Beck Technology and Togal.AI Announce Partnership and Future Integration with DESTINI Estimator

Beck Technology, a preconstruction data lifecycle company, and Togal.AI, a machine-learning takeoff software, announce their partnership. The partnership is the first phase of a future integration planned between Togal.AI and DESTINI Estimator; an integrated construction estimating software. The partnership teams up both companies to improve the speed and quality of 2D takeoff while simultaneously building a construction estimate. The upcoming integration is slated to be completed in 2022.

Togal.AI can interpret plans within a minimum of 97% accuracy through their innovative use of AIA measurement standards and machine-learning algorithms. Beck Technology plans to incorporate this efficient workflow into the DESTINI Estimator estimating software so preconstruction professionals can spend less time completing manual takeoff and more time on high-value activities like data analysis and “what-if” calculations.

The partnership is paving the way for a reduction of takeoff tasks to be completed by up to 90%.

From Togal.AI

“Our partnership with Beck Technology means the preconstruction phase can be completed faster than ever and more projects can be pursued,” said Patrick Hughes, President at Togal.AI. “The construction industry thrives on accuracy. By having Togal.AI integrated directly into DESTINI Estimator we are able to reduce the time waste of manual takeoff, manual data entry, and allow technology to assist in catching details that may be overlooked.”

From Beck Technology

“Artificial intelligence is not new to the construction industry but the way Togal.AI has applied AI to takeoff is truly innovative and adds enormous value,” said Stewart Carroll, President at Beck Technology. “One of the more time-consuming and high-risk tasks for an estimator is the takeoff process and our upcoming integration will drastically cut the time and risk associated with accurate takeoff. It supports Beck Technology’s efforts with global quantification by providing a trusted source of data. We believe items of cost should be quantified irrespective of whether they came from 2D takeoff, 3D takeoff, parametrically, or a hard-coded value.”

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