Data Panda pulls your GeoFleet vehicles, drivers and route markers and lines them up with the rest of your fleet stack. From one place, we turn it into dashboards, automations, AI workflows and custom apps your fleet manager, finance and dispatch teams use every day.
GeoFleet is the fleet platform built by Geotracer, a Belgian company headquartered in Oosterzele with more than twelve years in geolocation and telemetry. The team is small (about sixteen people across customer success, sales, planning and installation, finance and support) and they run the platform from the same building they install the hardware out of. Sectors on their site span transport, construction, equipment rental, service businesses and asset tracking, with named references like Willemen, Knauf, ALM Lift, Helder and Duvel.
For a fleet manager, GeoFleet is the system of record for which vehicles are out, who is driving them, and which sites or customer addresses (the markers) those vehicles touch through the day. The portal handles the live map well. The harder questions, like which van-driver pairs are racking up the most kilometres on which markers, how site visits line up with the dispatch plan, or which assets keep showing up on the wrong customer address, sit across GeoFleet and the systems around it. Pulling objects, persons and markers into a warehouse is how those answers stop being a portal export that gets forwarded as a screenshot.
Vehicles, drivers and markers joined to the accounting, CRM and dispatch data the rest of the business already trusts.
Turn marker arrivals and driver assignments into the nudges finance, sales and dispatch would otherwise chase by hand.
Use the marker history to predict where the fleet will be stretched and which sites take longer than the plan.
Small fleet, finance and dispatch tools that sit on GeoFleet data instead of another portal export.
A list of concrete reports, automations and AI features we have built on GeoFleet data. Pick the one that matches your situation.
Which customer markers are eating the most vehicle and driver time this month?
Marker arrivals per vehicle joined to driver assignments and to the customer that owns the address. Operations sees which sites consistently take longer than quoted, and finance sees whether the time on a marker matches what got billed for that customer, instead of a discussion on a portal screenshot.
Which driver was behind the wheel of that van between 10:00 and 14:00 on Tuesday?
Persons joined to objects through the GeoFleet driver-identification feed, with the active driver per vehicle per time window. HR and dispatch read the same record, so timesheet questions and incident reports are settled on data instead of a phone call to the driver.
Which markers in GeoFleet are not linked to any customer in our CRM?
Markers from GeoFleet matched against the company addresses in the CRM, with the unmatched list flagged. The fleet team cleans the marker library on a real list rather than discovering at the year-end review that half the visited addresses were typed twice with different spellings.
Hours per marker per customer next to the leasing, insurance and labour cost from accounting, instead of three exports stitched together. Site overruns become a monthly conversation with numbers behind them, not a buyback at year-end.
Customer visits verified against the CRM on actual marker arrival per address. Reps keep their autonomy and the sales manager stops phoning around to reconstruct who was where this week from memory and expense claims.
Marker dwell, driver-vehicle pairing and roster adherence on one dashboard per fleet manager. Dispatch and the workshop read the same picture, so the Monday call is about which crew goes where next, not about whose portal export is right.
Vehicle and driver hours per customer marker in GeoFleet are matched to the sales invoices booked on that same customer in Yuki, with the gap per site pulled out. Finance closes the month with each customer either in tolerance or flagged with the exact delta in hours, instead of opening a portal export and a Yuki invoice list side by side.
Driver hours per vehicle from GeoFleet flow into the fixed-asset records in Business Central on the right plate, so engine-hour-based depreciation, residual value and maintenance cost per hour reflect what the van and its driver really did. The finance team runs the quarterly fleet review on live operating-hour data, not on whatever number the workshop wrote down at the last service.
Vehicle arrivals on customer markers in GeoFleet flow into HubSpot as logged meeting activity on the matching company record, with arrival and departure time per stop. The sales manager sees which planned visits really happened and how long each one lasted, instead of relying on a weekly rep report typed from memory on Friday afternoon.
The Solvice route plan for the day is laid next to the actual marker arrivals in GeoFleet, with detour kilometres, marker overruns and skipped stops pulled out per vehicle. The dispatcher sees on Tuesday morning where Monday's plan lost time, and the planning model gets fed back the real travel and dwell times instead of the textbook ones.
These are the 3 tables we currently pull from GeoFleet into your warehouse. Query them directly in SQL, join them to the rest of your stack, or build reports on top.
Missing a table you need? We can extend the sync. Tell us what is missing and we will build it for you.
You keep the reporting tool you already have. We connect it to the warehouse where your GeoFleet data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
The connector brings three tables into the warehouse: objects (every vehicle, machine or asset registered in GeoFleet), persons (the drivers and operators known to the platform) and markers (the geographic points of interest, customer addresses and sites the fleet works around). That is the core of the GeoFleet data model and the right slice for vehicle-driver pairing, marker-time and dispatch-versus-actual reporting. Live position streams, tachograph downloads and temperature-sensor readings are not in this pull today.
The two platforms overlap in fleet tracking, but the connectors expose different slices. TraxGo gives you devices and latest positions, useful for kilometres and live whereabouts. GeoFleet gives you objects, persons and markers, useful for who-was-driving-what and which-customer-site-was-touched. Houses that run both will join them on the vehicle plate; houses that run one cover the report set their connector exposes.
The persons table identifies the drivers and operators registered in GeoFleet so they can be paired to objects and to marker activity. Driver behaviour scoring, tachograph downloads and temperature-sensor readings are captured by Geotracer on their side, but they are not part of the three-table pull this connector exposes today. If you need those in your warehouse, that is a separate scoping conversation with us, not a check box on the existing connector.
We review your GeoFleet setup and the systems around it. Together we pick the first thing worth building.