SymphonyAI Group acquires Azima Global
30/09/2019
SymphonyAI Group has recently announced the acquisition of Azima Global, a provider of machine condition monitoring and asset reliability solutions across several industrial verticals.SymphonyAI is building a group of leading companies that use artificial intelligence to transform business enterprises across several markets, including the industrial, retail, consumer, healthcare, financial services and media sectors. At the core of this is SymphonyAI’s artificial intelligence platform, eurekaAI, which drives actionable insights by applying machine learning to large datasets and on which SymphonyAI has already been developing applications focused on industrial predictive maintenance and process optimisation.
Over the past decade, Azima Global has built a suite of cloud-based machine diagnostic and analytic solutions, supported by a team of deep domain experts, that together deliver highly accurate and timely visibility into the condition of industrial assets at scale. The company has been providing these solutions to leading companies in the oil & gas, chemical, food manufacturing and other industries.
In joining the SymphonyAI Group of companies, Azima Global, renamed Symphony AzimaAI, will develop industry-pioneering products that leverage one of the largest dynamic mechanical fault mode datasets and combine automated machine condition diagnostic data and plant-level process data, to deliver enterprise-level AI-driven predictive asset health and performance management solutions. Customers will realise both strategic and economic value through the reduction of unplanned downtime, maintenance and capital expenditures and improvements in machine reliability and throughput. These next-generation solutions represent a new paradigm in the Industrial Internet of Things (IIoT) and will redefine performance benchmarks in a market segment that has been stalled by the limitations of traditional enterprise research planning (ERP) and computerised management maintenance systems (CMMSs).
