This Startup is Bringing AI to Construction to Enhance Safety and Optimize Project Management

Construction productivity levels are the lowest among all industries, and it's been that way for a while. Mckinsey reported in 2017 on the languishing growth of the construction sector’s labor-productivity, a mere 1% over the last two decades, compared to 3.6% in the world economy. In an effort to close that gap, Trusstor, an AI startup is building a holistic solution to bring full visibility to general contractors. 

Founded by Omri Sorek (CEO) and Ofer Simon (CTO), Trusstor is developing an AI based construction management hub for general and subcontractors management to optimize the entire building process while ensuring construction workers operate in the safest conditions possible.

By integrating real-time location systems, smart equipment and cutting edge artificial intelligence, Trusstor increases construction productivity and safety at scale. The company’s technology uses many multifunctional sensors placed within a construction site and on workers to track data. Trusstor enables quality data collecting and utilization for critical decision making- what they refer to as "Construction Intelligence." “This information could help alert and prevent injuries and accidents, common problems in the construction sector, amounting to millions in waste” explained Sorek.

“The first step of building a great product starts with a real understanding of the problem you’re trying to solve” shared Sorek. “We started researching and going over thousands of working logs, financial plans, budget versus actual, major issues in projects etc., across over 250 projects. In one particular project, we noticed $25 million spent on non-productive costs, close to 14% of the total project cost. From the safety aspect, there were over 3,000 safety violations and four fatalities in that project. Beyond the irreparable emotional damage, these safety issues accumulated to $1 million in safety violation related costs, all without accounting for costs associated with delayed delivery, tenants payment requirements, and fines that can reach millions per project.”

“Our goal is to gather data, and we do that by building end-user applications that answer the industry’s every-day needs and pain points” explained Simon. “Construction intelligence is a combination of AI and construction best practices to create a flow of data that feeds us with the best inputs. We’re creating a data lake of everything inside a construction site, from people to assets, harnesses, appliances and machinery, etc., with which we can draw insights to help general contractors optimize their building process, and predict productivity and safety issues.” By extracting features from the dataset, the startup plans to train a supervised machine learning algorithm to predict and forecast the likelihood of events in the worksite, for instance whether there will be a delay in a specific zone, or an accident to a specific employee in real time, with which it can take preventative measures.

In the first phase, the startup’s insights will be based on live data and will address real-time pain points in the construction site. As their data accumulates, they plan to implement the predictive aspect of construction intelligence. “When a general contractor plans their next building, we’ll be able to provide visibility on the roadmap of forecasted inefficiencies” added Sorek.

Trusstor raised a seed funding round in 2019 from a combination of venture capital and angel investors, and they’re already engaged with global Israel-based construction giants in paid pilot projects. The startup plans to use the funds to continue deploying their sensor fleet into worksites globally and develop their predictive algorithms by leveraging the unique dataset they’re collecting. In an industry comprised of over 150,000 companies globally, and where a disruption in labor-productivity inefficiency can generate an estimated $1.6 trillion in value, the startup is ushering in new intelligence to construction with seemingly unlimited potential.