AI VQC

DEPLOYING WITH YOUR OWN TEAM

Visual inspection launched by your own team — step by step.

Do you have a quality engineer and IT staff? That is enough to launch AIVQC without an integrator. Here is who does what, the path from the first image to a decision on the line, and where you can count on our help.

We designed AIVQC to be launched by the plant's own technical team, not an external integrator. Automatic training replaces machine-learning expertise, the Server installer guides IT staff step by step, and simulation mode lets the automation engineer check the integration before the station starts driving the line.

You pay for a software licence, not for specialists' hours — and the know-how stays in the company. The easiest start is a 30-day pilot on one station: on your own from the beta (February 2027) or with our support.

01

No integrator hours

For the first deployment and every change — a new product variant is work for your engineer, not an order and a lead time with a supplier.

02

Your hardware

The camera and computer you already have can stay, if they pass qualification.

03

Know-how stays in-house

The team that launched the first station repeats the same path on further lines.

04

Help when you need it

In one area, in a pilot or in a full deployment — you decide how much you do yourself.

STEP BY STEP

From installing Server to inspection on the line.

Five steps every station goes through — in a pilot and in a production deployment.

  1. 01

    Server

    IT installs Server as a Docker container on a Linux server, a Synology NAS or a Windows computer — or, at a small site, as a service on the Trainer computer.

  2. 02

    Image

    The engineer and the automation engineer choose the camera position and lighting so the defect is clearly visible. Existing hardware stays if it passes qualification.

  3. 03

    Model

    The engineer imports images, labels defects and confirms defect-free images. Automatic training chooses the model and parameters, and validation on an independent set shows whether the result meets the criteria.

  4. 04

    Station

    The automation engineer connects the station to the PLC over Modbus TCP and checks the whole logic in simulation mode. The approved recipe goes through Server to the selected station.

  5. 05

    Run and improve

    The operator starts inspection with one button. NOK and low-confidence images return to Trainer, and a new recipe version is made without an order to an integrator.

TEAM

Who does what.

Nobody on this team needs to be a machine-learning or vision-programming specialist. What is needed is knowledge of the product, the plant network and the PLC — which the plant already has.

RoleTasksDoes not need to know
Quality or process engineerLabels defects, sets the training goal and time, assesses the result and approves the recipeHow to choose a model architecture and training parameters
IT staffInstalls Server, looks after backups, updates and accessMachine learning
Automation engineerConnects the station to the PLC over Modbus TCP and tests it in simulation modeVision-system programming
OperatorsStart inspection, choose the recipe, run the shift and batchAI tools — they see the OK/NOK result with its decision time

SAVINGS

You pay for a licence, not for hours.

In a classic vision project, a large part of the cost is specialists' work — at launch and at every later change. When your own team deploys, that cost becomes work by people you already employ. How to work out the return using data from your own line is covered in How to calculate the return on automating quality inspection.

  • No integrator hours — for the first deployment and every change.
  • A new product variant is work for your engineer, not an order and a lead time with a supplier.
  • You reuse the camera and computer you already have, if they pass qualification.
  • Further lines repeat the same path with the same people.
  • Deployment can be part of a grant-funded project — funding a vision inspection system.

SUPPORT

You are not on your own.

Deploying with your own team does not mean doing everything yourself. Missing an automation engineer or unsure about the image? We help exactly where you need it. Technical details for IT are on the Security and IT page, and the full guide is in Deploying with your own team.

OptionWhat it covers
Self-run pilotFrom the beta (February 2027): 30 days, one Trainer workstation, one station, up to three defect classes
Pilot with our supportCamera, optics and lighting assessment, help with data and thresholds, a report recommending GO, CONDITIONAL GO or NO-GO
Help in one areaFor example choosing the camera and lighting, connecting to the PLC or preparing data
Full deploymentLicence, hardware qualification, configuration and integration by AIVQC

We quote individually. If you are planning a grant application, we will help describe the solution and its scope.

FAQ

Questions about deployment and the pilot

More questions in the FAQ →
What does the pilot involve?+

The pilot is the full platform on one station: one Trainer workstation, one inspection station and up to three defect classes for 30 days, with a free extension available. You train a model on images of your own product and see the result on your line before you decide on deployment. A pilot with our support ends with a report recommending GO, CONDITIONAL GO or NO-GO. Step by step: AI quality-inspection pilot.

Can I run the pilot on my own?+

Yes — from the beta, that is from February 2027. You install Server, connect Trainer and the station, and automatic training prepares the model. If you want to start earlier or prefer us alongside you, we will run the pilot together with you. You can sign up for the beta through the contact form.

Does the pilot guarantee a specific accuracy?+

We do not use one threshold for every project. Acceptance criteria are agreed before the pilot based on the risk and economics of the specific process. How to weigh false accepts against false rejects is covered in the article on decision thresholds.

What happens after a successful pilot?+

You choose how to deploy. We can prepare an offer for a full production deployment — licence, hardware qualification, configuration and integration — or provide the software alone if your own team deploys it.

Can we deploy AIVQC ourselves?+

Yes. If you have your own process engineers and IT staff, you have everything you need: Server installs like any Docker container — or, at a small site, as a service on the Trainer computer — and automatic training needs no machine-vision expert. You pay for a software licence, not for integrator hours — usually the biggest saving. Contact us for a quote.

Who do we need on the team to deploy AIVQC ourselves?+

A quality or process engineer who knows the product and its defects, IT staff to install Server, and an automation engineer to connect the station to the PLC. None of them needs to be a machine-learning specialist. Details are in the guide Deploying with your own team.

What if we lack an automation engineer or imaging experience?+

We can help in one area — for example choosing the camera and lighting, or connecting to the PLC — or run the pilot together with you. Deploying with your own team does not mean you are left on your own.

Can I use my existing camera or computer?+

Yes, if they pass qualification with the target camera, model, recipe, I/O and required cycle time. A processor or camera name alone does not guarantee the result. How to assess it is covered in Retrofit or new station?.

AIVQC PILOT

Try it on your own line.

Start with a 30-day pilot on one station and see the result on images of your own product before you decide on deployment.

Have a quality engineer and IT staff? Your own team can deploy AIVQC — you pay for a licence, not for integrator hours. Sign up for the beta →

  • 1 Trainer · 1 station
  • Up to 3 defect classes
  • 30 days + free extension
  • No cloud
Join the pilot →