Linköping, Sweden — 16 April 2026 — We are seeing strong and growing demand for Maintmaster Manufacturing Intelligence, our AI capability built specifically for industrial maintenance, production, and continuous improvement.
Years of investment in digital systems have created substantial reserves of operational data: work orders, fault records, shift notes, and technician observations accumulated across hundreds of assets and thousands of working days. The challenge is no longer collecting that data. It is putting it to work.
For most industrial operations, 3 problems compound one another. Maintenance teams keep fixing the same faults because the patterns buried in years of work order history are invisible at scale. Production teams keep losing time to recurring stoppages they cannot quantify. And CI managers spend more time compiling evidence than acting on it. The knowledge is there. Teams already know which machines cause the most trouble. What is missing is the data to prove it, prioritise it, and push improvement projects through the organisation. With a feeling, nothing moves. With data, it does.
Manufacturing Intelligence is designed to close that gap, and it is why manufacturers across precision manufacturing, sintered metals, glass, chemicals, packaging, and food production are using it to augment their teams' expertise.
"Your logged data already has the answers. With Manufacturing Intelligence, we bring those answers front and centre," says Magnus Nord, Chief Product Officer of Maintmaster.
Why generic AI falls short on the factory floor
Every major software vendor now markets AI. What most do not acknowledge is that generic AI was not built for manufacturing data.
Manufacturing has its own language. In some food and beverage operations, technicians write "produced pig feet" to mean they produced waste: a regional expression no internet-trained model recognises. In a precision metals plant, "M3 tension" refers to a specific production line that exists nowhere in any public dataset. Abbreviations, shorthand, and company-specific codes accumulate over decades into a vocabulary that lives only on the shop floor.
Generic AI also demands clean, structured input. No factory's data ever is. The same fault gets described differently across shifts, teams, and languages. Data ends up in the wrong fields. A system that requires data hygiene as a precondition for intelligence will never deliver value in a real manufacturing environment.
Manufacturing Intelligence was built for these conditions. The vision inspection cameras already running on production lines are purpose-built tools trained to detect one specific class of problem with high precision. MI works the same way: trained specifically to read manufacturing maintenance text, find failure patterns within it, and surface what is actionable. It does not memorise your data or retain it. Remove the maintenance records and the AI has nothing to say. Your operational knowledge stays entirely within your own systems.
Developed through our acquisition of Peoplegeist, a specialist in AI text analysis for manufacturing, it handles imperfect data entry, understands the jargon teams develop over years, and works across languages without requiring translation or clean-up.
"By joining Maintmaster, we can bring our technology to more manufacturers and make continuous improvement easier to start, faster to prove, and simpler to scale," says Leonard Lin, Product Manager and founder of Peoplegeist.
No new sensors, no infrastructure change, no data preparation required. The typical process: we analyse a selected asset or production area using existing data and present findings within weeks, so you see what the AI surfaces in your own system before any wider commitment is made.
One connected platform — not another system to manage
MI is the intelligence layer at the heart of the Maintmaster product suite: a connected platform combining CMMS, OEE, IoT, and AI, with shared data across all four products.
Because MI operates within the same environment as maintenance records, production performance data, and asset history, its intelligence is immediately available to every team that needs it. The maintenance manager gets recommendations drawn from years of work order history. The CI manager gets detailed pattern analysis to prepare data-driven improvement meetings. The production leader gets the numbers that turn a recurring frustration into a funded initiative. Management gets automated reports that keep improvement visible and accountable across the business.
CMMS and OEE are strong on their own, and significantly more powerful together. MI is the layer that transforms their combined data into a living operational picture, one that grows more useful the more the team uses it.
The result: maintenance and production data stops being a record of what happened and becomes a guide to what should happen next. Problems that recur get addressed at their source. Knowledge that once lived only in the heads of experienced engineers becomes accessible across teams, shifts, and sites.
That is the shift manufacturers are asking for. We built Manufacturing Intelligence to deliver it.
Learn more at https://maintmaster.com/manufacturing-intelligence.
About Maintmaster
With more than 700 industrial customers across 39 countries, Maintmaster helps manufacturers enhance efficiency, reduce downtime, and achieve sustainable performance improvements. Founded in Sweden in 2001, we combine CMMS, OEE, IoT, and AI in one connected platform, backed by more than two decades of industry expertise. maintmaster.com
Press contact Jon Lindholm, Chief Marketing Officer jon.lindholm@maintmaster.com | +46 768 43 43 72
