PM02 Optimisation
A practical workflow for finding planned maintenance tasks worth reviewing.
ABOUT NEXTGENMAINT
Practical AI for maintenance and reliability work.
NextGenMaint is a founder-led product initiative focused on helping asset-intensive energy and resources teams find measurable waste in planned maintenance, spare parts decisions and maintenance strategy work.
Why it exists
Why it exists
Maintenance waste often sits across work orders, task lists, inventory records and strategy documents. NextGenMaint is being built to make those review areas easier to find, inspect and validate with the people who own the decisions.
Focus areas
What we are building around
Dead Stock Reduction
A focused way to surface spare parts and inventory records that may need review.
Maintenance Strategy Support
A support layer for organising evidence around reliability and strategy decisions.
TEAM
Practical experience behind the product.
Hands-on experience across maintenance, AI implementation, research and software delivery, focused on tools that fit real reliability work.
Femi Arowosafe
Founder
Maintenance AI implementation, reliability strategy and product delivery.
MSc Software Engineering, BEng Electrical & Electronics Engineering
Mo Oyedeji, PhD
Innovation & Research Advisor
Product framing, R&D thinking and technical storytelling.
PhD Systems & Control Engineering
David Oladeji
Technical Delivery Advisor
Software architecture, product build planning and scalable delivery.
MSc Computer Science
Principles
Principles
01
Support engineering review.
02
Link value to real maintenance and inventory decisions.
03
Start narrow before scaling.
Interested in shaping a practical maintenance AI use case?
Share a focused problem, dataset or workflow worth testing.