Model your business in an expressive and executable way
with Relational Knowledge Graphs
Capture your collective “common sense”
RelationalAI’s knowledge graph provides a common model of your business to help you observe, decide, and act.
Streamline and enhance all your decisions
RelationalAI’s coprocessor powers advanced analytics and AI to ensure you can make consistent, high quality decisions at unprecedented speed across the entire organization.
Leverage the data cloud to its full potential
Our deep integration means you get powerful new decision tools all while maintaining your existing security and governance.
A different level of integration
We believe that rather than creating yet another silo, knowledge graphs should live with your data and take advantage of the tremendous value you get from centralizing everything in Snowflake’s data cloud.
Since RelationalAI’s native application is built on top of Snowpark Container Services, data never leaves the Snowflake perimeter. You get the same governance and the same security, but with a new set of tools for decision making.
Model your business with a Relational Knowledge Graph
We are the Relational Knowledge Graph native to Snowflake. Think of the relational knowledge graph as a “collective common sense.” With it, capture the concepts and relationships in a model that makes up your business so that decisions made by both people and agents are driven with intelligence.
Relational Knowledge Graphs for decisions driven by compound reasoning, pattern discovery, logical inference, prediction, and optimization.
Rich semantics pushed down to the data layer.
LLMs better aligned to your domain and specific business.
Features and capabilities
EXPRESSIVE KNOWLEDGE MODELING
Model complex business logic, constraints, and relationships using a declarative language designed for knowledge representation. Build and compose ontologies, rules, and logic in a way that integrates seamlessly with Python and supports both verbalized and programmatic workloads.
INTEGRATED REASONING
RelationalAI provides a comprehensive set of reasoners —including rule-based, graph, predictive, and prescriptive—that operate over a shared knowledge graph. These reasoners are composable and interoperable, enabling compound AI workloads with explainable, logic-driven outputs.
SNOWFLAKE-NATIVE DATA INTEGRATION
Build knowledge graphs and reason over Snowflake enterprise data—no data movement, extracts, or pipelines required. Reasoning is grounded in the most current data, enabling intelligent applications that are semantically aware.
CLOUD-NATIVE, SCALABLE ARCHITECTURE
Built on a cloud-native foundation, RelationalAI separates compute and storage and scales elastically to support demanding app and AI workloads. The system extends the relational paradigm to support graph and logic-based computation, enabling intelligent apps and reasoning at enterprise scale.
ENTERPRISE-GRADE SECURITY & GOVERNANCE
RelationalAI integrates with Snowflake’s security and governance model, including support for Tri-Secret Secure (TSS) and end-to-end data encryption. Inherit existing access controls and compliance posture, ensuring secure reasoning over sensitive enterprise data.
Built for advanced AI
Graph reasoning
Analyze interconnected data to uncover hidden patterns and relationships by leveraging advanced graph queries for path finding and graph algorithms for community detection, centrality, similarity, link prediction and path analysis. Build intelligent applications like fraud detection, customer 360, supply chain risk management, entity resolution, and more.
Rule-based reasoning
Simplify intelligent application development with expressive and scalable rule-based based reasoning, by bringing knowledge and semantics closer to your data, reduce your code footprint by 10x, improve accuracy, and drive consistency and reusability across your organizations with common business models understood by all.
Predictive reasoning
Predict the impact of your decisions by leveraging GenAI and Graph Neural Networks to build accurate models directly from your knowledge graph without the need for manual feature engineering.
Prescriptive reasoning
Optimize complex business operations faster and more efficiently with sophisticated solvers for mixed integer programming (MIP) and satisfiability (SAT). Understand business objectives and use a conceptual model of your business to identify optimization potential quickly and easily. (Coming soon)
Demos
This demo illustrates how to leverage RelationalAI’s native integration with Snowflake to implement GraphRAG (Graph Retrieval-Augmented Generation). It covers setting up the environment and executing reasoning workloads within Snowflake.
Explore how to detect fraudulent activities by applying graph analytics and reasoning over relational data using RelationalAI within Snowpark Container Services.
Learn how to construct a customer social graph to identify relationships and communities among customers, enhancing personalization and engagement strategies.