Home - Relational AI

Power every decision

with intelligence

Model your business with a Relational Knowledge Graph to build intelligent applications and turn LLMs into enterprise-grade decision engines—able to reason, predict, and optimize natively inside Snowflake.

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Model your business with a Relational Knowledge Graph...

a system for organizing data and rich semantics

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.

same architecture. Same paradigm. No silos.

Build AI-native applications, automate decisions, and scale intelligence directly in Snowflake, where your data lives.

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

Watch Snowflake introduce RelationalAI at the Snowflake Summit

Our advanced 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

Understanding how money, items, and data flow through your business is a key for detecting issues like fraud before they become significant liabilities. Use AI to label suspicious actors and then traverse the transaction graph for situations that need review.

Identifying key influencers within a customer base enhances marketing strategies and engagement. Using graph algorithms like PageRank, businesses can determine the most influential customers based on their connections and interactions, enabling targeted marketing and efficient resource allocation.

By leveraging the graph structure of the power grid, repairs can by easily prioritized by impact, ensuring critical loads and distribution centers are automatically prioritized first.

The industries we serve .... for problems that matter

FINANCIAL SERVICES

RETAIL & CONSUMER GOODS

TELECOM

ADVERTISING, MEDIA & ENTERTAINMENT

HEALTHCARE

MANUFACTURING

TECHNOLOGY

PUBLIC SECTOR

TRAVEL & HOSPITALITY

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

Track products throughout your supply chain with ease. Enhance operational efficiency by identifying bottlenecks and potential disruptions, ensuring timely deliveries and optimized inventory management.

Read case study

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.

Latest case studies

AI, Graphs, Manufacturing, Retail, Supply chain

RETAIL: AI-Driven Supply Chains at Scale
Customer 360°, Graphs, Optimization

FINANCE: Customer Value Through Graph Reasoning
Fraud detection, Optimization, Telecom

TELECOM: Smarter Enterprise AI Applications

Customer testimonials

We replaced over 100,000 lines of legacy code and reduced TCO by 50%—all while running directly in Snowflake.

Chief Product Officer, Blue Yonder

With RelationalAI, we went from weeks to minutes in processing time, eliminated 80,000 manual hours, and unlocked a $200M opportunity.

Partner, EY

RelationalAI helped AT&T create an enterprise-wide knowledge graph to drive consistency and save millions through better fraud detection.

VP of Data, AT&T

We saw a 10-fold reduction in both compute time and compute costs.

Cristian Figueroa, Head of Network Science and Behavioral Modeling, Cash App