Digital Guerilla

What previously took hours of manual column filtering, error highlighting, and cross-referencing in Excel now happens the moment data lands in Morta. The transformation is stark: before, each validation cycle meant opening spreadsheets, filtering columns one by one, and hoping the summary table stayed in sync. Now, validation columns show all errors colour-coded per row in real time, with no manual intervention.

By removing the human element from routine checks, the team eliminated the mistakes that inevitably crept into large-dataset validation. Pre-configured rules catch issues consistently regardless of who runs the check or which discipline’s data is being reviewed. Every discipline’s data is validated against the same centralised source tables — Uniclass 2015 PR classifications, Revit category mappings, and COBie schema requirements — and updates to source tables propagate to all validation checks automatically.

Design teams can now export data from Revit to Morta themselves and see results immediately, shifting quality assurance upstream. A summary table aggregates error counts and validation outcomes across all sheets and disciplines automatically, replacing the manual tracking that was previously maintained by hand. As Pawel puts it, this is still a work in progress — the goal is full automation where design teams validate independently before formal reviews, eliminating the need for specialist involvement in routine data quality checks.

Every time a Revit model needed validating, Pawel Kudosz faced the same grind. Link the models to a project template containing schedules. Export via DiRoots SheetLink into spreadsheets. Compile everything with Power Query. Override the pre-configured Excel files for Uniclass tables. Then the real work began: filtering each column individually, highlighting errors manually in yellow, and checking false positives one by one. For large models with thousands of elements across multiple disciplines, this was not just tedious — it was fragile. A summary table had to be maintained by hand to track error counts per sheet, and keeping it in sync with the actual validation results across multiple spreadsheets was an exercise in hope.

Excel had no native way to cross-reference against external source tables like Uniclass 2015 classifications or Revit category mappings. VLOOKUPs broke when data changed. Different disciplines submitted data in varying formats and levels of detail, and without automated enforcement, catching inconsistencies required exhaustive manual review of every submission. There was also no automated way to compare what was planned in the TIDP against what was actually uploaded to the CDE, or to reconcile data across multiple CDEs. These comparisons were done manually, if at all.

The key insight was simple: if the validation rules are already defined, why apply them by hand every time? Digital Guerilla set up Morta as their central validation platform, with pre-configured tables that validate data the moment it arrives. The export from Revit happens with a single click via DiRoots SheetLink — no more CSV files, no more Power Query compilation, no more overriding configuration files.

Once data lands in Morta, it’s checked automatically. The category column validates against a Revit categories source table. The COBie.type.category column checks against Uniclass 2015 PR. Classification codes are verified against another source table. Blanks in key fields are flagged instantly. A dedicated validations column shows all errors colour-coded per row — red for failures, green for passes — replacing the manual filtering and yellow highlighting entirely.

For more complex validations that Morta’s native rules can’t handle, Python scripts fill the gaps, and the team is working with Morta on additional solutions for edge cases. Beyond Revit data, Digital Guerilla also built TIDP and CDE validation into the workflow. Connected to two CDEs, the system catches what’s listed in the TIDP but never uploaded, and vice versa. It can even compare a contractor’s CDE against a client’s CDE to surface discrepancies. The long-term vision is self-service: design teams exporting from Revit to Morta themselves, seeing validation results immediately, catching errors before formal reviews rather than during them.

Pawel designed the workflow to be as simple as possible for end users while maintaining rigorous data quality standards. The DiRoots SheetLink plugin was configured to map Revit parameters to the corresponding Morta columns — once set up, the export is a single click from within Revit, and data lands in the correct table with validation results appearing immediately.

The upfront investment was in configuring Morta tables with the correct column types, validation rules, and cross-references to source tables before any data was imported. That investment pays off on every subsequent import, which requires zero additional configuration. The workflow integrates with the team’s existing toolset — DiRoots for Revit, Autodesk Construction Cloud, and SharePoint — so no new software had to be introduced beyond Morta itself. For validation logic beyond Morta’s native capabilities, the team developed Python scripts and continues working with Morta on solutions for edge cases. The system is designed for handoff: once the Morta tables and DiRoots mappings are configured, anyone can run the export and see validation results without specialist knowledge.