Why teams adopt it
Use it when validation rules must stay stable across iterations or across people—for repeatable QA, shared predicates and thresholds, and pass-rate comparison as versions ship.Core objects
Validation checks execute saved rules against tracked models when you run manually or when auto-run triggers on new versions. A rule can read properties on the object itself, on a related object such as the wall that hosts a door, or a calculated value. A result captures one completed run with scores, per-rule statuses, counts, and failing element links. History orders past results for a check so you can compare trends across versions.Quickstart
The end-to-end flow is the single setup path from authoring to result review.End-to-end flow
You need at least one published model version in the project.1
Open Run check
In the project sidebar, open Data Validation, then Run check.
2
Author or import rules
Use
WHERE / CHECK, or select Import IDS, Import COBie, or Import Speckle.3
Run preview
Validate filters on real data before save. Run Preview or
Ctrl+Enter / Cmd+Enter.4
Save
Set a name, optional description, scoped models, and manual or auto-run on new versions.
5
Track results
Open the check result page; expand rules and models to see filter-step counts when debugging
failures.
6
Share outcomes
Export BCF from result views where coordination tooling expects it.
After the first pass
For authoring details and run analysis, see Checks (including predicates and matching) and Viewing Results. To fetch check results and KPIs programmatically (GraphQL and Python), see Consuming Data Validation Results via GraphQL.Navigate from project sidebar
In the project sidebar:- Data Validation
- Run check — draft / preview without persisting yet
- Checks — saved checks (name and description editable; rules and scope frozen—see Checks)
Versions you can run against
Data Validation preview and saved-check runs need a version in the data format introduced in 2026.9. If preview does not load, publish a new version after the project has moved to the new format. See Speckle’s new data model.Progressive implementation sequence
Explore — run preview on real revisions first so scope errors show before saving (Run a first check). Persist — save against tracked models so reruns stay comparable over time (Operate checks over time, Practical review flow). Scale — set checks to auto-run so every new version is validated without anyone starting it (Validate incoming models automatically).Start here
Run and manage checks
Rules, predicates, preview, thresholds, saves, tracked models.
Validate every new version
Author a check once and let it run on each submission.
Interpret results
Latest versus history, statuses, drills.
Using dashboard widgets instead?
Dashboard widget validation is documented in Validation Widgets in
Dashboards.
Multi-model checks
A check that tracks more than one model is available on the Enterprise plan.
FAQ
Where did Project standards go?
Where did Project standards go?
Project standards are being retired, and the Data Validation sidebar shows Run check and
Checks only. Author and save checks instead; IDS and COBie imports now start a check. See
Project standards.
Do checks run automatically?
Do checks run automatically?
Checks can run in manual mode or auto-run on new model versions, depending on check trigger
settings.
Where do I inspect detailed outcomes?
Where do I inspect detailed outcomes?
Open the check detail page to inspect latest and historical rule outcomes. See Viewing
Results.
Can I still use the Model Validation widget?
Can I still use the Model Validation widget?
No, not any longer. The Model Validation widget is no longer supported. Use the Elements
table or Property checker in a dashboard, or a Data Validation check. Saved dashboards and
their data are kept. See Validation Widgets in
Dashboards.