Why Sovel exists
Industrial maintenance runs on expertise carried by people — systems capture only part of the story. Sovel exists to make that expertise visible, governable, and transferable, while experienced people are still here to partner on it.
Sovel is cofounded by a mechanical engineer who spent time across energy, water utilities, and manufacturing, and by a partner with a background in finance, economics, and consulting. From the plant floor and from the business case, we kept running into the same problem: the most critical operational knowledge lived in people's heads, not in systems.
The workers closest to retirement often held the deepest expertise. When they left, that knowledge went with them. The next technician would spend hours on something that used to take twenty minutes. Parts would get ordered wrong. The same failures would repeat.
What made this solvable is that the signal already exists. Work order history carries it: recurring failures, resolution times that spike when key people are absent, corrective work that quietly diverges from written procedures. Sovel was built to find that signal and help maintenance teams act on it before the knowledge walks out the door.
Every maintenance operation has a handful of people who know how everything really works. When they retire, transfer, or are out sick on the wrong day, that knowledge disappears — and no system flags it. The costs show up later: longer resolution times, repeated failures, new technicians who can't get up to speed.
The data to prevent this is already sitting in CMMS exports. Sovel scales the pattern-finding across thousands of work orders so maintenance leaders can see the risk before it becomes a problem, not after.
Sovel uses AI where it actually helps: finding patterns in work order history, structuring raw technician input, flagging contradictions in documented procedures. What it doesn't do is make decisions on its own. Every piece of knowledge goes through a reviewer before it becomes an operational artifact.
Your sign-off, your safety culture, and your change process stay intact. The goal is to preserve and transfer what experts know — not to replace their judgment.
"Detection shows where to ask; capture turns answers into governed artifacts. Sovel pairs both, with detection setting the pace."
Sovel is built for maintenance and reliability leaders at facilities where operational knowledge is critical:
- Water and wastewater treatment plants
- Power generation and utilities
- Manufacturing and process industries
- Oil, gas, and petrochemical facilities
- Mining and heavy industry
- Fleet and facility management operations
Sovel is in early validation. We're working with maintenance teams to test the detection engine, refine capture workflows, and prove that governed knowledge placement reduces operational risk.