Computer vision turns cameras on a line, a yard or a road into inspection and detection that runs without a person watching. We build it as a proof of concept on your own footage first, then take it to production.
Image and video intelligence (inspection, detection, counting and recognition) tuned to your real-world environment. We turn cameras and visual data into something your business can act on, automatically.
Last updated: 14 September 2026
Computer vision turns cameras on a line, a yard or a road into inspection and detection that runs without a person watching: crack detection on precast concrete, plate recognition for a low-emission zone, quality checks in food production. Built as a proof of concept on your own footage first, then production.
A huge amount of useful information arrives as images and video: products on a line, items on a shelf, documents, footage, scans. Computer vision turns that visual stream into structured signals: what's there, where, how many and whether something's wrong. The hard part is making it reliable in the real world, with real lighting, angles and edge cases. That's exactly what we do.
We build vision models around your actual conditions and your actual data, then deploy them where the camera already is: on the line, on the device or in the cloud.
Find, locate and count items, people or defects in images and video.
Spot defects and deviations on the line, faster and more consistently than the eye.
Read text and recognise products, plates or documents where you have the right to.
Turn live or recorded footage into events, alerts and useful metrics.
Run vision where the camera is, for speed and privacy, when the cloud isn't ideal.
GDPR-aware handling of imagery, especially where people are involved.
How it works
Four fixed steps. You see something real at the end of each one.
We define what to detect and what "good enough" accuracy means for you.
We gather and label representative images from your environment.
We build the model and test it against your real-world edge cases.
We put it on the line, the device or the cloud and monitor accuracy.
Not always. We can often start from a modest set and use techniques like augmentation and pre-trained models to get there with much less.
Usually, yes. We design around your current hardware and conditions wherever possible, rather than asking you to rip and replace.
Yes: we can deploy on the edge or on-device for speed and privacy when sending images to the cloud isn't practical or allowed.
We handle imagery with GDPR in mind, minimising, anonymising or processing on-device wherever people are involved.
We agree a target up front and test against your real edge cases, so accuracy is measured on your environment, not a clean demo dataset.
It depends on the use case. Some applications work with standard CCTV; others need industrial line-scan or area cameras. We specify hardware requirements during the audit phase and can advise on procurement.
We set accuracy targets based on the cost of false positives versus false negatives in your specific process. For most quality-control use cases, 95%+ precision is achievable within the first sprint.
Yes, when the use case requires it. We design for the required latency, from real-time edge inference to overnight batch processing. The right architecture is scoped up front.
We are a boutique applied-AI firm based in the Utrecht region, and computer vision is core to what we do. If you want a small, senior team that works hands-on with clients across the Netherlands and the wider EU, remotely or on-site as needed, in English or Dutch, we are a good fit. We are specialists, not a large consultancy, so you talk directly to the people building your model.
We start with a short paid discovery to scope what you need to detect and what accuracy is worth. Then we build at a fixed price: you own the source code and IP, senior engineers do the work, and EU AI Act and GDPR are handled by default. A proof-of-concept can start from a few thousand euros; a production build is larger and scoped after discovery. The Dutch WBSO scheme can offset R&D cost.
Catch cracks, spalling, chipping and voids on precast segments automatically, right on the production line.
Turn ordinary road footage into a live, prioritised map of potholes, cracks and obstacles, so teams fix the right defects first.
Read plates and check zone eligibility in real time (rain, glare or motion blur) with an audit trail behind every decision.
Spot the prized two-leaves-and-a-bud growth, catch pests and disease early, and put crews where they matter most, across 3,200 ha.
So you can price the gap before a call rather than after one.
What we found. Across thousands of hectares and a 10,000-strong workforce, quality and plant-protection decisions relied on manual spot-checks and experience. Effort and chemicals were spread too thinly to be efficient, and early pest or disease signs were easy to miss until they spread.
Real result from a Crux Digits engagement; client name withheld pending permission.
Tell us what you'd like to detect or inspect: we'll tell you what's feasible, in a free consultation.
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