How AI takeoffs actually work for general contractors.

The bottleneck.

A general contractor preparing a commercial bid spends most of the bid week measuring. Square feet of drywall. Cubic yards of concrete. Linear feet of pipe. Counts of fixtures across forty floor plans. The estimator either prints the drawings and uses a scale ruler or, more commonly in 2026, traces areas on PDFs in a digital takeoff tool. For a single mid-sized commercial project the work runs twelve to forty hours, and a five percent error in concrete volume on a real bid is fifty thousand dollars left on the table.

Every step downstream depends on the quantities being right. Pricing is unit cost times quantity. Labor is production rate times quantity. Subcontractor scopes are cross-checked against quantity. If the takeoff is wrong, the bid is wrong, and the project either loses money for two years or never wins in the first place. The reason AI tools matter at this step is that quantity measurement is the most rote, error-prone, time-intensive part of the process and the part where compute can plausibly do an estimator-grade job.

What changed in the last eighteen months.

Three categories of tools now handle takeoff work, in increasing order of automation. The first is the established generation: PlanSwift, Bluebeam Revu, On-Screen Takeoff. These are still dominant in the market and have rule-based automation features, but they keep the estimator's hand on every measurement. The second is the integrated PM-platform feature: Procore now offers Automated Area Takeoff, a machine-learning feature generally available for flooring, concrete, roofing, and self-perform general contractors, that detects room outlines from a floor plan with one click and supports auto-count for repeated symbols, with output flowing directly into Procore budgets and financials.

The third category is the AI-first specialist. Togal.AI uses computer vision trained specifically on architectural plans to detect and label rooms, walls, doors, and windows. A peer-reviewed University of Kansas study by Marulanda and colleagues measured Togal seventy-six percent faster than On-Screen Takeoff on a fire-station architectural test case, with takeoff accuracy within a five percent margin; on a more complex reflected-ceiling-plan case the speedup narrowed to twenty-three percent. Togal's Coastal Construction case study reports fourteen and a half hours saved per plan set after switching, totaling roughly thirteen thousand nine hundred hours and about one million dollars in cost savings across the first year. STACK, Kreo, and BuildVision occupy adjacent positions with different strengths in multi-trade coverage, BIM-first workflows, and broad takeoff categories. The category as a whole has crossed the line from technology demo to production tool.

What the workflow actually looks like.

With an AI-first tool, the estimator uploads a plan set in PDF or image format. The tool auto-organizes hundreds of sheets in seconds. With one click, the AI runs across every plan: it detects rooms and computes their area, perimeter, and feature counts. For a forty-page commercial set, the AI's core compute is a twelve-minute operation. The full workflow, including the human review step described next, brings the total to a few hours of estimator time on a job that previously consumed days.

The estimator then reviews the AI output. The first pass on a real plan set is rarely perfect: the AI may misread a hatched area, miss a small alcove, or mislabel a fixture. The estimator corrects these, and the tool learns from the corrections within the project. For repetitive elements, an image-based search lets the estimator draw a box around one fire-sprinkler head and have the tool find every matching instance across the whole set, which replaces the most tedious counting work. Quantities then export to whatever the firm uses to price: a spreadsheet, the integrated estimating module, or directly back into the project management platform.

The shift is not the AI replacing the estimator. The estimator's judgment still drives the bid. The shift is that the estimator spends two to four hours on what previously took most of a bid week, and spends the recovered time on the parts of the bid where judgment matters most: scope clarification, subcontractor leveling, and risk pricing.

Where the integrations matter.

A takeoff tool that produces quantities in a spreadsheet is useful. A takeoff tool whose quantities flow automatically into the project management platform's budget and then into the accounting system's job cost is meaningfully better, because every retyped number is a chance to introduce error and every manual handoff is friction the estimator pays for in time.

Procore Estimating handles the takeoff-to-budget flow natively because it lives inside Procore. Togal.AI lives in the Procore Marketplace and exports quantities back to Procore Estimating or to Excel. The accounting-system side of the loop is where construction-software middleware like Agave matters. Agave provides a configured connection between project management platforms and contractor ERP systems, with module-by-module scope control: Core for projects and cost codes, AP for invoices, AR for owner billing. The Workforce module is opt-in, so an organization that wants project cost data flowing without exposing payroll can stop at AP and AR.

The bigger payoff arrives once the integration loop closes. With actual field quantities flowing back into the project management platform from a workforce-tracking tool, and historical project costs accessible through the ERP integration, an estimator pricing the next bid can compare current quantities against historical actuals on comparable projects. The estimate gets calibrated by reality on every cycle. That is the destination state. The takeoff tool is the entry point.

What to evaluate before adopting.

Five questions matter more than the marketing pages.

• What formats does the tool actually read. Most bid packages arrive as PDF; some as DWG; a growing minority as Revit. A 2D-only tool covers most cases but blocks BIM-heavy work; a 3D-capable tool adds cost and complexity. Match the tool to the project mix.
• Where do quantities go after takeoff. Direct integration with the firm's existing estimating tool or project management platform is worth more than raw speed. A faster takeoff that creates a manual data-entry step downstream is not actually faster.
• Architectural-heavy or multi-trade. Some tools are stronger on architectural scopes (rooms, areas, finishes) and weaker on MEP. Others are designed for multi-trade workflows with broader symbol libraries. The right tool depends on whether the firm self-performs across many trades or focuses on a narrower scope.
• What does it cost against what it saves. An estimator at a $50–$75 burdened hourly rate, saving ten hours per takeoff, is a $500–$750 saving per bid. Published list prices for AI-first takeoff tools sit roughly between $175 and $300 per user per month for the standard plans (Kreo Pro at $175, BuildVision Pro and Togal in the $299 range), with higher per-user pricing for tools sold as add-ons to existing platforms (STACK Floor Plan AI at $899 per user). The math pays back on the first or second bid in any active month, but only if the tool is actually used; a license that sits unused costs the same as one that runs ten takeoffs.
• Does the team have the time to adopt it well. Configuration matters. Setting up the firm's cost codes, common room types, and export mappings to match the existing pricing flow takes one to two weeks of estimator attention. A tool deployed without that attention will produce quantities the team does not trust and will be quietly abandoned within a quarter.

How Rarefied Earth thinks about this work.

The firm's posture in construction technology is the same as in the bridge-engineering work that started it: structure the engagement around the questions a practicing engineer or estimator actually asks, not around a technology demo. Tool selection, configuration, integration with the existing stack, training, and the operational follow-through that determines whether a tool gets used or abandoned are all engineering work in their own right. The deliverable is not a tool license. The deliverable is a takeoff workflow that runs on Tuesday morning when a bid is due Friday, and whose output the estimator trusts well enough to put a number on it.

For general contractors evaluating where to start, the lowest-friction path is almost always the integrated PM-platform feature first. If the firm already uses Procore, enabling the Estimating module and configuring it against the firm's cost codes proves the concept on real bids in a few weeks. The AI-first specialist tools layer on top of that and pay for themselves the moment the firm has more bid volume than estimator hours. The accounting-system integration is the longer-horizon play that turns the takeoff tool into a feedback loop instead of a point solution.

Sources and further reading.

Related work.

The methodology that runs through this work, structuring deliverables around the questions practitioners actually ask, is the same one that produced the firm's PCI Journal pile-bent restoration research. The construction technology applications and the structural research are two expressions of the same posture, applied to different problems.