SafeGuard, an AI-Powered Safety Solution for Construction, Raises $8 Million

SafeGuard’stechnology identifies hazardous patterns, generates risk predictions, and enforces preemptive measures in real time and cross-industry.

SafeGuard is an international Safety-Tech company that uses machine learning to predict and prevent accidents on construction sites. Today, the startup announced an $8 million Series A funding round.

Hi-tech investors Ron Zuckerman and Hillel Kobrinsk lead the round. Also participating are Ronen Peled, Yehuda Rachamim, Zemach Hammerman, and Wall Street investor Jeffrey Schoenfeld.

SafeGuard is also announcing the creation of Otoos, a daughter company that will focus exclusively on the construction industry in the US. In addition, SafeGuard will expand the use of its end-to-end decision-making solution to other industries needing better safety technology.

Safety needs to improve

Jobsite injuries and deaths plague the construction industry. In the US alone, three workers die every day, and a worker gets injured every three minutes. Because 90% of all construction accidents are due to human error, fatal and non-fatal injuries continue to rise despite equipment, safety apps, and training advances.

Other jobs also carry disproportionate risk. Warehousing, for example, accounts for almost 8% of the 2.8 million non-fatal workplace injuries and illnesses reported by private industry employers.

“Unfortunately, our field is focused on digitizing compliance rather than innovating decision-support tools, but the reality is that compliance does not assure safety,” said Izhak Paz, CEO and founder of SafeGuard.

Automated decision-making

SafeGuard’s technology prevents accidents in real-time with its automated decision-making platform. SafeGuard is the only platform that collects data simultaneously from multiple sources: cameras, sensors, drones, statistic analysis, open data, and big data.

The algorithms identify on-site human error patterns and use AI to predict the probability of an accident occurring. The system then converts predictive data into proactive measures that enforce good decision-making beforehand. 

For example, SafeGuard machine learning capabilities can identify and stop a construction worker on the verge of making a mistake in real time. They prevent an accident by locking the worker out of the hazardous area. The same technology works in other industries as it aims to solve accidents at the root.

By implementing SafeGuard’s solution, a leading international construction firm lowered the number of fatal accidents from ten in 2016-2019 to just one over the last three years.

“SafeGuard’s automated decision-support platform gives project managers peace of mind by providing them with a powerful tool to protect on-site workers from human errors, thereby preventing accidents in real-time,” lead investor Hillel Kobrinsky concluded.

Source: SafeGuard, Tel Aviv, Israel, April 17, 2023