Helonic vs Togal AI
Compare AI-powered clash detection and code compliance with AI-powered quantity takeoff.
Quick summary
Choose Helonic if:
- You need coordination and compliance analysis
- You want a proprietary AI trained on construction drawings
- You need code compliance checking
- You want automated RFI generation
- You need cross-discipline clash detection
Choose Togal AI if:
- You need automated quantity takeoff
- You want area measurements from PDFs
- You need cost estimation support
- You want space classification
- You need measurement accuracy
Feature comparison
| Feature | Helonic | Togal AI |
|---|---|---|
| Clash detection | ||
| Quantity takeoff | ||
| Code compliance | ||
| Area measurement | ||
| Cross-discipline analysis | ||
| Cost estimation | Supports | |
| AI-powered | ||
| Works with PDFs | ||
| RFI generation | ||
| Space classification |
Different AI applications
Both Helonic and Togal AI use artificial intelligence on construction PDFs, but they solve completely different problems.
Togal AI measures quantities and classifies spaces for estimating. It reads floor plans and automatically calculates areas, identifies room types, and generates takeoff data that feeds into cost estimation workflows. Estimators use Togal to price the work faster and more accurately.
Helonic analyzes drawings for coordination issues and code violations. It reviews drawing sets across disciplines to identify clashes, missing information, and building code non-compliance. Project teams use Helonic to verify the drawings are correct before pricing and construction begin.
These tools are complementary, not competing. Use Helonic to ensure the drawings are right, then use Togal AI to measure and price them. Better drawings lead to more accurate takeoffs.
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