AllConnects is a Flemish specialist in fleet and asset management. With FLEET.connect, CHECK.connect, and LIVE.connect, companies in the construction, transportation, engineering, and rental industries track their vehicles, machinery, and teams, and that data is fed into their own business software via API integrations.
Why this question is popping up everywhere right now
Most fleet management platforms were built at a time when no one had heard of AI assistants. Today, for example, you can already use them to summarize emails, rewrite quotes, or analyze an Excel spreadsheet. So the next step is logical: why not do the same with data from your vehicles and machinery?
You'll want answers to questions such as:
On top of that, more and more companies are building their own small applications, often with the help of AI itself. When you start from a blank slate, it works surprisingly well. It only gets tricky when that application has to integrate with an existing system. And that’s exactly what an integration with your fleet data is.
From Data to Less Manual Work: The Role of an API
Your fleet management platform collects information about locations, trips, mileage, operating hours, and more. That data is also valuable outside the platform: in your scheduling, invoicing, maintenance tracking, or accounting.
An API (Application Programming Interface) is the connection that allows two software systems to exchange data. With an API, no one has to manually retype the same mileage or number of operating hours from one screen to another.
At AllConnects, API integrations are included with every FLEET.connect subscription. We offer three types of integration, depending on what your existing software can handle:
You can read more about this on our page about API integrations for track & trace.
API and MCP: What's the Difference?
The term MCP is also popping up more and more often. MCP stands for Model Context Protocol: an open standard that allows AI assistants such as Claude, ChatGPT, or Copilot to access data and functions in other systems. Through a specially configured MCP connection, an AI assistant can retrieve information on its own, rather than requiring you to first export it and paste it into a chat window.
| API | MCP | |
|---|---|---|
| What is it? | A connection through which software exchanges data | A standard that gives AI assistants access to data and features |
| Who uses it? | Your planning software, ERP, accounting, and dashboard | An AI assistant or AI application |
| Example | Mileage readings are automatically added to your maintenance schedule every night | You ask an AI assistant which machines ran the least last month |
| How do they compare? | MCP does not replace an API. It is, in fact, an access layer for AI that is typically built on top of existing APIs. | |
Not every platform can just connect with any AI assistant
Integrating your fleet management platform with an AI assistant requires the right technical infrastructure as well as clearly defined access rights: Who is allowed to view which data, and is the AI permitted only to read the data or also to make changes? The options available therefore depend on your platform, the available data, and the chosen integration method.
A mileage reading isn't always the same mileage reading
However, fleet data is more disorganized than you might think. For example, two devices transmit the same value but in different formats. One tracker sends an update every few seconds, while another does so only at set intervals. Sometimes a file even arrives at a time no one expected.
Take the odometer reading, for example. It can be determined in at least three ways:
| Source | How it works | What to Look For |
|---|---|---|
| CAN bus | Read directly from the vehicle: the odometer reading itself | Not every vehicle or brand releases every value |
| GPS-calculated | Calculated based on the tracker's GPS movements | May differ from the odometer reading, especially in cases of poor reception or short trips |
| Entered manually | Copied from a gas receipt, maintenance invoice, or vehicle inspection certificate | Typos and outdated values |
For a single vehicle, that might seem like a minor detail. But if you have an AI application compare 100 vehicles—half of which transmit CAN bus data and the other half GPS-calculated data—you’re comparing apples to oranges. The answer sounds convincing, but it’s not correct.
Anyone who combines data from different sources must therefore know the following for each value:
AI can help interpret data. However, the quality of the source data remains the determining factor. You can read more about the difference between calculated and raw data in our article on AI in fleet management.
Why It Works in Testing but Not on the Track
An initial test with an integration often yields quick results. You first retrieve some data, then have an AI assistant summarize it, and the results look impressive.
The challenge arises when that connection has to keep working every day: with dozens of vehicles, different trackers, machines that sit on a construction site for weeks, and a delivery van that temporarily loses signal in an underground parking garage.
What worked yesterday doesn't work today
After all, most problems with fleet connections aren’t visible in a demo. You only discover them once the actual vehicles are on the road: a changed format, a tracker that sends data later than planned, a value that’s suddenly missing. That’s why you should build in from the start what needs to happen if data doesn’t come through.
Start with one specific question
Do you want to get more out of your fleet data? Then don't start with the technology—start with the work you want to make easier.
Select one application
For example: entering mileage data into your maintenance schedule, using operating hours as the basis for your rental records, consolidating vehicle data in your company dashboard, or having an AI assistant summarize a periodic fleet report.
Determine what information you really need
Not everything the platform collects, but only what that specific application needs. Then, for each piece of data, record where it comes from and how often it is updated.
Test using real-world scenarios
And then there are the tricky ones: a vehicle that’s temporarily offline, a machine that’s been idle for a month, a missing value. After all, that’s exactly where you see whether the connection holds up.
Measure the results, and then expand
How much manual work will be eliminated? How many fewer errors will there be? Only once that first application is running reliably is it time to move on to the next one.
Be careful with personal information
Trip and location data can often be traced back to a driver or employee and are therefore subject to the GDPR. Therefore, verify where an AI application processes and stores the data, check whether there is a data processing agreement, and inform your employees in advance. Technical data, such as operating hours or error codes, is generally less sensitive than data regarding the driving behavior of a specific individual.
You also need someone who understands how you work
For a long time, the software itself was the most important factor in choosing a fleet management platform: the screens, the reports, and the way it worked. Now that it’s much easier to extract data from a system, that’s changing. It’s increasingly about how easily you can format your own data the way you need it, rather than having to learn how the platform presents it.
So, ask your supplier these questions before you start working on an integration:
Because a good data integration requires more than just technical access. You need someone who can explain why data differs, who can help you think through the design, and who is available when an integration suddenly stops working as expected. Someone who, if things go wrong, will be right by your side with a fire extinguisher in hand.
At AllConnects, we therefore start with your operations. What do you want to improve? What information do you need to do that? And how can you make that information usable in the systems you already use?
Want to integrate your fleet data with your business software or an AI application?
Tell us what you want to achieve. Then we'll work with you to determine what data you need, which integration is right for you, and what you can expect from it.
Get adviceFrequently Asked Questions
Can I link my fleet data to an AI assistant like Claude or ChatGPT?
That’s possible, but it depends on your fleet management platform, the available data, and the chosen integration method. The simplest approach is to export the data or retrieve it via an API and have it analyzed by an AI application. A direct integration—for example, via MCP—requires the appropriate technical infrastructure and clearly defined access rights.
What is the difference between an API and an MCP?
An API is a connection that allows two software systems to exchange data, such as your fleet management platform and your scheduling software. MCP (Model Context Protocol) is an open standard that allows AI assistants to access data and functions in other systems. MCP does not replace an API, but is typically built on top of it as an access layer for AI.
Why do the two systems show different mileage readings?
This is because mileage can be determined in various ways. One method reads the data directly from the vehicle via the CAN bus; another calculates it based on GPS movements; and a third involves manual entry. The timing of when a device transmits data also plays a role. Anyone compiling data must therefore know, for each value, where it comes from and how recent it is.
Are API integrations included with FLEET.connect?
Yes. API integrations are included with every FLEET.connect subscription. Depending on your existing software, this can be done by exporting and importing reports, through reports retrieved by your own software, or through direct data exchange in both directions.
Can I upload drivers' trip data into an AI application?
Trip and location data that can be traced back to an individual are subject to the GDPR. You therefore need a legal basis, must inform your employees in advance, and must verify where the AI application processes and stores the data, including a data processing agreement. In addition, use technical vehicle data or anonymized reports whenever possible.
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CAN bus data, really? Integrations API Integrations for Track & Trace
Hilde Lavrijssen Marketing Manager at AllConnects. Writes about fleet and asset management, workplace regulations, and what data can and cannot mean for a Belgian vehicle fleet.
Inspired by a post from our international technology partner about the growing demand for API and AI integrations in fleet management.
