Power every decision with intelligence
Model your business
with a
Relational Knowledge Graph…
Organize data as a graph
Data is organized as a set of concepts and the relationships between them, expressed relationally in graph normal form (GNF).
Represent knowledge relationally
Relationships are base or derived. If they are derived, they can be derived with a variety of relational intelligence reasoners such as graph, rule-based, predictive or prescriptive.
Leverage neural and symbolic reasoners
Relational intelligence combines neural & symbolic reasoners to help us reason about our past, present, and future. Answer important questions about your business beyond what you can answer with RAG and text-to-SQL.
... natively inside Snowflake.
Build AI-native applications, automate decisions, and scale intelligence directly in Snowflake, where your data lives. Same paradigm. Same Architecture. No silos.
Embedded: RelationalAI runs entirely within your Snowflake account, inside your security perimeter, governed by your policies — with no need to copy or synchronize data to external tools.
Cloud native: supports zero-copy cloning, versioning, and time travel for full flexibility and scale. Relational: broadly accessible paradigm allows you to leverage internal expertise with SQL and Python on Snowflake.
Why
customers choose RelationalAI
Value creation
Better decisions with AI
Efficiency
Order of magnitude code reduction
Operational simplicity
No need to manually synchronize data
Flexible pricing
Consumption-based pricing
Security
No data leaves Snowflake
Performance
Available across industries...
Retail & Consumer Goods
Healthcare
Manufacturing
Public Sector
Finance
Technology
Travel & Hospitality
Telecom
Advertising, Media & Entertainment
...to work on problems that matter.
Customer 360°
Uncover important relationships and connections to improve engagement. By integrating data from various sources, gain a comprehensive view of your customers, enabling more personalized interactions and targeted marketing strategies.
Supply chain optimization
Track products throughout your supply chain with ease. Enhance operational efficiency by identifying bottlenecks and potential disruptions, ensuring timely deliveries and optimized inventory management.
Fraud detection
Build graph-based features to augment your fraud model predictions. Leverage advanced analytics to detect unusual patterns and suspicious activities, reducing the risk of fraudulent transactions and protecting your business.
Entity resolution
Use a knowledge graph to “see” through noisy data to find related information and duplicated data. Achieve higher data accuracy and consistency, improving decision-making and operational efficiency by eliminating redundancies and ensuring reliable insights.
Recommendations
Identify similar consumers or products for personalized recommendations. Enhance customer satisfaction and drive sales by offering tailored suggestions based on user behavior and preferences, fostering a more engaging shopping experience.
Influencer analysis
Identify influencers and communities in your customer base. Leverage insights to amplify your marketing campaigns by targeting key opinion leaders and understanding the social dynamics within your customer network.
Relational Intelligence able to leverage compound AI reasoners
Graph reasoning
Uncover hidden patterns with advanced graph queries for path finding and graph algorithms for community detection, centrality, similarity, and more
Rules-based reasoning
Simplify intelligent application development with expressive and scalable rule-based based reasoning
Predictive reasoning
Predict the impact of your decisions by leveraging GenAI and Graph Neural Networks
Prescriptive reasoning
Optimize business operations with sophisticated solvers for mixed integer programming (MIP) and satisfiability (SAT)
How it works
Testimonials
Latest case studies
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Manufacturing, RetailAI-driven supply chains at scale
