand how to prepare relational data for knowledge graphs.