BOQ Comparison & Cost Deviation Engine
Aligns design vs implementation BOQs, surfacing cost creep in week 2–3 instead of project close.
What was breaking
Comparing design BOQ against implementation BOQ was manual and error-prone. Small deviations across hundreds of items quietly compounded into $2–5M undetected cost overruns per project.
BOQ Deviation Engine
An AI alignment and deviation engine that reconciles mismatched BOQ formats, normalises units and visualises category-level variance with line-item traceability.
- Fuzzy structure alignment across formats
- Unit and terminology normalisation
- Category-level deviation analytics
- Heatmaps and high-variance alerts
- Line-item cost traceability
How it works
- 01
Align
Fuzzy matching reconciles items across different BOQ formats.
- 02
Normalise
Inconsistent units and terminology harmonised.
- 03
Detect
Category-level variance and high-deviation hot spots flagged.
- 04
Visualise
Heatmaps, percentage-change tables and executive summaries.
- 01
Align
Fuzzy matching reconciles items across different BOQ formats.
- 02
Normalise
Inconsistent units and terminology harmonised.
- 03
Detect
Category-level variance and high-deviation hot spots flagged.
- 04
Visualise
Heatmaps, percentage-change tables and executive summaries.
Before vs. after
| Metric | Before | After | Improvement |
|---|---|---|---|
| Reconciliation | 3–4 weeks | 2–3 days | 85% faster |
| Undetected variance | 3–5% pre-finalisation | <0.5% | Early detection |
| Finance confidence | Low during execution | Real-time visibility | Continuous |
What changed
- ✓Significant reconciliation time reduction
- ✓Cost overrun visibility in weeks 2–3 rather than at close
- ✓Detailed line-item traceability
- ✓Applied to 5 major projects ($200M+ in cost visibility)
Inside the build
Could this work for your team?
We adapt these blueprints to your domain, data and governance constraints — typically delivering a working prototype in weeks.