metaphactory

metaphactory is an enterprise knowledge graph platform developed by metaphacts that transforms raw organizational data into consumable, contextual, and actionable knowledge. Designed to drive knowledge democratization across the enterprise, it combines semantic knowledge modeling, insights and knowledge discovery, and AI-driven capabilities to support continuous decision intelligence. The platform is suited for a wide range of users — from knowledge graph engineers and domain experts to business users — enabling all stakeholders to contribute to and benefit from a shared, semantically enriched information architecture.

By leveraging neuro-symbolic integration and open W3C standards, metaphactory provides a flexible, trustworthy, and explainable foundation for AI initiatives. It supports both top-down and bottom-up approaches to knowledge management, offering fast time to value and risk mitigation compared to building custom solutions or relying on rigid, proprietary products.

Core Value Propositions

• Unlock AI initiatives across the enterprise by enriching them with rich, machine-interpretable semantics, adding a layer of trust and transparency to previously opaque solutions.
• Capture hidden expert knowledge by enabling business users and domain experts to encode their domain expertise in reusable and extensible semantic models.
• Transform raw data into human- and machine-interpretable knowledge using FAIR Data standards and semantic enrichment.
• Empower end users to experience and consume knowledge in context, abstracting from the underlying complexity of the knowledge graph.
• Scale business decisions with explainable and actionable insights delivered through intuitive discovery interfaces and AI-driven analytics.
• Build a connected and contextualized enterprise information architecture grounded in a semantic model.

Semantic Knowledge Modeling

• Visual semantic modeling interface provides a user-friendly environment for creating, importing, extending, editing, exploring, visualizing, and documenting semantic models using an accessible visual language suitable for both technical and non-technical users.
• The visual language translates to core elements of OWL and SHACL, producing semantic models based on open W3C modeling and validation standards.
• Metadata curation and model cataloging support search and full model governance.
• Tight integration between semantic models and vocabularies allows classes in the modeling interface to be linked to controlled vocabularies.
• Vocabulary and taxonomy management via an intuitive, form-based interface supports creation and editing of SKOS vocabularies, hierarchical lists (hypernyms and hyponyms), multilingual synonyms and symbols, and performant tree visualization of term hierarchies.
• Import and export of vocabularies created in external tools, with vocabulary cataloging, versioning via Git, and metadata curation.
• Data catalog integration supports creation, management, or import of dataset metadata, with support for DCAT and Dublin Core standards, and exposure of dataset metadata in search interfaces, knowledge panels, and custom dashboards.
• Integration with public ontologies and vocabularies — including HCLSIG/PharmaOntology, MeSH, IDMP, STW thesaurus, Bibframe, schema.org, ISO15926-14, FIBO, and others — allows bootstrapping, extending, or implementing these as the basis for proprietary knowledge models.
• Publishing of semantic models via API and web application, with SSO integration, a templating engine for tailored presentation to different user groups, and flexible open formats for sharing within the community or for pre-competitive research.
• AI-assisted semantic modeling simplifies and enhances the modeling process.

Collaboration and Asset Governance

• Collaborative environment supports an agile and iterative modeling process, allowing all stakeholders — from knowledge graph engineers and taxonomists to domain experts and business users — to contribute equally without requiring external expert tools or causing synchronization issues.
• Cataloging, import/export, versioning, and metadata management for semantic models, vocabularies, and datasets to foster reuse and build scalable governance processes.
• Lifecycle and change management via a versioning mechanism and editorial workflow, enabling users to change model status (e.g., from 'In development' to 'In review'), lock or unlock models, and communicate feedback.
• Git integration for asset versioning, supporting embedding of knowledge modeling into CI/CD and governance processes.
• Notification functionality sends updates to users or downstream systems on actions or status changes related to semantic models or vocabularies.
• Detailed provenance documentation of an asset's creation, ownership, history, and changes, supporting traceability and quality preservation.
• Roles and permissions management enforces security and ensures accountability and traceability.

Insights and Knowledge Discovery

• AI-native apps and conversational interfaces grounded in a semantic model enable precise information retrieval and the uncovering of hidden connections within data.
• Extraction of valuable insights and their transformation into actionable knowledge.
• Model-driven approach to application building that powers advanced and innovative solutions.
• Rapid prototyping of applications to validate new use cases, saving significant time and financial investment.
• Features include conversational interfaces, search, visualization, interactive exploration, authoring, and personal and collaborative knowledge organization.

Knowledge Graph Management and AI Capabilities

• Data access services, federation across multiple data sources, middleware services, data and query engineering, and data quality management.
• Neuro-symbolic integration natively combines symbolic AI (knowledge graphs) with neural AI tools, supporting a human-in-the-loop approach for trustworthy and explainable AI.

metaphactory is compatible with a range of graph databases and supports enterprise deployment requirements including SSO integration. The platform has been adopted across industries including pharma and life sciences, engineering and manufacturing, automotive, aerospace, and cultural heritage, with customers such as Boehringer Ingelheim and institutions involved in the Sloane Collection project leveraging it for enterprise knowledge graph initiatives.