The Speckle website also uses Workflows for high-level solution areas—for example project dashboards and progress tracking, present and review models, and exchange design data. Here, each page is a detailed, repeatable workflow you can follow in the product.
Common foundation
All workflows in this section assume a shared baseline for how data is stored and evolved:What is a workflow?
A workflow in this section is not a single feature or connector. It is a repeatable pattern that combines multiple capabilities to achieve a specific outcome in a defined context. Each workflow answers:- What outcome does this achieve?
- What capabilities are composed?
- In what context is this used?
Workflow guides
Start from the outcome you want, not only the tool you use. Each guide below follows a pattern (observation, evaluation, transformation, extraction, or reconstruction): the first sentence describes the pattern; the rest is what that guide walks through. These are composable—you might chain evaluation into reconstruction, or transformation before extraction.Design review
Observation — Understand and review model data without modifying it. Saved views, federation, markups, and issues for structured design reviews.
Model validation
Evaluation — Assess model data against rules or criteria to produce signal. Intelligence dashboards with Property Checker and Model Validation against your rulesets.
Grasshopper componentised pipeline
Transformation — Modify, restructure, or derive new data from existing models. Split large definitions into modules that hand off data through Speckle models.
Revit room data extraction
Extraction — Use model data outside Speckle for reporting, analytics, or integration. Pull room data from Revit with SpecklePy for Pandas, Power BI, or other systems.
Mapping to native systems
Reconstruction — Reinterpret Speckle data into native elements in a target system. Map geometry and data to native families and types. Coming soon.