Ontology deal to provide EXFO with real-time network topology discovery and service-chain mapping to improve network visibility platform for operators.
EXFO said it has acquired privately held Ontology Systems in a deal valued at $7.6 million, net of cash.
U.K.-based Ontology works with real-time network topology discovery and service-chain mapping designed to provide visibility into network services, which EXFO said will bolster its service assurance and real-time 3G analytics platforms in providing “a truly comprehensive view across physical, virtual and hybrid networks.”
The company cited the growing use of virtualized network technologies like software-defined networking and network functions virtualization as supporting greater agility in network operations, which in turn has created the need for automated network inventory solutions integrated with probing agents to “accelerate fault discovery, root-cause analysis and eventually closed-loop automation in hybrid physical-virtual environments.”
“Based on early discussions with [communications service providers], this new offering is resonating very strongly with them since they are striving to improve customer experience while becoming more agile and cost efficient,” explained EXFO Founder, Chairman and CEO Germain Lamonde.
Ontology is said to have generated $4 million in revenues over the past 12 months, including sales to tier-one CSPs. EXFO said the deal would be neutral to adjusted earnings before interest, taxes, depreciation and amortization in fiscal 2017, and accretive moving forward.
EXFO late last year purchased the majority of assets from California-based Absolute Analysis for $8.25 million in a move to boost its capabilities in fiber-based network testing to support wireless networks. EXFO said the purchase included “technology, expertise and solutions in the area of radio frequency testing for fiber-based radio access networks” and added that “in a market where subscriber quality of experience is a profitability game changer, [mobile network operators] have little room for error while pressure is increasing to deploy faster and minimize operating expenses.”
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