AI consultant in Almere

Under the traffic order of June 2026, from 1 January 2028, only zero-emission commercial vehicles and lorries will generally be allowed in the main shopping areas of Almere Stad, Almere Haven and Almere Buiten. Commercial vehicles with emission class 6 may still enter until 1 January 2029. For some lorries, the deadline is 1 January 2030, depending on their type and date of first registration.

For each vehicle, you therefore need its emission class, date of first registration, contract end date and journeys to the town centres. If those details are held in different systems, you can bring them together by registration number. This usually calls for a dashboard, for example in Power BI, not an AI model. The municipality has a logistics adviser who can advise on the transition itself.

First, you need to know what is currently in stock and what is being used. At Athlon, parts for maintenance and repairs were tracked in separate systems and spreadsheets, so no one had a complete, up-to-date picture. Together, we built a central data platform for purchasing, the workshop and logistics, with a pipeline on Azure to synchronise the sources automatically.

We then developed a reservation system and predictive models using machine learning to show which parts would be needed and when. Check first whether a part has the same number in the purchasing and workshop systems; if not, you will need a mapping table. Read the Athlon case study.

You can see how quickly tyres wear and where consumption differs from what you expect. For Athlon, we built dashboards using Qlik, Python and Snowflake that gave the asset management team insight into the fleet’s tyre consumption and wear patterns. The team could then identify and address unexpected tyre wear and consumption.

A dashboard like this is a sensible first step: only once you can see where the differences are can you tell whether predicting wear would add value. Read the tyre wear case study or learn more about business intelligence.

That depends on the purpose. Journey data from telematics — the in-car system that transmits journey and location data — is personal data if it can be linked to a driver. In that case, the GDPR applies. If a system can track employees’ behaviour or performance, a works council generally has the right to approve its introduction (Article 27 of the Dutch Works Councils Act, WOR).

Annex III of the AI Regulation lists AI systems intended to monitor and evaluate people’s performance and behaviour in a work relationship. Such systems are generally high-risk, with requirements applying from 2 December 2027. A model for wear or parts demand can often operate at vehicle level, although a registration number can also be linked to a driver.

We can help you take stock and prepare the risk classification; your legal or compliance team decides on the legal interpretation. See also the AI Act.

According to the municipality of Almere (2020), Stichtsekant, alongside the A6 and A27, mainly attracts distribution and logistics companies with large warehouses. Flevokust Haven in Lelystad combines a multimodal inland port with a business park, where JYSK and BESTSELLER are among the companies that have chosen to establish a distribution centre.

In warehouses like these, the first questions may be about planning: which shipment goes to which loading dock, or whether a container travels by water, rail or road. A model using order and journey history can make a suggestion for the planner to adjust or approve. Read more about optimising planning with AI or data in logistics.

Yes. Athlon Netherlands has its visitor address on Veluwezoom in Almere, and we worked with Athlon on inventory management and tyre wear analysis. According to the municipality’s economic agenda (2023), Almere is a young city with a relatively strong ICT and technology sector, where major companies have their headquarters.

We work from Amsterdam, on Westerdoksdijk. We can come to you for a meeting, or meet online.

When a list or fixed rule already answers the question. You can identify which vans are not zero-emission from their registration numbers and contracts. A minimum stock level per part that works in practice does not need to become a predictive model. An overview or a setting in the existing system is enough.

A model only pays off when there are many vehicles, parts or journeys and the same decision comes up repeatedly. For a small fleet or organisation, data and AI for SMEs is a more sensible starting point.