London-registered Soter Analytics has raised $12 million in a Series A funding round. The company uses a combination of wearable technology and AI-powered coaching programmes to help workers avoid musculoskeletal problems, e.g. injuries to muscles, bones, tendons, and nerves. The funding will be used to press forward with international expansion plans. To date, the firm has raised $13.8 million.
No one enjoys sitting on the injured reserve list, certainly not from a work-related issue. And yet, more than 50 percent of workers in the EU report being sidelined due to injuries accrued at the daily grind. In fact, yours truly wears a pair of pressure gloves in order to avoid aching hands at the end of banging out up to 14 news items in one day.
By tracking major back and shoulder movements, Soter uses AI-driven computer vision technologies and wearables to help employers keep staff on the up and up by identifying and helping prevent manual handling injuries across a wide range of industries including warehousing, manufacturing, and construction.
The firm counts Travis Perkins, Wincanton, and Merck Animal Health in the UK; Giant Eagle Supermarkets, Coca-Cola, and Gap in the US; and Woolworths and Roy Hill in Australia.
“Today marks an important milestone for Soter Analytics and our mission to empower organisations to make their workplace safer. Our bespoke technology provides an end-to-end safety solution through AI and machine learning, and this fundraise shows that our investors and partners have recognised the strength of our product,” explained co-founder Matthew Hart. “This fresh capital will allow us to invest in research and development and work alongside organisations to help them improve workplace safety, decrease employee turnover, and enable injured workers return to work faster.”
Soter Analytics’ $12 million Series A round was led by round led by AV8 Ventures, with OTB Ventures, btov Industrial Technologies Fund, and Verve Ventures participating. Soter Analytics has previously been backed by Startup Wise Guys.