FogHorn, a developer of Edge AI software for industrial and commercial Internet of Things (IoT) solutions, outlined plans to follow on the successful rollout of the Lightning Health & Safety Solution (LHSS) with more integrated solutions targeting edge AI deployments as it announced that it has received several awards and other recognition for its edge computing technology.
FogHorn’s Lightning Edge AI Platform and its customers received several industry accolades for delivering transformational business results for industrial and commercial organizations, as well as its edge-native artificial intelligence (AI) and IIoT platform:
● World Economic Forum: honored as a 2020 Technology Pioneer, a cohort including future headline-makers addressing global issues with cutting-edge technology.
● IoT World: recognized as the winner in the Best Edge Computing Solution category and a finalist in the Best Manufacturing IoT Deployment category for the Stanley Black and Decker vision-based measuring tape defect detection system. Saudi Aramco was recognized as the winner in Best Energy IoT Deployment for its Auto Well Space Out solution using the Lightning Edge AI Platform.
● Analytics Insight: listed as Most Promising IoT Startup to Watch in 2020.
● CRN: honored on the 2020 Emerging Vendors list in the IoT category.
● IoT Evolution: named IoT Product of the Year.
“Following our Series C funding round in February, we doubled down on innovation and expansion of our product portfolio to support existing and new customer needs, as demonstrated by the positive industry feedback and successful release of FogHorn’s Lightning Health & Safety Solution,” said David C. King, CEO of FogHorn. “Over the next six to 12 months, we look forward to expanding our Lightning Solutions offerings to span a variety of industry use cases, delivering out-of-the-box packages to help both industrial and commercial customers more rapidly deploy edge AI and immediately derive insights to solve critical problems.”
edge AI | FogHorn | IIoT | ML | systems integration