Togal.AI

Name: Togal.AI
Brand: Togal.AI
Rating: 4.8 (51 reviews)

The AI-powered pre-construction takeoff software built BY estimators, FOR estimators

Est 2019|Valuation $50M|Raised $17.5M|24 Ref Customers

LinkedIn 7K|Web traffic 124K|FTEs 65|HQ Miami, Florida, US

Published Oct 7, 2026

01Common complaints

- When a fully integrated estimating and proposal generation system is required: competitors that emphasize combined takeoff and estimating workflows may be a better fit for single-system requirements. - When structural or concrete-heavy quantity surveying (volumes, rebar calculations) is a primary requirement: review feedback indicates these capabilities may be limited. - When workflows depend primarily on elevation-driven takeoffs: at least one reviewer reported issues with elevation sheets. - When the procurement process requires publicly documented security certifications (SOC 2/ISO) and the vendor cannot provide required documentation. - When the organization requires robust assembly-building and advanced formula frameworks inside the tool without using additional systems.

Deal disqualifiers (poor fit)

Organizations requiring advanced structural takeoffs (e.g., rebar weight, concrete volume) or highly trade-specific estimating automation not present in the product.
Organizations seeking a single platform that includes assemblies, detailed estimating, and proposal generation without third-party integration.
Organizations with strict compliance requirements that necessitate publicly documented vendor certifications when such documentation is not provided.

Issues and limitations evidenced in reviews

Multi-tab drawing loading problems reported by multiple users.
Feature gaps: assemblies, advanced material calculations, and improved spreadsheet integration are frequently requested.
Difficulty distinguishing some wall types (for example, different stud sizes) has been reported as a limitation in some use cases.
Exterior work automation was reported as unsupported by at least one reviewer focused on painting.

Vendor-acknowledged limitations and roadmap

Public sources show ongoing product updates and customer responsiveness, but a detailed public roadmap with delivery dates was not found.

Scale limitations

No public performance or SLA documentation located; some reviewers report slow performance. Procurement teams should stress-test the platform with representative large plan sets and multi-user concurrency scenarios.

02Why they buy

Unique selling points supported by customer feedback

Time reductions for certain takeoff scenarios and fewer manual steps reported by multiple reviewers.
Ease of use relative to some legacy tools, with reviewers noting a short learning curve for specific workflows.
Excel export capabilities are cited as valuable for integrating takeoff results into estimating processes.
Positive onboarding and support experiences are reported by multiple reviewers.

Unique selling points that require validation

Vendor-reported accuracy and speed metrics (e.g., 98% accuracy, 80% faster) should be validated against the organization’s plan sets, trades, and measurement criteria.

Areas where competitors may have advantages

Integrated estimating and proposal generation workflows.
Mature assembly and cost-database workflows and deep customization options.

03Field reports

Review platform signal (G2)

- Togal.AI is very highly rated on G2, indicating generally positive reviewer sentiment for the use cases represented. The G2 "Pros & Cons" roll-up highlights common positives such as ease of use, time savings, and estimating support; it also notes negatives such as missing features, bugs, and performance issues. #### Positive review excerpts (G2) - Reviewers note usability and Excel export capabilities and reference ongoing product updates. - Several reviewers reported material productivity improvements after initial setup, indicating the product reached partial completion on plans with limited manual work. - Reviewers emphasized value for large projects and daily use cases. #### Negative/critical review excerpts (G2) - Some reviewers report workflow-impacting bugs (for example, issues when opening drawing sheets in multiple tabs where drawings do not load properly). - Reviewers describe feature gaps and trade-specific limitations, such as inability to perform a takeoff from a selected area on a sheet, issues with elevation drawings, and navigation friction that can require multiple tabs. - Requests for assemblies, improved spreadsheet integration, and more advanced measurement/material tools appear among critical feedback.

Trustpilot signal

Trustpilot contains negative feedback, indicating that at least some customers perceived a mismatch between expectations and delivered functionality, specifically around advanced quantity surveying features.

Interpretation: G2’s larger sample suggests generally positive satisfaction for floor-plan takeoffs and certain trades; Trustpilot feedback and G2 critiques indicate potential mismatches for structural/concrete-heavy estimating requirements.

Why customers selected Togal.AI (as suggested by reviews)

Common themes in reviewer feedback include:

Reduced manual steps and time savings for certain takeoff scenarios.
Ability to export quantities to Excel and organize plan/takeoff data for downstream pricing.
Positive onboarding and support experiences cited by multiple reviewers.

Why some customers might leave / churn risk factors

Based on negative feedback themes:

Requirement for a full estimating suite (assemblies, proposals) rather than a takeoff-focused tool.
Need for advanced trade-specific calculations (e.g., structural rebar weight or concrete volume estimation) not supported by the product as described in reviews.
Bugs or performance problems that affect large-plan workflows.

Vendor/press-highlighted outcomes

Press coverage and vendor statements describe customer outcomes that claim substantial time and cost savings. These outcomes were presented via press articles citing vendor statements; independent methodology or audit was not available. Treat such outcomes as directional and validate in a pilot.

Partner ecosystem and integrations (indicative "case study" signal)

Partner announcements reference availability and integration with established estimating platforms; partner materials include partner-stated accuracy metrics for floor plans. These materials are promotional and should be validated in pilots using organizational plan sets.
Historical partner announcements referenced planned integrations with estimating platforms. Buyers should verify current integration status and available features during evaluation.

Mixed results / operational caveats

No publicly visible narratives of large-scale failed implementations were located in the reviewed sources; however, reviewer content suggests that complex or irregular drawings may require manual adjustments and that certain drawing types (e.g., elevations) may underperform.

04Best fit

Company size

Likely best fit: organizations ranging from small subcontractors up through large contractors, with estimating teams that process frequent bids and would benefit from time reductions in takeoffs.

Industries / verticals

Commercial construction, general contracting, and subcontracting trades.
Review evidence indicates adoption in painting and wallcovering trade workflows and in renovation takeoffs; vendor materials position the product broadly for construction estimating.

Roles and personas

Decision makers: Preconstruction Director, Chief Estimator, VP of Operations, Estimating Manager.
Daily users: Estimators, takeoff specialists, and project staff supporting pricing.

Pain points Togal addresses

Time-consuming manual takeoffs and repetitive tracing/counting tasks.
Need to export quantities to spreadsheets for pricing.
Collaboration friction across distributed estimating teams and external stakeholders.

Qualification criteria (good fit)

Organizations that primarily need fast, repeatable floor-plan takeoffs (rooms/areas/walls/counts) and can operationalize human review and correction of AI outputs.
Teams that value cloud collaboration and external sharing.

05The pitch

What the product does (objective value proposition)

Togal.AI is a cloud-based construction takeoff platform that uses machine learning models to detect, label, and measure elements on plan sets (primarily architectural floor plans). The vendor positions the product as an AI-assisted tool to reduce manual tracing and counting and shorten the time required for quantity takeoffs; outputs can be exported for estimating workflows. The product includes an in-app conversational feature (Togal.CHAT) for querying plans and an AI-driven image/symbol search capability for locating elements within drawings. Key vendor-reported claims emphasize improved accuracy and faster takeoffs; the vendor has not disclosed full methodology behind those figures.

Target market and positioning

- **Primary users:** construction estimators, preconstruction teams, subcontractor estimators (notably trades such as painting/wallcovering based on reviewer roles). - **Positioning:** An AI-assisted automation layer intended to reduce time spent on takeoffs; the vendor positions the product as complementary to downstream estimating systems. - **Typical buying centers:** estimating managers, preconstruction directors, operations leaders at subcontractors and general contractors.

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