Falkonry Edge Analyzer Enables Predictive Analysis On Edge Devices

Oct. 21, 2019
Edge Analyzer enables non-data scientists to create and deploy predictive operations in cloud, on premise and at the edge.

Falkonry, Inc. launches the Falkonry Edge Analyzer, a portable self-contained engine that enables customers to deploy predictive analysis on edge devices for low latency applications in disconnected environments or close to data sources. The new Edge Analyzer is available as part of Falkonry’s “pre-packaged” machine learning system, Falkonry LRS.

Falkonry LRS enables operations teams to create and deploy predictive analytics in the cloud, on premise or on the edge without requiring data scientists. The automated feature learning solves the most complex problem of applying machine learning on time series data saving time and building accurate predictive models. The explanation feature gives insight into model results, quantifying signal contribution and enabling SMEs to perform root cause analysis.

Edge Analyzers can be created in Falkonry LRS and transported for installation in remote or mobile environments. Minimal resource requirements allow for operation in constrained environments. They are configurable for high availability and can tolerate sensor and network outages. Use of containers enables runtime to be insulated from other processing activities. Each Edge Analyzer can be used to monitor multiple edge endpoints, and several Edge Analyzers can be deployed on a single computer to support multiple assessments.  Each Edge Analyzer includes a perpetual use license.