Every drywall estimator has run the same gauntlet. You measure the square footage off the plans perfectly, clean lines, correct scale, no arguing with the number. Then you have to turn that square footage into an actual bill of materials: how many sheets, how much track, how many screws per sheet, how many boxes of mud, how many rolls of tape, all adjusted for a waste factor that is really just an educated guess dressed up as a formula. Get any one of those conversions wrong and the crew is either standing around waiting on a supply run or sitting on three unopened pallets nobody ordered.

That gap, between measuring a wall and actually knowing what it takes to build it, is exactly what a product update out this week is aimed at closing.

Togal.AI, the Miami based construction estimating software company, launched Assemblies, a feature that connects measured quantities straight from a takeoff to the materials, labor, and equipment needed to build them, starting with drywall. According to coverage of the launch, estimators build an assembly once, defining the materials, labor, and equipment for a given wall type along with the formulas that size them, and from then on, classifying a measured wall automatically triggers those quantity calculations, no separate spreadsheet required. Contractors can build their own assemblies from scratch or adapt templates to match how their shop already estimates, and Togal.AI is offering to help migrate existing assembly libraries out of PlanSwift or On-Screen Takeoff rather than asking a firm to rebuild years of refined formulas from zero. Founder and CEO Patrick Murphy framed the reasoning plainly: drywall is a good example of why construction estimating is so much harder than simply measuring a set of plans, since the actual complexity lives in everything that has to happen after the measurement is done.

The company's own history makes the framing land a little harder than it might from a generic AI vendor. Murphy, a former U.S. Congressman, built Togal.AI out of his family's multi-generational construction business after watching his grandfather run estimates with printed plans and a scale ruler, and returning from Congress to find the industry hadn't moved much past that. That is a founder who has personally stood at a plan table doing the exact conversion Assemblies is now trying to automate, which is a different kind of credibility than a platform built by people who have only ever seen a jobsite in a sales deck.

What is worth watching here is not really the drywall part. It is the fact that Togal.AI is explicitly framing this as the first of a series, a move toward trade specific logic baked into the software rather than one generic takeoff tool asked to serve every trade the same way. That is a meaningfully different bet than the one most estimating AI has made so far, which has largely been about reading a drawing faster and calling it done. A framing carpenter, an electrician, and a drywall sub are not measuring the same thing in the same way, and a tool that actually encodes each trade's own logic, its own waste factors, its own material relationships, is a narrower and harder product to build than a universal takeoff engine, which is presumably why it is showing up now as an expansion rather than a launch feature. It is the same instinct behind purpose built agents anywhere in construction: a model that understands the specific shape of one job does more for the person doing that job than a general purpose tool that technically covers everything and specializes in nothing.

None of this is a nine figure funding round or a jobsite robot, and it will not generate the same headline as an autonomous excavator. But estimators are not losing money on the parts of a bid that are dramatic. They are losing it in the quiet arithmetic between a measured wall and an ordered pallet, the exact seam a feature like this is built to close.

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