Our mission

Close the gap between detecting a loss
and controlling it in real time.

Most manufacturers already know, eventually, that they lost money last week. Qmach-AI exists to answer five questions continuously, not in a monthly review.

The five questions

Every module in Qmach-AI ultimately exists to answer one of these, faster and with more evidence than a spreadsheet or a gut call can:

1
Where are we losing money right now?
2
What is causing the loss?
3
What evidence supports that conclusion?
4
Who must act, and by when?
5
Did the action actually recover the projected value?

Why this matters

Qmach-AI's critical gap to close is the distance between detecting a loss and controlling the shop floor in real time. A quality team that already has a strong investigation process still loses days translating a defect spike into an evidence-backed root cause, a rupee figure, and a verified fix. We are building the system that closes that gap — for scrap, rework, downtime, speed loss and material loss alike — so a factory moves from a collection of disconnected tools into one focused loss-intelligence system.

What we value

Evidence over intuitionEvery hypothesis carries traceable provenance back to the production, quality or maintenance record it came from — not a black-box score.
Rupees, not just red flagsA loss isn't real to a factory until it has a number attached. We rank findings by financial impact and urgency, not alert volume.
Built for the floor, not the boardroomThe people closest to a loss — quality engineers, maintenance leads, line supervisors — should be the ones who can act on it fastest.

An example, not a hypothetical

"Line 3 generated an estimated loss this week." That sentence, backed by a ranked cause, supporting evidence, an assigned owner with a due date, and a verified recovery figure once the fix lands — is the shape of every answer Qmach-AI is trying to give.