For manufacturing plants

Assess AI for inspection and inbound/outbound document workflows

For plants that already have CCTV installed, still rely mainly on visual inspection, and still key inbound and outbound documents by hand.

We begin by assessing your equipment and operating environment, then shape an approach suited to the cameras, sensors, or machinery already in place.
Motion and defect detection on a production line
What plants actually deal with

Four things that inflate cost with nobody seeing the number

Defects surface at the end of the line, too late to fix

Visual inspection at the end of the line means you learn about a problem after a whole batch is made, with no footage to trace the cause.

Buddy punching, and overtime that does not match real work

Card or PIN attendance can be used on someone else's behalf, and when a payroll dispute arises there is nothing to verify it against.

Every inbound and outbound document is still keyed by hand

Delivery notes, tax invoices, and goods-receipt documents are re-keyed into the system, creating a bottleneck and typos that surface during audit.

Production reports lag reality by days

By the time the numbers are consolidated it is too late to act, and each shift reports a different figure.

What we put in place

Fixed one at a time, starting with the fastest payback

Computer Vision

Real-time mid-line defect detection

Assess CCTV compatibility and site conditions to design event screening and evidence for later team review.

Face Recognition

Add evidence to attendance review

Image evidence, event history, consent, access, and retention controls can be designed for review by the organization's DPO or responsible team before use.

AI-OCR

Read inbound and outbound documents automatically

Assess real delivery notes, tax invoices, and goods-receipt samples, including printed or handwritten documents, with review before posting.

Example engagement

An automotive parts manufacturer in Rayong

The plant inspected defects visually at the end of the line, so problems surfaced only after a full batch was produced, and every inbound material document was still keyed in by hand.

The shape of the engagement: move the inspection point from the end of the line to the middle, so defects appear while they can still be corrected, and connect AI-OCR to inbound documents to stop the re-keying. The real gain comes from comparing that plant own defect rate and keying time, before and after.

Suitable inspection points
Defined after assessing cameras, angles, and line speed
Existing cameras
Uses the CCTV already installed; no machine changes
Runs in parallel first
Compared against your current inspection before it decides anything
Who this fits

If your plant matches these, it is worth a conversation

  • Enough inbound and outbound documents to keep someone keying
  • CCTV already installed in the production area
  • Defect inspection is still mainly visual
  • A quality or IT owner who can take part in the project
Not a fit yet if

We will say so plainly if it is not worth starting

  • No defect data is recorded at all yet, so before/after cannot be measured
  • The production line is being fully replaced within the year
  • You want a system that decides entirely on its own with no human review
Start with your own numbers

Send 10 real inbound/outbound documents and see how accurately they read

The team will confirm scope, timing, fees, and data handling before the assessment begins.