Solution

Reference data that every system trusts.
And every AI agent can use.

Enterprise reference data is the foundation everything else builds on: product catalogs, supplier records, classification schemes, pricing structures, organizational hierarchies. When reference data is inconsistent, every downstream system inherits the problem. Data Graphs provides a single governed source of truth, accessible to both enterprise systems and AI agents.

One governed source. Every system aligned. Every AI grounded.

The challenge

Reference data is the weakest link in most enterprises

Reference data sits at the heart of every enterprise operation: product categories, supplier records, geographic hierarchies, classification schemes, pricing tiers, compliance codes. When this foundational data is scattered across ERP, CRM, PIM, and other systems, inconsistencies cascade through every process that depends on it.

Traditional master data management tools address the symptoms with point-to-point synchronization and rigid schemas. But in an AI-first world, the problem has a new dimension: AI agents need governed, relationship-rich reference data to reason over, not just flat lookup tables to query. The reference data backbone needs to serve both systems and intelligence.

Why Data Graphs for reference data
🔗
Unified reference graph
Integrate and map reference entities across ERP, CRM, PIM, DAM, HR, and supply chain systems into a single knowledge graph. One source of truth, not dozens of copies.
🏷
Rich classification hierarchies
Model product categories, industry codes, regulatory classifications, and organizational structures as graph-native hierarchies with full traversal and inheritance.
🛡
Governed stewardship workflows
Role-based access control, approval workflows, audit trails, and version history ensure reference data changes are deliberate, traceable, and compliant.
🤖
AI-ready via MCP and GraphRAG
AI agents and copilots access your reference data natively through MCP services and hybrid GraphRAG. Governance and permissions enforced automatically at the point of query.
📐
Flexible domain modeling
Visual modeling tools let you define reference data schemas that match your business reality. No rigid predefined structures. Adapt as your domain evolves.
🔄
Real-time API distribution
RESTful APIs with JSON-LD payloads distribute governed reference data to every consuming system in real time. W3C RDF compatible for standards-based interoperability.
Use cases
🏢

Master data management across enterprise systems

Unify reference data across ERP, CRM, PIM, DAM, MAM, HR, and other enterprise systems. Data Graphs integrates and maps data entities, enforcing governance to ensure consistency and reliability. Retailers synchronize product information seamlessly across e-commerce, inventory, marketing assets, and supply chain systems, eliminating the drift that causes operational errors.

📦

Product information management and analytics

Centrally manage product categories, attributes, pricing structures, vendor information, and analytics as governed reference data. Link this to product content and assets for consistent delivery across every sales channel. Data Graphs gives product teams a single, reliable foundation that feeds every downstream system and AI workflow.

🔗

Supply chain reference data

Model reference data for suppliers, parts, materials, shipping routes, and compliance requirements in a single knowledge graph. Track relationships and dependencies across multi-tier supply chains in real time. Global manufacturers maintain comprehensive, governed supplier networks that optimize operations and surface risk before it materializes.

How it works

From fragmented lookups to a governed reference graph

01

Model your reference data domain: entities, relationships, hierarchies, controlled vocabularies

02

Ingest and map reference data from existing enterprise systems via API or bulk import

03

Govern with stewardship workflows: approvals, versioning, audit trails, role-based access

04

Distribute governed reference data to consuming systems via real-time APIs

05

AI agents and copilots query your reference graph natively through MCP services

How Data Graphs compares

Beyond traditional MDM tools

Capability
Data Graphs
Traditional MDM
Spreadsheets
Generic databases
Relationship-rich data model
Knowledge graph native
Flat/tabular
None
Schema-dependent
AI access (MCP/GraphRAG)
Built-in
No
No
No
Classification hierarchies
Graph-native traversal
Limited
Manual
Custom build
Governance & stewardship
Full RBAC, audit trails
Partial
None
Manual
Cross-system distribution
Real-time APIs
Batch sync
Manual export
Custom integration
Domain flexibility
Visual modeling
Rigid schemas
Freeform
Code-only

Ready to unify your reference data?

See how Data Graphs can give every system and every AI agent a single, governed source of truth.