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FogHorn Systems is the developer of an edge intelligence software designed to deliver real time industrial grade analytics to resource constrained edge devices. The company's software augments edge computing with machine learning to bring intelligence to industrial Internet-of-Things (IoT) which works with mainstream IoT platforms in the public cloud and can be integrated with Amazon Web Services (AWS), Google Cloud, and Microsoft Azure.
The FogHorn platform brings the analytics and machine learning to the on-premises edge environment and enables applications for advanced monitoring and diagnostics, machine performance optimization, proactive maintenance and operational intelligence use cases. Their platform is ideally suited for OEM's, systems integrators, and end customers in manufacturing, power and water, oil and gas, renewable energy, mining, transportation, healthcare, retail, as well as connected infrastructure and connected vehicle applications.
FogHorn's Lightning Edge Intelligence product portfolio bring their IoT and edge computing as close to the source of streaming sensor data as possible. The platform is compact and works to deliver low latency for onsite data processing, real-time analytics, ML and AI capabilities.

Map of where in data stream FogHorn places their Lightning Edge Intelligence platform.
The features in Lightning Edge Intelligence include VEL Complex Event Processor which is designed for industrial use and to perform real-time analytics of disparate streams of sensor data, works to optimize constrained and diverse compute environment with limited to no connectivity, works to simplify interoperability with existing OT systems, and handles machine learning pre and post processing which includes cleansing, filtering, normalizing and contextualizing streaming sensor data. Edgified Machine Learning, or EdgeML, is a learning model which, once trained, enables iterative closed-loop edge to cloud machine learning cycle and works to execute neural net models in constrained compute models.
Other features include their FogHorn Manager which is a browser-based tool allowing configuration and custom application across the platform; REX, a sensor traffic debug tool; VIZ, which allows the user to visualize real-time streams and to validate sensors, troubleshoot input sources, see the results of analytic expressions and view the output of machine learning algorithms; and VEL Studio which allows users to author and debug analytic expressions through a drag and drop interface and includes commonly used templates.
FogHorn's Lightning Mobile brings their edge computing platform to Android-based mobile devices, which brings real-time analytiics, machine learning and AI to field operations without relying on cloud connectivity.
FogHorn's revenue is a subscription cost based on the combination of selected software plan charges plus the infrastructure costs for the virtual machines running FogHorn's software. FogHorn's pricing structure varies depending on enterprise agreements or other discounts, but Microsoft's Azure Marketplace lists the starting cost for FogHorn's software at $1.40/hour. They list three recommended virtual machines: the first offers 4 compute cores, with 7GB of RAM and 285GB of disk space for an added $0.24/hour; the second with 2 compute cores, 14GB of RAM and 135GB of disk space for an added $0.25/hour; and the third offering 8 compute cores, 14GB of RAM and 605GB of disk space for an aded $0.48/hour.
Based on this model, the pricing of FogHorn's platform ranges from approximately $1200 a month to $1400 a month.
Licensing and cloud services are a part of the revenue breakdown for FogHorn. The other portion, which does not have a fixed cost, is maintenance, professional services and training involved in the implementation and on-going use of their edge computing system. A breakdown of competitor Splunk's annual revenue shows their operational intelligence platform sees 33.4% of their annual revenue from maintenance, professional services and training.
Other competitors include Exosite, an enterprise IoT software company that helps manufacturers gain insight into their products and the people that use them; Ayla Networks, which also offers an IoT platform for device management; Splunk, which provides operational intelligence software to monitor, analyze and report real-time machine data; and Relayr, which offers an IoT platform for device manufacturers, app developers and software companies.