Manufacturing
AI on the plant floor, not just the slide deck.
Quality exceptions caught before they become scrap. Procurement that reorders before the line stops. Production reporting that assembles itself before the morning meeting.
We are new — no roster of plant managers to point to yet. What we have is a model: start with one workflow, project the savings honestly at your cost rates, deliver in a fixed sprint, and stay accountable after launch.
Based in Canada? Government programs may be able to offset the cost — see Grant-Backed AI →
Where we focus
The workflows costing manufacturers the most
These are documented, solvable problems. The question is which one to start with.
Quality logging is paper-based and caught in batches
We build digital quality capture workflows that log defects, deviations, and inspection results in real time, with automatic escalation when a threshold is crossed. Your quality team stops reviewing yesterday's paper logs and starts responding to today's alerts.
Procurement timing is reactive, not data-driven
We connect your inventory, production schedule, and supplier lead time data to build automated reorder triggers. Parts and raw materials get flagged for purchase before they hit the floor — not after a line stops because something ran out.
Production reporting takes hours to assemble manually
We automate the pull and rollup of shift output, yield, downtime, and OEE data from your production systems. Operations managers get a structured daily or weekly report without anyone building it by hand.
Exceptions surface too late to act on
We build exception monitoring across your key production and quality metrics. When yield drops below target, a machine shows unusual cycle times, or a supplier delivery is late, the right person is notified in time to intervene.
Illustrative scenario
What this looks like in practice
A representative scenario — not a specific client. It shows how the engagement model applies to a common pain in manufacturing operations.
Illustrative · Representative, not a specific client
A regional contract manufacturer. Two shifts, three production lines. Quality inspectors fill paper-based inspection sheets every two hours. At shift end, a supervisor compiles the results into a spreadsheet — 45 minutes per shift, producing data already 8–16 hours old by the time anyone reads it.
We start with the quality data capture and reporting workflow. Paper sheets become digital capture at the line. When a defect rate crosses a defined threshold, the right supervisor is notified immediately — not at the end-of-shift review. The shift summary report builds itself from the captured data.
The quality team stops transcribing and starts responding. The engagement runs 6–8 weeks, fixed cost. We monitor the integration after launch so data gaps surface before they produce a bad report.
How we work
The ReadyIQ model for manufacturers
Four steps that apply to every engagement. Operational, not aspirational.
One workflow first
We start with the process costing your operations the most — in hours, in scrap, or in reactive firefighting. We map it, estimate the savings, and get your sign-off before we build anything.
ROI before you pay
Before the sprint begins, you see a documented estimate: hours saved, scrap reduced, or downtime avoided — at your cost rates. If the math does not work, we say so.
Fixed sprint, known cost
The engagement runs 4–8 weeks with a fixed price. No open-ended retainers. You know the cost before we start.
Post-build monitoring
After launch, we monitor for drift. Machine integrations change, ERP schemas update, production lines shift — we stay on it so your operations team does not have to.
On the technical side
We work with what you already have
No rip-and-replace required
We connect to your existing ERP, MES, SCADA, or inventory systems. Our integrations sit alongside your current stack, pulling and pushing data through APIs or file-based handoffs — whichever your systems support.
Before the sprint begins, we do a systems inventory: what data lives where, what is accessible, and what we will need to work around. You see the integration plan before we commit to scope.
Deliverables
What you get from a manufacturing engagement
- Process map with time-per-step and automation opportunity scoring
- Built and tested automations deployed to your environment
- Integration with your existing systems (ERP, MES, SCADA, inventory software)
- Exception alerting and threshold-based escalation workflows
- Runbook: what each automation does, how to monitor it, how to handle edge cases
- Training session for your operations, quality, and procurement teams
- 30-day post-launch monitoring window
Canadian grant angle
Federal, provincial, and regional programs may offset part of the cost of an engagement like this for a Canadian manufacturer. Eligibility, amounts, and timing are determined by the program administrator — not by us, and we will never promise an approval. What we do: scope the work first, and if a program plausibly fits, structure the deliverables so the paperwork is clean.
See how Grant-Backed AI worksStart here
Find out what AI is worth on your production floor
The free AI scorecard takes 5 minutes. It shows which workflows in your operation have the highest automation potential — a concrete starting point for the conversation.
No commitment. The discovery call is 30 minutes. If the ROI math does not work, we say so.