Silicon Valley startup named one of CRN’s 10 coolest IoT startups for 2016 and HPE Matter’s highest ranking IoT startup to watch in 2017.
Mountain View, CA (PRWEB) December 27, 2016
FogHorn™ Systems, a leading developer of “edge intelligence” software for industrial and commercial Internet of Things (IoT) applications, announced today that it has received recognition as a leading IoT startup by two major technology publications in December, 2016. The announcements topped off several significant company milestones of the last six months including $12 million in Series A Funding in July and the inaugural release of FogHorn Lightning, the company’s flagship software platform, in September.
On December 16, CRN Magazine officially recognized FogHorn for its wide-ranging solutions for OEMs, systems integrators and customers in vertical markets – such as smart cities, health care, retail and manufacturing – through its “edge intelligence” software.
According to the publication’s announcement, FogHorn’s software platform carries machine learning to the on-premise edge environment to prevent catastrophic failures in machines such as industrial pumps or wind turbines. “The company also provides a scalable edge analytics platform to enable real-time, on-site stream processing of sensor data from industrial machines.”
HPE Matter, a digital magazine produced by Hewlett Packard Enterprise in partnership with such notable publications as WIRED, The Telegraph, The Register and The Atlantic, announced what it considers to be the hottest IoT companies that will make the biggest splash in 2017 with FogHorn leading the field of eight companies recognized by the publication.
HPE Matter credits FogHorn with creating a “stack” of specialized software that ingests locally created sensor data which it then processes at the edge creating useful insights. By enabling enterprises to bring this intelligence to the edge, they can dramatically reduce bandwidth usage and latency which in turn accelerates decision-making. “FogHorn and its model is likely to be crucial to the success or failure of intelligent IoT projects,” the publication said.
FogHorn software can “communicate via the cloud to centralized management systems that use machine learning and advanced analytics.” By strategically using the cloud for selective operations rather than flooding the Internet with massive amounts of raw sensor data, enterprises can not only lower costs but also fine tune their operational intelligence, machine learning, predictive maintenance and enhance the overall usability of their assets.
“All of our hard work of the past two years is really paying off and the IoT industry has definitely taken notice,” said FogHorn CEO David C. King. “This recognition by CRN and HPE Matter indicates that our focus and commitment to intelligence at the edge is resonating with virtually every type of industrial enterprise from energy and manufacturing, to transportation and healthcare and everything in between.”
For additional information or a product demonstration
Visit the FogHorn web site at http://www.foghorn-systems.com or send an email to info(at)foghorn-systems(dot)com for an individual demonstration.
About FogHorn Systems
FogHorn is a leading developer of “edge intelligence” software for industrial and commercial IoT application solutions. FogHorn’s software platform brings the power of advanced analytics and machine learning to the on-premise edge environment enabling a new class of applications for advanced monitoring and diagnostics, machine performance optimization, proactive maintenance and operational intelligence use cases. FogHorn’s technology is ideally suited for OEMs, systems integrators and end customers in manufacturing, power and water, oil and gas, renewable energy, mining, transportation, healthcare, retail, as well as Smart Grid, Smart City, Smart Building and connected vehicle applications.
FogHorn Energy Forecasting Demo
FogHorn and Lightning are trademarks of FogHorn Systems. The names of actual companies and products mentioned herein may be the trademarks of their respective owners.
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