AI-integrated manufacturing
From bare land to a line that predicts its own failures. Six disciplines — AI, greenfield delivery, HRMS, TQM, TPM and ESG — installed as one system, on your floor, by people who have run plants themselves.
Overall equipment effectiveness
78.4%
▲ 6.1 pts since install
First-pass yield
96.2%
▲ 2.4 pts since install
Mean time to repair
41min
▼ 17 min since install
Energy per unit
2.14kWh
▼ 16% since install
Illustrative readout from an installed programme. Every figure on this site is an illustration until it is your plant’s — which is exactly what the first two weeks are for.
What we do
Most plants buy these six things from five vendors and then spend three years making them talk to each other. We install them as one thing, because the data, the standard work and the people are the same in all six.
01 — AI-Integrated Manufacturing
11 wkpilot to production
02 — Greenfield Projects
0 → 1land to running line
03 — HRMS & Workforce Systems
1record, one source of truth
04 — Total Quality Management
≤1%first-pass reject target
05 — Total Productive Maintenance
85%world-class OEE, held
06 — ESG & Sustainability
3scopes, measured not estimated
Not sure which one
That is what the first two weeks are for. We walk the floor, read the data you already have, and come back with the order to do things in — priced.
The thread
A vision model is only as good as the quality system that defines a defect. A failure prediction is only useful if maintenance planning can act on it. A carbon number is only auditable if the shop-floor data is clean. Bought separately, these six disciplines fight. Installed together, each one makes the next cheaper.
TQM
What counts as a defect, measured the same way twice. Without it every model learns someone’s opinion.
TPM
A prediction with no planned-maintenance route behind it is a notification nobody opens.
HRMS
Skills, shifts and incentives are what turn a new standard into the way the shift actually runs.
ESG
Scope 1 and 2 come out of the same energy data the OEE model already consumes. Measured once, used twice.
Greenfield
The cheapest place to design intelligence into a plant is before the floor is poured. We run greenfield projects from the demand case to the ramp curve — and the data architecture is drawn at the same time as the layout.
Stage 01
Demand case, capacity model, site options and the number the board has to approve.
Stage 02
Layout, material flow, line balance and the data architecture — before concrete.
Stage 03
Equipment specification, vendor selection, technical negotiation, delivery control.
Stage 04
Civil, utilities and installation supervised against the design, not against the invoice.
Stage 05
Validation, trial runs, standard work written and the shift trained on it.
Stage 06
Rate, yield and OEE driven to plan, then handed to a team that can hold it.
Installation 01
Four plants, three countries, one shared vendor base. Eleven weeks on the line with the plant’s own supervisors, against a number agreed in week two.
−41%
First-pass rework
7.2% → 4.2%
+18%
Line throughput
812/sh → 958/sh
−9 days
Vendor lead time
31 days → 22 days
Two cycles after we left, all three were still moving in the same direction. That is the only test we accept.
Beyond the plant
The state with India’s largest industrial workforce teaches almost nothing about industry. MADE HERE is our schools programme — six modules on how a factory actually works, taught by practitioners, funded by manufacturers, in the schools around their plants.
Next step
Whether it is a site that has not been built yet or a line that will not hold its gains, the first conversation is the same: what is happening, what it costs, and what it would take to change it.
