2016 - Senseye, the Manufacturing Uptime as a Service company closes funding round

10 November 2016

Senseye, the Manufacturing Uptime as a Service company, today announced the close of a significant seed funding round, led by Breed Reply, alongside IQ Capital. Existing angel investors also participated. The capital will be used to launch Senseye’s revolutionary predictive maintenance software which automates analysis of condition monitoring data and enables advanced prognostics – automatically diagnosing failures as well as forecasting when a machine is likely to fail. 

iStock-464871255_lowThe software is cloud-based and designed to be used without any technical expertise in condition monitoring. It is already trusted by a major automotive OEM, helping it to avoid unplanned downtime which can cost in excess of $2m per hour

Industry 4.0 is already generating a huge amount of information that goes largely unexploited due to the amount of manual analysis needed to extract value from condition monitoring and prognostics using traditional methods. “Our software is data scientist and diagnostic engineer in the cloud, it brings advanced predictive maintenance to companies that don’t want to spend a fortune on manual analysis but want to save money on operations and maintenance” says Senseye CEO Simon Kampa. 

“We’re delighted to welcome Senseye into our growing IoT portfolio of 14 companies. Senseye brings immense benefits to manufacturing prognostics with its innovative approach within Industry 4.0” says Emanuele Angelidis, Breed Reply CEO. 

Senseye is leading the cloud-based condition-monitoring and prognostics market, being already engaged by a number of Fortune 100 companies. The award winning product is usable from day-one and available as a simple subscription service, allowing the company to rapidly and successfully acquire new business. 

“I was particularly impressed by the depth of Senseye’s automated analysis across a wide range of manufacturing assets” says IQ Capital partner Ed Stacey. 

Senseye has produced a free White Paper on prognostics and how it helps predictive maintenance, available here: 

Download our prognostics white paper 

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