Ensure asset reliability with predictive maintenance

Predictive Maintenance

Save your business time and money by eliminating unscheduled equipment or system failure.

Adopting machine learning into the maintenance of your equipment and other assets can help determine the condition to detect anomalies and possible defects in order to be fixed before failure occurs.  


Proactive maintenance – What's the benefit?  

Predictive maintenance can improve productivity, product quality and supports the overall effectiveness of assets and environments.  

Having more proactive maintenance can also improve assets by,  

  • Reduction or near elimination of unscheduled equipment downtime caused by equipment or system failure 
  • Better management of assets and increased life expectancy of assets – in some cases by 20-40% [1] 
  • Reduction in maintenance costs – down by 50%[1] 
  • Minimises costs spent on maintenance staff, spare parts, and equipment 
  • Reduces stock of spare parts due to increased service life of equipment and assets. No need to stock “just in case”. 
  • Improved safety through the workplace for technicians and operators 


A partner you can trust  

At Kainos, we’re known for engineering excellence; we combine expertise in innovation and robust engineering to quickly and effectively deliver value and transformation.  

We work in partnership with you through custom-built capability; together with your team our experts use a proven enablement framework to transfer knowledge and skills. 

See how we can help your business

Looking to digitally transform your business? Get in touch to see how we can help you.

Our People

Gary Hunter
Business Development Director, Data & AI - Commercial ·
For more than 25 years Gary has worked delivering technology-based solutions to business problems. He is a Chartered Management Institute certified Professional Consultant and Business Analyst who was reborn in the cloud 6 years ago and has subsequently worked on more than 35 cloud big data and ML transformation projects
Gareth Workman
Chief AI Officer ·
Gareth Workman leads AI strategy for Kainos, working across the business to define goals for success and to harness the benefits of AI for our people, customers and partners. Gareth has over 18 years of experience at Kainos in several technical positions including principal architect, CIO and cloud practice director.
Ruth McGuinness
Data & AI Practice Lead · Kainos
Ruth has over nine years of experience in the tech and AI space. She is passionate about unlocking the benefits of AI/ML to improve business and wider society.
Lee Johnston
Business Development Manager ·
With a passion for helping customers solve their most complex problems, Lee has over 7 years of experience delivering digital transformation projects. Lee supports customers to take advantage of their data and works with them to unlock business value.