Tech Startup TOGAL.AI Deploys Algorithms to Automate 2D Takeoffs
Automating some of the more tedious tasks in construction has been a target of machine learning for years, but the startup TOGAL.AI has zeroed in on one annoying task that has been overlooked. Calculating takeoffs on 2D drawings during bid prep often falls to an estimator, diligently drawing polygons to calculate how many door frames, light fixtures or square feet of carpet are needed.
TOGAL.AI’s system aims to automate that process. “When we look at our financials, our biggest piece of overhead is preconstruction,” says Patrick Murphy, CEO of TOGAL.AI and executive vice president of his family’s firm, Miami-based Coastal Construction. This work needs to get done whether you win or lose the bid, and it eats up time and money, says Murphy. “It takes seasoned estimators two or three days. But we built a series of algorithms—neural networks trained on past data—that can do that in minutes.”
“With today’s busy marketplace and tight labor force, our industry is forced to do more with less,” says Patrick J. Mc Gowan, CEO of East Rutherford, N.J.-based Mc Gowan Builders. “Being able to rely on new technologies like TOGAL.AI will allow us to focus on more significant tasks like value engineering and pricing.”
TOGAL.AI can ingest any JPG, PDF or CAD for 2D drawings, with no initial need to guide it. But an estimator is still kept in the loop. “Humans still do the pricing; this just speeds up the time-consuming piece,” Murphy says.
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