Helonic vs Tuuli
Two AI platforms for construction drawing QA/QC, one built on proprietary AI with PM integrations, the other on firm-adaptive learning from past project outcomes.
Quick summary
Choose Helonic if:
- You want proprietary AI built for construction drawing accuracy
- You need native Procore and Autodesk integration
- You are a GC, owner, or sub managing large drawing sets
- You want broad detection: clashes, code, MEP, structural
- You need issues to flow into RFIs automatically
Choose Tuuli if:
- You want QC that learns from your firm's past RFIs and change orders
- Consistent enforcement of firm-specific standards is a priority
- You are an architecture or engineering firm focused on design QA
- You value SOC 2 Type 1 compliance out of the box
- You want to capture institutional knowledge as staff turn over
Feature comparison
| Feature | Helonic | Tuuli |
|---|---|---|
| Automated issue detection | ||
| Proprietary AI model | ||
| Learns from past project outcomes | ||
| Firm-specific standard enforcement | ||
| Code compliance checking | 380+ codes | |
| Cross-discipline coordination | ||
| Procore integration | ||
| Autodesk integration | ||
| RFI generation | ||
| Issue traceability | By AI confidence scoring | To source clause/sheet |
| SOC 2 compliance | Type II | Type 1 |
| Target audience | GCs, owners, subs | Architects, engineers |
Two different AI approaches
Both Helonic and Tuuli automate construction drawing QA/QC with AI. They share the same goal, catch issues before they reach the field, but take fundamentally different approaches to how they find those issues and who they are built for.
Helonic uses a proprietary AI model built specifically for construction drawings. Every drawing is analyzed by Helonic's purpose-built AI, which has been trained to understand construction drawing conventions, code requirements, and cross-discipline coordination patterns. This approach catches coordination conflicts, code violations, structural concerns, and MEP issues across the full spectrum, without needing historical project data to start.
Tuuli learns from your firm's history. It analyzes past RFIs, permit comments, and change orders to identify patterns specific to your firm and project types. Over time, it adapts its QC checks based on what has actually gone wrong on your past projects, rather than relying solely on general code provisions. This is powerful for firms with years of project data and recurring issue patterns.
The audience split is meaningful. Tuuli is designed by architects, for architects and engineers doing design-phase QA/QC. It enforces firm-specific drafting standards and captures institutional knowledge. Helonic targets the construction side, GCs, owners, and subcontractors who need to review incoming drawing sets, detect cross-discipline conflicts, and push issues into Procore or Autodesk as RFIs.
Integration ecosystems differ significantly. Helonic connects natively to Procore and Autodesk, so detected issues flow directly into your existing project management and RFI workflows, and is SOC 2 Type II compliant. Tuuli focuses on being a self-contained QA/QC layer within the design workflow, with SOC 2 Type 1 compliance and enterprise-grade security for firms handling sensitive project data.
Frequently Asked Questions
How does Tuuli's learning approach compare to Helonic's proprietary AI analysis?
Which platform is better for general contractors?
Can Tuuli integrate with Procore or Autodesk?
Which is better for enforcing firm-specific drafting standards?
Can architects and GCs on the same project use both tools?
Milind Sagaram
Co-founder & CEO, HelonicMilind is the co-founder and CEO of Helonic, where he leads product and go-to-market for AI-powered construction drawing analysis. He works closely with general contractors, project managers, estimators, and owners to understand how drawing quality drives project outcomes - and where AI can reduce RFIs, change orders, and rework. Milind has interviewed hundreds of construction professionals across project delivery roles, from preconstruction estimators at ENR top-400 contractors to facilities directors at institutional owners, and uses those conversations to shape both product direction and the way Helonic talks about the work.
- Construction project delivery and preconstruction
- RFI and change order economics
- Owner and GC workflows for drawing QA/QC
- Estimating risk and bid-stage scope assessment
How this page was researched: This comparison reflects the documented capabilities of Helonic and Tuuli as of 2026, contrasting Helonic's proprietary drawing AI with Tuuli's firm-adaptive learning from past RFIs and change orders. Feature assessments are based on each product's public documentation and Helonic's own review of the workflows described.
Last reviewed by Milind Sagaram · May 2026
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