MākuSafe Named ACORD InsurTech Innovation Challenge Winner 2019!
November 1, 2019
MākuSafe Wins Global InsurTech Innovation Challenge at ACORD Connect Boston Finals
West Des Moines, Iowa - MākuSafe, an Iowa-based technology company, was named the 2019 ACORD Insurtech Innovation Challenge (AIIC) winner in Boston. The competition brought three regional challenge winners to the ACORD Connect event to pitch their insurance innovations to conference attendees for the final leg of the competition. Gabriel Glynn, founder of MākuSafe, accepted the award at a ceremony on October 31, 2019.
Insurtech startups from around the world competed in regional competitions held in New York, London and Chicago earlier this year. MākuSafe won the Chicago regional in June, securing the company a spot to compete in Boston as one of three finalists, and ultimately winning the competition.
As the winner of the competition, MākuSafe earned a $15,000 cash prize and the opportunity to share its workforce wearable technology, promoted by ACORD. All regional finalists also received a membership to ACORD, distribution and promotion of a whitepaper and tickets to ACORD Connect 2019.
“This is such an incredible honor and a testament to the hard work of our team. Big thanks to ACORD for giving MākuSafe, and the greater insurtech community, the opportunity for this kind of partnership, said Gabriel Glynn, CEO and co-founder of MākuSafe. “Our product is now deployed in six states, and we’ve more than doubled our team this year. The prize money and additional exposure provided by ACORD will go a long way in accelerating our growth into 2020.”
Each day around the world, more than 1,000 people die in workplace accidents. In the US alone, more than $1.2 billion is paid out every week in workers compensation claims. MākuSafe addresses these issues with their award-winning technology solution.
Their patented wearable armband device gathers real-time data, including near-misses, environmental leading indicators and hazardous human motion data. It works in tandem with their AI-driven cloud platform, MākuSmart. Together, they identify trends and generate alerts to improve worker health, safety and productivity before incidents and injuries occur.
Data gathered by MākuSafe devices also helps insurance companies engage with their worker’s compensation policyholders to mitigate risks and hazards before claims result.
MākuSafe is an Insurtech Safety Data & Analytics company based in America's Heartland. Our mission is to improve worker health, safety, and productivity while reducing worker compensation claims and mitigating workplace risks. Founded in 2016, MākuSafe developed proprietary wearable technology that gathers real-time environmental and motion data from workers. Our SaaS cloud platform, MākuSmart, then uses machine learning to identify high-risk trends in the facility. Our award-winning technology auto-records near-misses, proactively targets resources to specific conditions & occurrences, and streamlines compliance reporting. MākuSafe delivers its solution through insurers as well as direct to end users. The mission that guides MākuSafe is making the world a safer place through use of technology and data.
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ACORD (Association for Cooperative Operations Research and Development) is the global standards-setting body for the insurance and related financial services industries. ACORD facilitates fast, accurate data exchange, and efficient workflows through the development of electronic standards, standardized forms, and tools to support their use. ACORD members worldwide include hundreds of insurance and reinsurance companies, agents and brokers, software providers, financial services organizations and industry associations. ACORD maintains offices in New York and London. Learn more at www.acord.org
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.