MākuSafe Featured in Industry Week & EHS Today

By Staff

January 25, 2019

In a recent article examining startups in the industrial safety space, MākuSafe was lauded as one of the successful advanced technologies to change the way companies monitor and hopefully prevent industrial accidents. The article examined several innovative startups and technologies hoping to reduce injuries and preventable accidents in the workplace. Here's what they had to say about MakuSafe:

"Various startups have been experimenting with advanced technologies such as IoT and machine learning to effectively predict accidents and therefore prevent them from happening. US-based startup MākuSafe has succeeded. The company's proprietary wearable technology gathers real-time environmental and motion data from workers in industries such as manufacturing, agriculture, and logistics, then interprets the data using Machine Learning to identify high-risk trends.

The system auto-records near-misses proactively targets resources to specific conditions and occurrences and streamlines compliance reporting. Not only does the MākuSmart dashboard help safety managers increase efficiency, but insurance carriers can also use the data collected by the wearables to create more accurate P&C policies for businesses and access detailed information for workers' compensation policies. It's also an effective tool for insurance brokers looking to implement risk control strategies and reduce client loss trends."

We love seeing a focus on worker safety. By leveraging technology, we can provide the actionable insights companies need to help reduce the number of incidents each year and make sure workers get home safe to their families.

The story also appeared in EHS Today

Read the full article

About MākuSafe

MākuSafe was formed by a powerful team of software, hardware and data engineers in an effort to prove that workplaces around the globe can be made safer by gathering environmental data around workers WHILE they work. Using analytics and machine learning technology we can turn that data into predictors so that accidents can be stopped before they happen.

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