Province vs Togal.ai: 2026 Comparison
Togal measures the plans. Province reads the set.
Togal.ai is built to automate quantity takeoff — rooms, walls, and areas measured from PDF plans in minutes. Province is built to read the full governing set, surfacing conflicts, drafting RFIs, and generating citation-backed scopes across drawings, specs, and addenda.
Togal.ai is the superior choice for automated quantity takeoff — measuring rooms, walls, areas, and counts from PDF plan sets in minutes for estimators. Province excels as a preconstruction document intelligence platform built for general contractors who need the full set read — particularly citation-backed constructability reviews, automated scope-of-work generation, and cross-document conflict detection across drawings, specs, and addenda.
- Your bottleneck is quantity takeoff — measuring areas, lengths, and counts off PDF plans.
- Estimators want a fast, self-serve tool to bid more projects in less time.
- You need calibrated measurement output that feeds your estimating spreadsheet.
- You need the full set understood — drawings, specs, and addenda — not just quantities measured.
- You want citation-backed scopes of work, constructability reviews, and RFIs drafted from real conflicts.
- You need drawing-versus-spec discrepancies and missing scope flagged before pricing.
One measures the quantities. One reads the set.
| Capability | Province (AI precon document intelligence) | Togal.ai (AI takeoff & estimating) |
|---|---|---|
| Automated quantity takeoff | Not the focus | Yes |
| Reads specifications & contracts | Yes | Limited |
| Citation-backed answers to the set | Yes | Partial |
| Automated constructability review | Yes | |
| Scope-of-work generation | Citation-traced | From takeoff |
| Cross-document conflict detection | Yes | |
| RFI drafting from conflicts | Yes | |
| Responsibility matrix | Yes | |
| Same-day turnaround analysis | Yes | Self-serve |
Takeoff tells you how much. It doesn't tell you what's wrong.
Reads, not just measures. Province reads the full set and understands what they require, so it can flag conflicts and missing scope, not just count quantities.
Every output cited to the page. Province anchors each finding and scope line to its exact sheet and spec section, so the answer is verifiable.
The deliverables before the bid. Constructability reviews, severity-ranked RFIs, division-by-division scopes, and a responsibility matrix — same-day.
Province vs Togal.ai, answered.
Is Province better than Togal.ai?
Province is better for general contractors who need the full set read for constructability reviews, scopes, and RFIs. Togal.ai is better for estimators whose main need is fast, automated quantity takeoff. Many teams use a takeoff tool and Province together because they solve different problems.
What is the difference between Province and Togal.ai?
Togal.ai automates quantity takeoff — measuring rooms, walls, areas, and counts from PDF plans. Province is a document intelligence platform that reads drawings, specs, and addenda to generate citation-backed scopes, draft RFIs, run constructability reviews, and detect conflicts across the set.
Is Province cheaper than Togal.ai?
Togal.ai is reported at roughly $199 to $299 per user per month depending on plan. Province is priced per engagement and quote-based, with no per-seat license to manage. Request a quote from Province to compare against your team size and document volume.
Can Province replace Togal.ai?
Province replaces the document-review and scope work, but it is not a quantity-takeoff tool. If your bottleneck is measuring quantities off plans, keep Togal.ai for takeoff and use Province for constructability, scopes, RFIs, and conflict detection across the full set.
Who should use Togal.ai instead of Province?
Togal.ai is the better fit for estimators whose primary workflow is quantity takeoff — fast, accurate measurement of areas, lengths, and counts from PDF plans to support cost modeling — and who do not need full-set constructability review or citation-backed scope generation.
Stop reading the set.
Start asking it.
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