How to Get Started with Orbyfy™️
A simple, three-step process to unlock physics-grounded climate insights for your assets, portfolios and infrastructure.
1. Define your geographic scope
First, pinpoint the physical footprint you want to analyze. This can be as narrow as a single address or as broad as an entire metropolitan area.
Addresses & Parcels: Individual homes, commercial buildings, substations, data centers
Neighborhoods & ZIP Code Zones: Aggregated clusters for portfolio-level assessment
City or County Boundaries: Comprehensive urban or regional digital twins
Critical Infrastructure Corridors: Transmission lines, pipelines, road networks
Output: A geospatial template (GeoJSON, Shapefile or CSV) containing the coordinates and extents for all points, polygons or line-features under study.
2. Select your climate scenario
Next, choose the hazard and scenario you want to model. Orbyfy supports many different climate scenarios.
For Utilities
High-intensity sparks from vegetation impingement on distribution conductors
Extreme wind-driven ember transport across transmission corridors
For Banks & Insurers
1-in-100-year flood or storm surge events across loan and policy portfolios
Scenario stress-tests under elevated temperature, wind or precipitation extremes
For Real-Estate & Developers
“What-if” future storm intensities for code-compliant building designs
Flood-proofing analysis: levee breach, rapid snowmelt, urban drainage failure
Output: A scenario manifest—detailing hazard type, return period or forecast window, and any custom physics-AI parameters.
3. Identify your key outputs
Finally, tell us what insights you need to drive decisions. Our Physics-AI engine will translate climate forces into impact metrics, maps and risk scores. Common outputs include:
Asset & Portfolio Metrics
Proxy building material & code assumptions
ASCE-compliant design specifications & loadings
Structural vulnerability profiles
Scenario exceedance probabilities
Portfolio climate VaR tables
Geospatial Deliverables
Flood-depth & fire-intensity raster layers
Geolocated damage categorizations (CSV/GeoJSON)
Time-series animations of hazard progression
Interactive dashboard with time-slider control
API endpoints for automated GIS or BI ingestion
Risk & Financial KPIs
Damage & risk scorecards
Climate-adjusted probability of default (PD)
Loss given default (LGD)
Expected loss % (HAZUS, ASCE 24-14)
Return periods & exceedance curves
Output: A tailored package—exportable CSV/GeoJSON layers, interactive browser visualizer, API endpoints, and tabular KPI reports—for seamless integration into your workflows.