We’re incredibly excited to announce the release of metaphactory 5.8, which introduces many new features to metaphactory, including new AI assistance to metaphactory’s semantic modeling capabilities, a Vocabulary Mapping Editor, and improvements to the ontology review process. 

AI-assisted semantic knowledge modeling

The latest metaphactory release introduces a powerful AI modeling agent to support the modeling lifecycle from idea to implementation. The new built-in AI assistant allows users to build, edit and manage semantic knowledge models in metaphactory with enhanced speed and precision. 

The agent is capable of executing a myriad of tasks, including performing quality checks, making recommendations for classes, identifying opportunities for reuse and more—thereby accelerating the modeling process from start to finish. Domain experts and business users can readily contribute to the model thanks to the guidance of the intelligent agent in an easy-to-use chat interface.

Additionally, the agent follows proven methodologies, like the metaphacts Semantic Knowledge Modeling Guidelines and the Linked Open Terms methodology, and leverages OWL and SHACL open standards for crucial interoperability and flexibility.

This feature is immediately available to all metaphactory users as part of this release. If you are a current metaphactory customer, speak with your account manager to start leveraging AI assistance.

The modeling agent is powered by metis, our new knowledge-driven AI platform on top of metaphactory, which will be generally available in an upcoming full launch. 

Tap into metaphactory’s powerful data mapping capabilities

metaphactory now offers the seamless mapping of physical data elements (like database tables, columns, or JSON objects and properties) to their logical counterparts in your ontology-based data models (classes, relations and attributes).

The feature enables you to:

• Answer key questions like “Where is data for the ‘Order’ class stored?” across all your systems.
• Understand how updates to logical models affect physical implementations — and vice versa.
• Catch unexpected changes in physical schemas to notify downstream processes (e.g., any ETL).

By connecting conceptual models, logical data models, and physical implementations in a unified metadata graph, organizations can drive smarter governance and architectural decisions, better aligning business vision with IT execution.

AI-powered mapping

Additionally, there is now AI-powered support that can help bootstrap these mappings and accelerate adoption and reduce manual effort, saving you significant time in the mapping process.

Introducing the Vocabulary Mapping Editor

As part of this release, the Vocabulary Mapping Editor is now generally available. The Vocabulary Mapping Editor enables alignment between two vocabularies, such as internal terminology and community standards, and offers enhanced flexibility by separating mappings from their source vocabularies. Rather than remaining embedded within a vocabulary, mappings can now be managed as a separate asset and be created and maintained independently of the source vocabulary’s ownership or lifecycle state. 

The new structure improves clarity, simplifies lifecycle handling, and supports more flexible downstream consumption. Additionally, this update brings improved usability and performance.

New commenting feature enhances ontology review process

New commenting capabilities make ontology reviews more collaborative and efficient. Reviewers can now leave comments directly on individual classes, relations and attributes. 

Comments can be marked as resolved, and elements can be filtered based on unresolved discussions, making it easier to track feedback and stay on top of all assets.

Beyond these highlights, this metaphactory release delivers numerous other enhancements. View the full release notes [link] or contact us for more details.

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