
Your Enterprise Data is Disconnected. Your Business Isn't
In large enterprises, simple, high-value questions often become complex, manual projects because the data lives in disconnected silos.
Answering simple business questions takes weeks
AI and analytics projects constantly stall.
Data loses its context every time a system changes.
Unique IDs forming the connective tissue across business applications
The FAIR Data Registry solves data fragmentation at its core. It removes ambiguity by registering all important data objects with clear semantic context so that data can be automatically connected across systems forming a virtual linked data network.

Creates a Future-Proof AI-Ready Data Foundation

Reduces Manual Effort and Expert Bottlenecks

Achieve Compliance in Months, Not Years

The Strategic Foundation for Data-Driven Leaders
“Partnering with ACCURIDS to introduce a graph-based Browser for Reference and Master Data has brought substantial value to our users facilitating easy access, discoverability, and connectivity of critical data in Regulatory Science, R&D. Especially the platform's responsiveness and user-friendly interface are appreciated by our user community.”
How to Implement FAIR Data at Scale
A permanent identity for your data that survives system changes


A flexible, connected view of your data that mirrors your business
Find the data you need, when you need it, how you need it

Trustworthy, reliable data for your most critical decisions
How the FAIR Data Registry Actually Works
A full walkthrough from namespace registration to 25M+ connected identifiers in 18 min.
Six components for a
shared Data Language
Ontology
Reference and Master Data
Data Registry
Graph
Quality
AI deeply embedded
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From Global Compliance Mandate to Strategic Asset
Security & Compliance
You Can Trust.
Designed for GxP
&
21 CFR Part 11
Flexible Deployment for Your Environment
Full Data Control
& Isolation
Frequently asked questions
Its a system the manages Globally Unique Persistent Identifeirs for all your important data objects across the enterprise. The FAIR Data Registry does not copy data but provides a logical, unified, persistent "Data Identity Resolver". By centralizing the governance oversight of which systems manage with data objects, we decouple the identity of data from the systems where they are currently manged. This creates a reliable virtual network of interlinked data - independent of system and application changes and from your existing, fragmented systems. It is a central source of truth built on a Knowledge Graph core that is purpose-built to make your data Findable, Accessible, Interoperable, and Reusable (FAIR) across the enterprise. This transforms your siloed information into a lasting, strategic, and AI-ready asset.
Our platform embeds FAIR principles into its core architecture:
- Findable: It assigns a persistent, unique ID to every unified "Golden Record" of data, such as a substance or product.
- Accessible: The unified "Product Data Backbone" can be directly and easily accessed by business users and applications , with flexible deployment options to meet your enterprise security needs.
- Interoperable: We use the official IDMP Ontology as a common language, automatically transforming differently structured data into a single, uniform format that ensures true interoperability.
- Reusable: By connecting data in a Knowledge Graph, we create a rich semantic network that makes the data immediately actionable and reliable for reuse in analytics, automation, and AI models.
The core of our platform is the Knowledge Graph. Unlike traditional databases that store data in rigid tables, a knowledge graph is designed to map the complex relationships between data points. This creates a semantic network that understands, for example, which substance belongs to which product and which was used in which clinical trial. This contextual understanding is the key to unlocking true interoperability and surfacing hidden insights for AI and advanced analytics.
Yes. The IDMP Fabric focuses on medicinal product data using the pre-built IDMP Ontology. The Fair Data Registry handles any data type with flexible ontologies. Organizations can use one or both depending on their needs.
AI and machine learning models are only as good as the data they are trained on. Most AI initiatives struggle because data is fragmented, inconsistent, and lacks the necessary context to be useful.
Our platform directly solves this by creating a foundational, AI-ready asset. By standardizing and unifying your data into "Golden Records" and then connecting them in a Knowledge Graph, we build a rich semantic context around your information. This process unlocks the immediate, reliable AI value from your standardized data, allowing your data science teams to focus on building powerful models instead of manually cleaning data.
News & Insights
`Ready to Build a` Truly Connected Enterprise?
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