SUNNYVALE, Calif. & ORLANDO, Fla.--(BUSINESS WIRE)--Falkonry, Inc. today announced the launch of its Falkonry Edge Analyzer while attending the Gartner Data and Analytics Summit. The Edge Analyzer is 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 leading “pre-packaged” machine learning system, Falkonry LRS. Falkonry LRS is now the industry’s first predictive operations product that enables operations teams to create and deploy predictive analytics in the cloud or on-premises or on the edge - without requiring data scientists.
“Many organizations can benefit from a packaged analytics application that includes embedded machine learning capabilities, especially when pursuing a common and well-defined advanced analytics problem, such as price optimization or fraud detection,” write Peter Krensky, Sr. Principal, Analyst and Carlie Idoine, Sr. Director Analyst at Gartner in the March 2018 research, How Data Science Teams Leverage Machine Learning and Other Advanced Analytics.
“Before using Falkonry, companies often found themselves stuck in proof of concepts without a clear path for scaling to production,” said Dr. Nikunj Mehta, Founder and CEO of Falkonry. “The ability for operations teams to create and deploy predictive models at the edge and on premises has addressed the integration and skills gap challenges, while realizing five to ten times annual ROI.”
Prediction & Explanation
Falkonry LRS enables operations teams to discover, explain and predict behaviors that matter 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 allows 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.
“Real-time asset monitoring and predictive analytics is important to Fluke,” said Oliver Sturrock, CTO of Fluke Digital Systems. “Falkonry’s solution scores high in terms of architecture, scalability and flexibility to deploy in the cloud or at the edge for real-time insights.”
Live Demonstration at Hannover Messe
Falkonry will demonstrate the new Edge Analyzer in the Siemens booth [Hall 9 - Booth D35] at the upcoming Hannover Messe show on April 3 in Hannover, Germany. Attendees will see how powerful machine learning models can be deployed on lightweight edge devices to analyze large number of signals and predict complex conditions. These predictions can be used to create alerts for operational control systems or dashboards.
Falkonry is the leading provider of predictive operations technology for companies looking to achieve significant improvements in the uptime, yield, quality and safety of their operations. Falkonry enables operations teams to discover, explain and predict behaviors that matter, without requiring data scientists. Falkonry’s “pre-packaged” machine learning system, Falkonry LRS, complements a user’s domain expertise with predictive operations technology to more deeply understand their operations, and can scale across assets, processes and operations. For more information about Falkonry and its products, please visit www.falkonry.com