Use Case

AI-Driven Reference Data for Accurate Insights

Data Graphs leverages its AI capabilities to centralize reference data, ensuring consistent and accurate information while overcoming traditional obstacles of siloed systems. It streamlines operations, empowers smarter decision-making, and is the backbone of your AI strategy.

Master Data Management for Enterprise Systems

Unify reference data across ERP, CRM, PIM, DAM, MAM, HR, or other systems, driving organizational coherence and operational efficiency.

How it works

Data Graphs integrates and maps data entities, enforcing robust data governance to ensure consistency and reliability across systems.

Example

Retailers synchronize product information seamlessly across e-commerce, inventory, product and marketing asset management, and supply chain systems, enhancing agility and accuracy.

Product Information Management and Analytics

Optimize product catalog management with AI-powered insights to drive strategic decisions and operational alignment.

How it works

Data Graphs centrally manages reference data (product categories, attributes, pricing, vendor info, and analytics) while linking it to product information and assets for consistent sales channel delivery.

Example

E-commerce companies can rely on Data Graphs to maintain a consistent reference dataset for product information and analytics, enhancing cross-channel alignment and operational efficiency.

Supply Chain Reference Data Management

Manage and optimize supply chain data with the precision and intelligence of AI-driven insights.

How it works

Data Graphs lets you model reference data for suppliers, parts, and shipping, intelligently tracking relationships and dependencies in real-time.

Example

Global manufacturers can leverage Data Graphs to maintain a comprehensive, real-time database of suppliers, parts, and routes, optimizing supply chain operations and reducing risk.