RelationalAI is the industry's first AI coprocessor for data clouds and language models. Its groundbreaking relational knowledge graph system expands data clouds with integrated support for graph analytics, business rules, optimization, and other composite AI workloads, powering better business decisions.

RelationalAI is cloud-native and is built with the proven and trusted relational paradigm. These characteristics enable RelationalAI to seamlessly extend data clouds and empower you to implement intelligent applications with semantic layers on a data-centric foundation.

Benefit from a universal data representation that can be projected as tables, graphs, JSON, tensors, and matrices, and novel join algorithms that dramatically speed up graph traversal, multi-way joins, and complex queries without sacrificing performance.

Security and privacy of customer data are protected by following industry best practices. Data is encrypted in transit and at rest.

Common use cases include:

Entity Resolution. See through noisy data to find related information and duplication where the data lives and benefit from advanced features for higher accuracy.

Fraud Detection. Identify sophisticated fraudulent activity in e-commerce, financial services, telecommunications, and more by surfacing meaningful patterns and predictive elements in your data to reduce loss and protect your customers.

Supply Chain Risk Management. Mitigate risks through a comprehensive understanding of the relationships across your supply chain.

Investment Opportunities. Identify new investment opportunities armed with data from various sources in a unified single view.

Customer 360. Uncover important relationships and connections to improve recommendations.