Brainport runs on machines that make machines. We build industrial AI for Eindhoven's high-tech and manufacturing companies — predictive maintenance, computer-vision quality control, OEE and demand forecasting — so you cut downtime, lift yield and own the solution outright.
Last updated: 11 June 2026
Crux Digits is a boutique, senior-led AI consultancy serving Eindhoven and the Brainport region. We build industrial AI for high-tech and machine-building companies: predictive maintenance to cut downtime, computer-vision quality control, OEE and process automation, and demand forecasting. Senior people stay on the project, you own the solution, and EU AI Act and AVG compliance are built in from day one.
Eindhoven does not run on retail footfall or office services. It runs on machines that make machines. The Brainport region — ASML and its supplier web, the High Tech Campus, the Automotive Campus in Helmond, the metal and plastics shops feeding the equipment builders — is one of the densest concentrations of high-tech maakindustrie in Europe. That changes what an AI project actually has to survive. A model here meets sub-micron tolerances, mixed high-mix low-volume production, machine controllers from four decades of vintages, and a quality bar where a single escaped defect can halt a customer's line. Generic AI advice written for a webshop or a marketing funnel simply does not touch this world.
That is the gap an AI Consultant in Eindhoven has to fill: someone who treats the factory floor as the spec, not the slide. The numbers that decide whether a Brabant machine builder or precision shop makes money this quarter are OEE, scrap rate, first-pass yield, unplanned downtime and the cost of a warranty return. None of those move because you bought a dashboard. They move when the decision underneath gets sharper — when the machine that used to fail mid-batch gets pulled in on a planned slot, when the inspector who eyeballed 2,000 parts a shift gets a camera that never blinks, when the production plan stops triggering Friday overtime. That decision layer is where Industrial AI in Eindhoven earns its keep.
In a capital-intensive Brainport plant, an unplanned stop is rarely just a repair bill. It is a stalled line, a missed delivery window to a demanding OEM, scrapped work-in-progress and — on a constrained machine — output you can never get back, because the asset is already the bottleneck. Predictive maintenance reads the signals a machine gives off long before it dies: vibration, spindle current, temperature drift, acoustic signature, cycle-time creep. The model learns the difference between normal wear and a bearing, pump or drive heading for failure, and flags the component while there is still time to schedule the fix.
The measurable win is maintenance shifting from emergency to planned — far cheaper, far less disruptive — plus fewer surprise stops, longer asset life and a spare-parts budget you can actually forecast. The engineering hard part is the same one we solved in our predictive maintenance case study: telling a genuine fault signature apart from the ordinary noise of a working machine, early enough to act and without crying wolf so often that operators stop listening. Client names stay confidential, but the pattern is universal across Manufacturing AI in Eindhoven.
For high-tech assembly and precision parts, the cost of a defect escaping is brutal — a return from a tier-one customer, a halted line downstream, a reputation dent in a region where everyone knows everyone. Manual inspection cannot scale to the volumes or the tolerances, and human attention drifts over a shift. Computer-vision quality control changes the economics: a camera and a trained model check every part at line speed, flag surface defects, missing components, solder faults, dimensional drift, contamination or assembly errors, and log every decision for traceability.
The outcomes operators feel are concrete — higher first-pass yield, fewer warranty returns, scrap caught at the station where it is still cheap to reject, and an audit trail behind every pass-or-fail. The genuinely difficult part is robustness: distinguishing a real defect from glare, motion blur, a harmless scuff or a lighting change. That is exactly the problem behind our visual-defect detection work, and it sits at the centre of our computer vision service. We build vision systems that hold up on a real production line, not just in a clean demo.
OEE — availability times performance times quality — is the single number that tells a plant manager how much real output the equipment is giving up. AI attacks all three legs at once: predictive maintenance protects availability, process models reduce micro-stops and speed losses that drag down performance, and vision inspection lifts the quality leg. The point is not a prettier OEE chart; it is finding the specific hours the line is quietly leaking and putting a euro figure on recovering them. On a constrained machine, a few recovered points of OEE can defer a capital purchase entirely.
Process automation goes further into the everyday friction. Models tune process parameters to cut changeover losses and stabilise yield on high-mix runs, anomaly detection catches a drifting process before it makes a batch of scrap, and energy models trim the consumption of power-hungry equipment — no small thing for an Eindhoven plant facing both grid congestion and rising tariffs. We also automate the paperwork around production: reading supplier certificates, matching incoming goods to specs, and routing exceptions to a human. The connective tissue for these workflows is our AI automation practice, which strings these steps into agents that handle the routine end-to-end so engineers spend their time on judgement, not data entry.
Brainport supply chains are long, specialised and unforgiving of a missed signal. A demand forecasting model that learns the seasonality, the order-book lead times and the demand variability in your own history turns a guessed production plan into a defensible one — fewer expedite shipments at premium freight, less cash tied up in the wrong work-in-progress, and smoother capacity and shift planning so you are not recovering from a Monday surprise with weekend overtime. We delivered exactly this shape of problem in our demand forecasting and production planning case study for a large manufacturer: turn demand signals into a production plan, smooth changeover losses and defend market position.
Here is the part the demos skip: none of these models work on messy data. On a Brainport floor the signals live in PLCs, SCADA, an MES, an ageing ERP, quality logs in spreadsheets and a fleet of machine controllers that were never designed to talk to anything. A predictive-maintenance or yield model is only as good as the sensor history feeding it, and that history is deceptively dirty — gaps, drifted tags, timestamps that do not line up across machines. A large share of any honest AI Development in Eindhoven project is data engineering: instrumenting machines where sensors are thin, joining OT and IT data, cleaning the streams and building the pipeline that keeps fresh data flowing once the model is live. We are upfront about this because pretending otherwise is how factory AI projects quietly fail six months in. This is also where the national depth of our manufacturing AI work pays off — the integration patterns are hard-won, not improvised.
Factory AI touches data that regulators care about — worker-productivity signals, camera feeds, and decisions that affect quality liability and people's shifts. Under the EU AI Act some industrial use cases carry real obligations, and the AVG/GDPR governs the personal data throughout. We design for it from the start: data minimisation, clear retention, documented decision logic and a human in the loop where it belongs. Productivity and vision models in particular are handled with care — they exist to protect quality and balance the workload, not to surveil individuals. Compliance-first is not a brake on the project; it is what makes a model you can actually deploy on a line and defend to a customer's auditor.
Crux Digits is a boutique, senior-led AI consultancy founded in 2022, based at Vlierhoeve 100 in Nieuwegein in the province of Utrecht — a short run down the A2 from Eindhoven — serving the Brainport region and the whole of the Netherlands and Europe. We sit deliberately between two options that fail the typical Dutch high-tech and machine-building company. The big enterprise consultancies and the better-known data-science firms — the Accenture, Deloitte, Capgemini and Xebia tier — bill heavily, staff your project with juniors and leave you dependent on them. The weekend-rebranded "AI" web agencies cannot build a production model that survives contact with real OT data and a sub-micron tolerance. We are the AI engineering partner in the middle: senior people stay on your project from audit to launch, and you end up owning the solution outright — code, model and pipeline.
The commercial path is transparent and fixed-step, all prices excluding VAT. An AI Audit & Strategy at EUR 2,500 pinpoints where the money actually leaks — downtime, scrap, yield or the labour bill — and whether AI is even the right tool. A Proof of Concept at EUR 20,000 puts a working model on your own machine data so you judge it on results, not slides. Production launch starts from EUR 50,000, with day-rate guidance around EUR 150 per hour. You can see the full breakdown on our pricing page, and the breadth behind it across 13 delivered case studies spanning predictive maintenance, computer vision, demand forecasting and NLP. If OEE, downtime, scrap or first-pass yield are the numbers keeping you up, those are exactly the numbers we like to attack first — start with a short conversation through our AI consulting team and we will map a realistic path from a single use case to AI running live on your Brainport floor.
Eindhoven and the wider Brainport region host a dense high-tech ecosystem around ASML, the High Tech Campus, the Automotive Campus in Helmond and many specialised software and AI firms. For industrial and manufacturing AI specifically, Crux Digits serves Brainport companies from nearby Nieuwegein, combining senior consultants with hands-on engineering rather than the junior staffing typical of large consultancies.
Brainport manufacturers apply AI to the numbers that decide profit: predictive maintenance to cut unplanned downtime, computer-vision quality control to lift first-pass yield, OEE optimisation and process automation to reduce scrap and micro-stops, and demand forecasting to stabilise production planning. The biggest, fastest wins usually come from protecting expensive machine-hours and catching defects before they reach a demanding OEM customer.
The best fit for a Brainport manufacturer is a senior-led partner that treats the factory floor as the spec and can survive real OT data and tight tolerances. Crux Digits is a boutique AI consultancy that sits between heavyweight firms and rebranded web agencies: senior people stay on the project from audit to launch, you own the code and model outright, and pricing is fixed-step and transparent.
AI reduces downtime through predictive maintenance. Models read vibration, current, temperature, acoustic signatures and cycle-time drift, learn the difference between normal wear and an impending fault, and flag the failing component early enough to schedule the fix. Maintenance shifts from emergency to planned — far cheaper and less disruptive — with fewer surprise stops, longer asset life and a more predictable spare-parts budget.
Crux Digits uses fixed-step pricing, excluding VAT. An AI Audit & Strategy at EUR 2,500 pinpoints where money leaks — downtime, scrap, yield or labour — and whether AI is the right tool. A Proof of Concept on your own machine data is EUR 20,000, and production launch starts from EUR 50,000, with day-rate guidance around EUR 150 per hour outside the ladder.
It depends on data readiness, but a Proof of Concept on your own parts typically comes first so you judge results before committing to production. Much of the timeline is data engineering — capturing labelled images, handling glare and motion blur, and integrating with the line. We size the opportunity in euros up front, so you know what recovered yield or fewer warranty returns are worth before building.
No. Crux Digits is based in Nieuwegein in the province of Utrecht and serves the Brainport region, the whole of the Netherlands and Europe, working bilingually in English and Dutch. The Eindhoven focus reflects the region's industrial and high-tech density; the same predictive maintenance, computer vision, OEE and forecasting capabilities apply to manufacturers and machine builders anywhere we operate.
Tell us where machine-hours, yield or quality leak on your Brainport floor — we'll map a path to value in a free consultation.
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