METAPHACTORY SOLUTION
Build a connected enterprise information architecture with a semantic model
A semantic layer at the core of your Enterprise Information Architecture allows you to create a data environment that is robust, adaptable and scalable.
Make insights-driven decisions
Optimizing processes for speed and efficiency becomes crucial as your IT landscape expands. A semantic model provides a comprehensive digital representation of your organization's information landscape, enabling you to understand and analyze the relationships between systems, processes and business objects. This clarity empowers your teams to make data-driven decisions, enhancing efficiency and reducing redundancies.
Manage risks effectively
Understanding dependencies between business objects, business processes and IT infrastructure is critical for risk mitigation, operational efficiency and regulatory compliance. A semantic model consolidates distributed information, helping you assess the impact of system migrations or integrations, system failures or regulatory changes in real time. With this insight, you can make proactive decisions, safeguard critical operations and ensure business continuity.
Plan for future growth
Expanding into new markets, integrating new products or adopting emerging technologies requires an agile and scalable information architecture. A semantic model ensures seamless interoperability, allowing you to incorporate new systems, tools and data sources without disrupting existing operations. By creating a unified, contextualized view of your enterprise information landscape, you can future-proof your organization and accelerate digital transformation.
Unlock explainable AI-powered insights with a semantic layer
A semantic layer at the core of your Enterprise Information Architecture allows you to create a data environment that is robust, adaptable and scalable.
Are struggling with fragmented, isolated data sources that make it difficult to power AI applications and retrieve reliable and explainable business insights? A semantic model will help you unify information distributed across your enterprise information landscape and enable AI agents with explicit facts, helping you answer critical questions in minutes. Metadata from new data sources can be integrated seamlessly and evolving user questions are handled effortlessly and dynamically. By providing structured, connected and contextualized enterprise knowledge, this approach ensures faster, more trustworthy decision-making and improves efficiency, transparency and strategic agility.

Your benefits with metaphactory
Proven solution
This American multinational food corporation leverages a metaphactory-driven Enterprise Information Architecture solution to save time and cost spent on analyzing their complex IT landscape of ERP systems when preparing for system migrations, upgrades, integration or consolidation and API publishing.
A deep-dive into metaphactory’s Enterprise Information Architecture solution
A semantic knowledge model to integrate enterprise information from many data sources and answer Enterprise Information Architecture-specific questions
A semantic layer of connected metadata…
Business critical information that describes business processes, business objects (the input & output of business processes), roles and responsibilities, IT systems and data products is explicitly defined, connected and mapped into a unified, coherent business object framework – the semantic model.

… to surface powerful AI-driven insights
A semantic layer at the core of your Enterprise Information Architecture empowers end users to answer complex questions, surface hidden insights and democratize knowledge across the enterprise.
Typically, such information is hosted across isolated systems, such as:
» Data catalogs & lineage tools
» Business glossary management tools
» Business continuity management tools
» Data governance & GxP compliance tools
» Business process modeling tools
» Master data management tools
» Enterprise architecture modeling tools
» Business management software, e.g., ERP or PLM systems
» Static documentation, e.g., using UML
While these systems are not replaced, the information they hold is seamlessly connected using virtual access (federation) or by materializing relevant metadata in the semantic layer. This provides a single source of truth for your enterprise information landscape, as well as a consistent and unified understanding of business objects, and is key to governing and shaping your Enterprise Information Architecture.
An LLM-powered AI agent allows end users to ask sophisticated questions in natural language and – because it is grounded in factual, explicit knowledge from the knowledge graph – returns context-sensitive, trustworthy and explainable insights. Alternatively, users can leverage a semantic search interface to interact with the data.
Typical questions your users will be able to get answers to within seconds are:
» Which IT systems contain information related to a specific business entity?
» Which business processes are affected by a system shutdown?
» Which business processes are most impacted by supply chain disruptions?
» What critical business risks arise from reliance on third-party data sources?
» Which IT systems would be impacted by a new data protection law?
See metaphactory for Enterprise Information Architecture in action





