Use Cases
Metapad empowers organizations to model, simulate, and understand complex systems. Here are some of the ways our customers use the platform.
Enterprise Architecture & Transformation
Model your enterprise as a connected system — capabilities, applications, data flows, technology, ownership — so you can plan transformation with impact analysis instead of guesswork. The architecture stops being slides that go stale and becomes a living artifact every stakeholder can read.
- Visualize dependencies between business capabilities and IT systems
- Plan transformations with full impact analysis before committing
- Maintain a living architecture model instead of slides that decay
- Align EA, business, and IT stakeholders around one shared view
Supply Chain Modeling
Map your supply chain end-to-end — multi-tier suppliers, facilities, products, flows, risks — and simulate disruptions before they hit production. The same model serves operational analysis and regulatory reporting.
- Map multi-tier supplier networks across geographies and products
- Simulate demand shocks, supplier failures, and resilience scenarios
- Identify single points of failure and concentration risk
- Document supply chains for LkSG, CSRD, and EU due-diligence reporting
Business Process Management
Capture processes with full semantic context — not just steps, but the systems, data, and people behind them — so process design connects to the rest of the enterprise rather than living in an isolated BPM silo.
- Document processes with their full operational and IT context
- Identify automation opportunities by tracing real dependencies
- Run "what-if" simulations before reorganizing
- Support audit, compliance, and operational excellence reviews
Knowledge Management
Turn institutional knowledge into a queryable graph — who knows what, who has done what, what depends on what — that AI assistants can reason over reliably and that survives staff turnover.
- Capture and share organizational knowledge across silos
- Connect experts, expertise, and the systems they touch
- Enable natural-language and AI-powered queries with grounded context
- Onboard new team members with structured, current knowledge
Data Governance
Model your data landscape alongside the business context that makes it meaningful — domains, ownership, lineage, policies, quality rules — so governance becomes an active practice instead of a static registry.
- Map data flows and lineage across systems and domains
- Assign clear ownership, accountability, and stewardship
- Define and enforce data policies and quality rules
- Meet GDPR, AI Act, and data mesh requirements with documented evidence
Digital Twin Development
Build a living digital representation of a physical or organizational system — start as a lightweight prototype, evolve into a connected twin that mirrors reality, simulates futures, and feeds external dashboards or 3D viewers via API.
- Start as a prototype with no infrastructure commitment
- Connect live data when you're ready (sensors, ERP, custom systems)
- Run scenarios and what-if analyses without real-world risk
- Serve as the semantic layer behind visualizations and ops platforms