91% of manufacturers are increasing AI spend. 0% have it fully running.
Your systems each do their job. The problem lives in the gaps between them, the handoffs that still run on spreadsheets and email. For mid-market manufacturers and contract shops, we connect what you already have before adding anything new.
Canadian HQ Outcome-based pricing, not hourly billing Need → Scope → Build → Launch → Evolve
The industry-wide gap, in three numbers
73% / 0%
of mid-sized manufacturers are still in early AI testing. None report full deployment across the business.
Source: Kaufman Rossin, 2026
55%
name legacy ERP integration their single biggest obstacle to making AI actually work.
Source: Kaufman Rossin, 2026
$340K/yr
lost by the average small or mid-sized shop to preventable workflow gaps: scheduling, comms, QC paperwork, compliance.
Source: US Tech Automations, 2026
Sound familiar?
This is what that gap looks like on the shop floor, not a slide deck.
A custom order still routes like this: sales enters it into a spreadsheet, emails production, production emails procurement.
QC documentation eats roughly a third of your quality team's time, before they've analyzed a single result.
Customer service loses over two hours a day just answering "where's my order."
Nearly half of production delays trace back to a material shortage that was predictable from the schedule.
If your last AI pilot stalled, you're in the majority.
73% of mid-sized manufacturers are still stuck in early testing, and 55% say the reason is legacy ERP, not the AI itself. We start with the data infrastructure underneath, not another point tool bolted on top of a system built before AI existed.
Start with a scoped audit, not a sales call
- Scope
- Map your ERP, floor data, and where manual handoffs are costing you
- Investment
- $5,000 credit toward your first build
- Deliverable
- A scoped, priced plan, not a deck
- Turnaround
- 2 weeks from kickoff
$13M / 16wk
One manufacturer connected 31 machines across four departments and unlocked $13M in incremental capacity within 16 weeks, by fixing the data layer first.
Source: Supply Chain Management Review, 2026