FogHorn Systems, a start-up based in Mountain View, California, released its Lightning ML edge intelligence software for the Industrial Internet of Things (IIoT).
The company said its Lightning ML brings the power of machine learning at the edge in three ways:
- Leverages existing models and algorithms: can execute proprietary algorithms and machine learning models on live data streams produced physical assets and industrial control systems
- Makes machine learning OT-accessible: offer tools to generate machine learning insights
- Runs in tiny software footprint: Lightning ML platform requires less than 256MB of memory footprint.
Lightning ML supports all x86-based IIoT gateways and OT systems as well as ARM32 OT control systems (like PLCs and DCSs). It also supports the newest generation of small footprint Raspberry Pi derivative IIoT gateways. The FogHorn Lightning ML software platform can run entirely on premise or connect to any private cloud or public cloud environment.
“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 (OT) and IIoT devices right at the edge through our complex event processing (CEP) analytics engine. With the introduction of Lightning ML, we now offer customers the game changing combination of real-time streaming analytics and advanced machine learning capabilities powered by our high-performance CEP engine,” said said FogHorn CEO David C. King.
- In May 2017, FogHorn Systems announced today that it had raised additional Series A funding from Dell Technologies Capital and Saudi Aramco Energy Ventures (SAEV). The extended funding brings FogHorn’s total Series A round to $15 million, excluding the conversion of $2.5 million in seed funding. Dell Technologies Capital added to its initial Series A investment. Saudi Aramco Energy Ventures is a new investor in the company.
