From Architecture to Action: Automating the AI-Ready Data Foundation

Research Context and Background

Enterprise artificial intelligence often fails not because of the models used, but because of the data they rely on. For AI to be trusted and useful, companies need stable data identities, complete history, clear relationships, and defined business rules. These elements must be built into the integration layer of their data systems. Many organizations move to modern platforms like Microsoft Fabric using a quick "lift and shift" method. This approach moves existing data without fixing underlying issues. As a result, the data remains hard to find and inconsistent. This causes AI projects to stall months after the initial migration because the system cannot understand the data it is supposed to use. Building the foundation properly usually takes too long, forcing teams to choose between speed and quality. IRiS is a platform designed to solve this problem by automating the creation of a strong data foundation.

Benefits

IRiS helps organizations build a solid base for their AI projects without sacrificing speed. The platform reads existing data metadata, analyzes the data, and guides users through the design process. It then automatically generates the necessary code and governance rules for the integration layer. Key advantages include:

• Strong Data Structure:IRiS uses Data Vault 2.1 to create a foundation that provides stable identities for data entities, keeps a full history of changes, and makes relationships between data points clear. This structure is essential for AI to function correctly.
• Ten Times Faster Modeling:Tasks that used to take four hours per table now take less than 15 minutes. This speed allows companies to build an AI-ready system quickly without skipping important groundwork.
• Built-in Governance:The platform enforces standards consistently across all teams. It documents definitions as it works, ensuring the foundation is robust and follows company rules.

Use Cases

IRiS is designed for organizations that want to move to modern data platforms like Microsoft Fabric and need an AI-ready foundation. It fits into the Medallion zones of existing enterprise data stacks. A specific example is a financial services company that wanted to predict customer churn. To do this, they needed five specific data capabilities. IRiS delivered these by using specific Data Vault structures to explain the data clearly. This approach ensures that the link between the data method and the AI result is obvious. The platform allows companies to start using AI capabilities in the first sprint of a project rather than waiting years to build the foundation. This investment can be reused for every future AI project the company undertakes.

Pricing

IRiS is available on the Microsoft Azure Marketplace as a Managed Application. It is eligible for MACC, which allows purchases to be paid for using existing Microsoft Azure consumption commitments. This means companies can use their current budget allocations instead of going through separate procurement processes to buy the tool.

Vibes

The tool is positioned as a solution that removes the trade-off between speed and quality in data migration. By combining global Data Vault leadership with Microsoft Fabric expertise, the platform empowers organizations with a robust and AI-ready system. The approach is described as fast and frictionless, helping teams avoid the common pitfall of building the same foundation twice for different projects.

Additional Information

IRiS is a product developed by Scalefree International. The company combines its global leadership in Data Vault with deep expertise in Microsoft Fabric. This partnership covers both the migration expertise and the practitioner capability needed to solve data foundation problems. The solution is not a complete AI stack on its own. Instead, it sits below RAG pipelines, LLM interfaces, and ML platforms to provide the necessary groundwork for them to succeed.