| Contributor
For decades, the construction industry’s least glamorous step has been the “takeoff.” This is the painstaking process of counting and measuring every stud, sheet of drywall, window, and baseboard from 2D plans, quietly devouring time and budgets. In a sector already squeezed by rising land prices, material costs, and labor shortages, those weeks of manual quantification represent millions of dollars in overhead that never swing a hammer.
Togal AI argues that if we want to lower the price of building homes in America, we should start here. The company’s core product automates that entire process in seconds using its own computer-vision algorithm trained on millions of labeled construction plans. Could transforming the most tedious step in construction be the key to unlocking affordable housing at scale?
Cloud-Based Muscle Meets Job-Site Reality
Legacy estimating software largely mimics the old ruler and roller routine on a PDF, and is still reliant on human clicks and on-premise downloads. Togal’s platform is cloud-based, which makes a surprisingly big difference. Contractors upload massive plan sets without the email and zip shuffle, collaborators work from a shared link rather than juggling file versions, and AI handles the grunt work of drawing polygons, counting fixtures, and calculating linear footage.
Patrick Murphy, the founder and CEO, likens the switch to going from a manual screwdriver to a power drill. Most users, he says, realize that the tool is not replacing their judgment but freeing them to spend hours on higher-value decisions such as re-engineering a bid to save a client money instead of measuring baseboards all afternoon.
Proof in the Numbers
The cost savings claims are not theoretical. Miami-based Coastal Construction reported saving roughly 10,000 labor hours, which equates to about one million dollars, in its first year on Togal. A North Carolina painting contractor increased its bidding capacity by 215% in just two months, while a Florida flooring firm cut a 30-story high-rise takeoff from two weeks to a few hours, winning what became one of its most profitable jobs.
“If AI can automate all that, now you can use that extra time to do the more valuable things. Maybe re-engineering the job to save 10%, picking different materials, better subcontractors,” Murphy illustrates.
Those wins matter beyond balance sheets. If weeks of pre-construction estimating can be compressed into hours, project timelines shorten, carrying costs drop, and more bids reach the market. Murphy argues that eliminating those hidden delays can bend the cost curve of housing by as much as 20%, enough to make a measurable impact on America’s affordability crisis.
Talking to the Blueprints
A more recent feature, Togal Chat, integrates GPT-style large language models so contractors can interrogate thousands of pages of spec books, change orders, and RFIs as if they were asking a colleague. A superintendent can type, “What kind of grill is specified in the plans and what outlet do they require?” and get an instant, cited answer instead of rifling through binders or chasing the architect.
That conversational access to the fine print not only saves keystrokes, but also reduces miscommunication, which is often the silent culprit behind change-order disputes and blown budgets.
Teaching an Old Industry New Tricks
Adoption still takes effort. Many estimators cling to familiar tools. Some fear being automated out of a job, while others expect AI to “do their laundry and wash the car,” as Murphy jokes. “The first step is the hardest. Every step after that gets easier. AI is here to stay, and we’re still in the early innings. People haven’t missed the boat yet.”
Togal counters with free live onboarding sessions every Tuesday and encourages even senior executives to get hands-on so they grasp the technology’s limits and strengths. Once they do, loyalty tends to stick. “Give us eight hours on the platform and you will not go back,” Murphy claims, a sentiment echoed by users who lament the decades they spent clicking corners on PDFs.
Beyond measuring drywall, Togal’s roadmap stretches into precise customization. The team is training its models to learn each user’s regional construction preferences, such as stud spacing in Miami compared with Seattle, so estimates become personalized and pricing more accurate over time.
Murphy’s five-year vision sounds bold yet practical. A homeowner could type an address, a budget, and a preferred style such as “Mediterranean three-bedroom with garage” and receive a full code-compliant construction set that includes plumbing diagrams and electrical plans in minutes. City permitting will still need to catch up, but the technical groundwork is already underway.
A Wake-Up Call for Builders
Housing affordability will not be solved by subsidies alone. Compressing multiyear pre-construction cycles into days or weeks and trimming 20% off project costs could expand supply faster than most policy interventions. For seasoned builders, ignoring AI-driven estimating tools like Togal may soon look as shortsighted as ignoring Excel in the 1990s.
Togal AI’s growth from thousands of users across dozens of countries to winning the Associated General Contractors’ “Innovation of the Year” award suggests the experiment has already left the lab. The larger question is whether the rest of the construction sector will pick up the power drill or continue turning the manual screwdriver while housing costs climb.
