Senseye is a leading industrial solution company for AI driven Machine Health Management. The company helps global industrial organisations unlock savings through machine health optimization in key industries such as automotive, manufacturing, heavy industry and CPG / FMCG.
Easy Engineering: What are the main areas of activity of the company?
SENSEYE: The Senseye PdM Suite delivers AI driven Predictive Maintenance at enterprise scale, it is used by digital maintenance teams at global industrial companies to help avoid machine failure by providing the right information ahead of time to direct human expertise.
E.E: What’s the news for 2021 about new products?
SENSEYE: Senseye has announced ROI Lock®, the first ever business outcome guarantee in the industrial space. In collaboration with SCOR, a leading global reinsurance company, Senseye guarantees 100% ROI within 12 months for customers using its Senseye PdM Complete solution.
Senseye has always believed in the commoditization of sensing hardware and has partnered with leading providers through it’s ‘Senseye Ready’ program, giving Senseye the ability to offer a complete hardware and software vertical stack solution, using the best off the shelf hardware preconfigured to be ‘plug and play’ with Senseye software, making getting started in sophisticated PdM extremely easy for end users.
E.E: What are the ranges of products?
SENSEYE: Senseye’s core product is Senseye PdM, offered as a managed service to guide customers on their predictive maintenance journey to full ROI as well as an enterprise version to multiply the efforts of existing digital maintenance teams. These are supported by enabling products such as Senseye PdM Omniverse®, a knowledge platform consisting of videos, tutorials, processes, community forums and workshop materials to enable customers and partners to take charge or their own PdM journeys.
E.E: At what stage is the market where you are currently active?
SENSEYE: Predictive Maintenance is a proven technology, with Senseye having helped companies like Nissan to reduce their unplanned downtime by 50% and achieve full ROI in less than three months. The Industry 4.0 space is increasingly mature; a serious indication of which is Amazon recently launching its own vertically integrated solution for predictive maintenance.
E.E: What can you tell us about market trends?
SENSEYE: As case studies for the efficacy of PdM start to make their way into the public (e.g. 40% maintenance efficiency improvement, 20% reduced overall maintenance spend, 50% increase in availability), there is increasing confidence in the market in the necessary use of the technology. This is accompanied by in increasing availability of data as customers start to either retrofit increasingly inexpensive sensor options with new machines being supplied with connectivity by default.
E.E: What are the most innovative products marketed?
SENSEYE: Senseye PdM Complete delivers business outcomes through PdM – or all money is returned (through ROI Lock®).
Senseye PdM Omniverse® Solves the culture & knowledge gap to enable customers and patners to take charge of their PdM journey.
Senseye PdM Ready: Vertically integrated solution offering.
Using leading off the shelf hardware, preconfigured to send data to Senseye
E.E: What estimations do you have for 2021?
SENSEYE: An increase in buying confidence as the world starts to return to a more normal level following the global pandemic in the latter half of 2021. Some industries such as CPG / FMCG have seen a dramatic increase in demand which has placed their production assets under further stress – highlighting the need for more sophisticated and automated monitoring to ensure that production quotas can be met on time and to the right quality.
We are also seeing the increased commoditization of sensing hardware – with reliable wireless sensing becoming increasingly inexpensive and common from multiple vendors. This dramatically improves access to data for the larger retrofit market where industrial machines may be expected to have a lifetime of around 20 years.
