AI & IoT Predictive Maintenance
Where we're at?

Concept and business plan team may be incomplete.

Idea is formed project ready to launch.

Have paying customers adapting to market.

Growing company and users!

If something new is not ten times better than a substitute, it is not worth building! We have developed an entirely new Solution for Predictive Maintenance using the Internet of Things with Machine Learning.

We have entirely re-imagined how maintenance is conducted, focusing on management. Existing preventative maintenance solutions rely on providing raw data for hard to find and expensive technicians to manually analyse. We remove that whole layer of complexity, focusing on delivering simple, actionable alerts to potential machinery problems.

Our sensor provides many times more information than most existing solutions, generating a much more detailed insight into the condition of the machine being monitored. However, having a better picture is only half the solution, it is the ability to accurately analyse the information that sets our solution apart from the crowd. We have collected an unprecedented amount of data on all types of machinery from our customers and repositories like NASA. Using proprietary in-house designed algorithms from our PhD eggheads, through Machine Learning we match deterioration patterns to provide managers clear easy to understand information and projections about machinery health in an even more intuitive solution than a Star Trek ship.

For a relatively small investment, facilities can start to engage with our solution which is an investment, not a cost, since there will be a significant return in reduced unscheduled downtime as well as a reduction in un- necessary planned maintenance. Once the benefits have been demonstrated in a facility, scaling to include as many machines as necessary is simply a case of installing additional sensor hardware and the associated SaaS licence. A low incremental cost investment process that will require little direct additional input from our sales and technical support teams, facilitating the possibility of rapid to exponential growth.

Managers of facilities for the first time can track the productivity of their machines easily with clear notifications and solutions. Substitutes required a deep understanding of waveforms and mathematics. We do not train humans, we train AI algorithms with even denser data, so you do not have to, allowing managers to track a machine's performance against itself and others over different time periods, from days to years.

Timely providing the right management information to keep all the wheels of industry turning.

The problems we are solving are the excessive and unnecessary downtime of equipment, whilst simultaneously having the capability of avoiding catastrophic events caused by equipment failure. Such failures can be avoided by implementing an appropriate Predictive Maintenance Solution. Previously managers didn’t have the ability to see real-time data about their machine's health and remaining useful life without the use of an engineer. Our solution enables facility managers to see real-time data about their machines allowing them to make data-driven decisions no matter where they are. There is a big untapped market for such solutions in a lot of different vertical applications.

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  • Steve circal
    Svyatoslav Andriyishen
    AI Scientist Director
    Driven for dynamic development with an aptitude for quickly mastering and applying new computational and mathematical technologies, techniques, and... Read More
  • Lud round
    Dr. Ludovic Krundel
    Ludovic is a research scientist passionate about cybernetics, machine-learning, mobile robotics, quantum physics as well as trans-techs and their i... Read More
  • Owen circal
    Owen Chui
    More than 20 years of working experience in electronics/I.T. technology business with global exposure. He has excellent track records in project m... Read More
  • Alain round
    Alain Garner
    Born in England and educated at boarding school in the United States, I love tech and disruptive companies evolution from both the financial and te... Read More
  • Matt circal
    Matthew Regan
    Business Analyst
  • Ivan circal
    Ivan Ho
    Sales Consultent
    Seasoned Electronics Component Sales and Marketing executive for multiple multinational corporations with a focus on Asian markets spanning 30 year... Read More