IoT Startup FogHorn Systems CEO: Channel 'Critical Component' Of Next Generation Edge Software Platform

FogHorn Systems on Tuesday unveiled its next-generation edge intelligence software platform, which helps customers better integrate machine learning capabilities into their operational technology.

CEO David King said that systems integrators with specialized knowledge of OT play a "critical component" in consulting with and implementing the IoT platform for industrial customers.

"As companies push into the IIoT game it is creating new opportunities for consulting partners … customers don't just want to take big data and process it for insights, they want to take sensors and figure out how to make their industrial processes better," he told CRN. "It’s a very different set of businesses processes that IT systems integrators consultants can handle."

[Related: FogHorn Systems Lands $12 Million In Series A Funding As Company Strengthens Industrial IoT Offerings]

FogHorn’s industrial Internet of Things software stack combines technologies to blend sensor data from industrial machines with cloud-based management, analysis and machine learning capabilities.

The company, which landed $12 million in Series A funding in 2016, targets vertical markets like manufacturing, oil and gas, power and water, as well as smart building applications.

The Mountain View, Calif.-based company's next-generation industrial IoT software platform, Lightning ML, touts integrated machine learning capabilities and is universally compatible across all major industrial IoT systems.

With new machine learning capabilities, Lightning ML enables machine learning models to run on operational technology types of devices like programmable logic controllers, ruggedized industrial IoT gateways, and industrial PCs and servers – so that customers can generate machine learning insights.

King said that Lightning ML helps customers combine real-time streaming analytics and advanced machine learning capabilities on their industrial machines – but also supports ARM 32, a processor that is widely-used in OT control systems like programmable logic controllers and SCADA systems.

"The addition of FogHorn Lightning ML is a monumental leap forward in delivering on the promise of actionable insights for our IIoT customers," said King. "In the initial launch of FogHorn’s Lightning platform, we successfully miniaturized the massive computing capabilities previously available only in the cloud. This allows customers to run powerful, big data analytics directly on operations technology and IIoT devices right at the edge through our complex event processing analytics engine."

FogHorn said that its Lightning ML software platform could run entirely on premises or it can connect to any private or public cloud. The platform has a drag-and-drop authoring tool that abstracts away the complexities of any underlying IIoT deployment, allowing operators to focus on translating their domain expertise into meaningful analytics and machine learning insights.

"OT staff are domain experts in their respective industrial environments, but not necessarily experts in edge computing and advanced IT," said FogHorn CTO Sastry Malladi in a statement. "By giving them intuitive tools to automate, monitor and take action on their industrial data in real-time, operators can enhance situational awareness, prevent process failures and identify new efficiencies that lead to huge business benefits. This is a very different approach from other IT-centric solutions that fail to leverage the tribal knowledge of key OT experts."

According to King, in addition to integrating with larger IoT-focused industrial companies like GE, FogHorn sells branded solutions through larger systems integrators, and partners with solution providers, and IoT gateway and cloud providers to offer white-labeled services.

King said that he hopes to continue tightening the company's channel strategy around edge and automated machine response capabilities for industrial customers. "IoT, in general, is getting a lot more attention in the channel," he said.

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