Togal AI
Paid ✓ VerifiedTogal AI automates construction takeoff and floor plan measurement, extracting quantities and dimensions from architectural drawings using AI.
📋 About Togal AI
Togal AI is an AI-powered construction takeoff platform that automates the measurement and quantity extraction process from architectural and engineering drawings. Construction estimators and project managers traditionally spend significant time manually measuring floor plans and counting items on construction drawings to produce quantity takeoffs — the input data needed for cost estimation. Togal replaces this manual process by automatically detecting, labeling, and measuring spaces, walls, openings, and other elements directly from uploaded PDF drawings.
The platform uses computer vision trained on construction drawing conventions to identify architectural elements and extract their dimensions without requiring the user to manually trace or click on each element. Users upload a drawing set and Togal produces a structured takeoff with area calculations, linear measurements, and item counts that can be reviewed, edited, and exported into estimation software or spreadsheets. The time saving is most significant on large, complex drawing sets where manual takeoff would consume days of estimator time.
Togal AI targets general contractors, subcontractors, and construction estimating teams across commercial, residential, and industrial construction. Pricing is enterprise and team-based, reflecting the professional productivity context and the integration needs of construction firms that rely on established estimation workflows. The platform integrates with common construction software including Procore and others, allowing takeoff data to flow into existing project management and estimation systems.
⚡ Key Features of Togal AI
Automated Quantity Takeoff
Togal ai analyzes uploaded construction drawings and automatically identifies, labels, and measures architectural elements — rooms, walls, openings, fixtures — to produce a structured quantity takeoff without manual tracing. The AI is trained on construction drawing conventions and can handle the variety of notation styles, scales, and drawing standards used across different architecture and engineering firms. Takeoff results include area calculations, linear measurements, and item counts organized by element type.
Floor Plan Recognition
The computer vision model recognizes floor plan layouts and automatically segments spaces by room type, producing labeled area measurements that match the drawing's intended spatial organization. Space recognition works across residential, commercial, and industrial drawing types and can handle multi-story building plans by processing each floor separately while maintaining project-level organization. Recognized spaces can be manually corrected or reclassified if the AI misidentifies a room type.
Drawing Set Management
Togal ai organizes uploaded drawing sets by project, with version tracking so estimators can compare takeoff results between drawing revisions and identify what has changed. Managing a multi-building or multi-phase project involves organizing many drawing files, and the project structure in togal ai keeps measurements associated with the correct drawing version and building component throughout the estimate lifecycle.
Review and Edit Workflow
After automated takeoff, estimators review results in an overlay interface that shows the AI's measurements on top of the original drawing, making it easy to visually verify accuracy and identify any elements the AI missed or misclassified. Individual measurements can be adjusted, additional elements added manually, and incorrect detections removed — the automated result serves as a fast first pass that a human estimator refines rather than approves blindly.
Export and Integration
Takeoff data can be exported to Excel and CSV formats for use in any estimation spreadsheet workflow, and Togal ai integrates with construction project management platforms including Procore to enable direct data transfer into project records. This integration reduces the manual data entry step between takeoff completion and estimate assembly, which is a common source of transcription errors in traditional workflows.
Comparison and Change Detection
Togal ai can compare takeoff results from two versions of the same drawing and highlight the differences — identifying added, removed, or modified elements between design revisions. This change detection is valuable during the design development phase when drawings are revised repeatedly and estimators need to update their quantities without re-running a full takeoff from scratch.
🎯 Use Cases for Togal AI
⚖️ Togal AI Pros & Cons
Advantages
- ✓Reduces quantity takeoff time from days to hours on complex drawing sets
- ✓Review-and-edit workflow maintains estimator control over final numbers rather than fully automating the output
- ✓Export and integration with common construction software fits into existing estimation workflows
- ✓Change detection between drawing versions saves significant re-work time during iterative design phases
Drawbacks
- ✗Enterprise pricing is a significant investment for small contractors with limited bid volume
- ✗AI accuracy varies on unconventional drawing formats or non-standard notation — manual review is still required
- ✗Only useful for the measurement step — does not handle pricing, labor rates, or full estimate assembly
- ✗Requires good-quality PDF drawings; low-resolution or hand-drawn plan scans reduce recognition accuracy
📖 How to Use Togal AI
Contact Togal through togal.ai to set up an account and discuss team or enterprise access.
Create a project and upload the construction drawing PDFs you need to take off.
Run the automated takeoff and wait for Togal to process and label the drawing elements.
Review the results in the overlay interface, correcting any misclassifications or adding missed elements.
Organize the verified measurements by trade or element type to match your estimation format.
Export to Excel or push data to your connected construction management platform for estimate assembly.
❓ Togal AI FAQ
Togal ai processes architectural and construction floor plan drawings in PDF format across residential, commercial, and industrial building types. Performance is best on clear, digital drawing sets — hand-drawn or low-resolution scanned plans may have lower recognition accuracy.
Togal ai automates the first-pass measurement step of quantity takeoff, not the estimating judgment. Estimators review and verify AI-generated measurements before they go into an estimate, and the pricing, labor, and assembly steps remain manual human-driven work.
Togal ai integrates with Procore and exports to Excel and CSV for compatibility with other estimation platforms. Check togal.ai for the current integration list as new platform connections are added.
Togal ai reports high accuracy on well-formatted digital drawing sets, with typical performance significantly faster than manual takeoff even accounting for review and correction time. Accuracy varies by drawing complexity and format — the review workflow is designed to catch and fix AI errors before they affect the estimate.
Yes, togal ai supports multi-story and multi-building project organization, processing each floor or building as a separate component while keeping all measurements organized under a single project. Drawing set uploads can include all floors and the results are organized accordingly.
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