Asset Mechanics publishes System Cards to provide transparency about our methods, the validation of reference class models, and the limits of their applicability within the public sector.
Our documentation explains:
- How RCF-AI and other models are structured
- How reference class validation was conducted
- How performance was evaluated
- What limitations and conditions apply
This supports transparency about AI models in the public sector and contributes to informed decision-making in the early stages of projects.
- Read the System Card RCF-AI Dike Reinforcement Estimations
- Read the System Card RCF-AI Land Exploitation risk
Additional Documentation
- Validation standard: Empirically validated risks(background)
- Pilot case: RCF-AI driven dike cost estimations (background and application)
- Knowledge session: Macro economic risks in land development projects(background and application)
- Services: Reference Class Forecasting with AI for large projects(why and how we support this)
Version Control
System Cards are published with version identifiers. The latest version is always shown at the top of the document, including the date and, where relevant, context for the changes.
