The mountains of Adamawa. We can see you.
From collection to understanding.
Operational intelligence from drone, geospatial, and sensor data.
Nigeria · Mount Dimlang · 8°23′42″N 11°46′36″E
Terrain and mission illustrative
01The problem
Drones collect data.
A single operation can produce hours of video, thousands of stills, thermal passes, and continuous telemetry. More sensors means more of it, not more understanding.
Dimlang turns data into intelligence.
Organised by place and time, tied to its source, and reviewed by people who can act on it. That is the layer Dimlang is building.
02The platform
Dimlang is not building drones. It is building what sits behind them: the pipeline from raw mission data to something an analyst can review and a responder can use.
Drone, EO, IR, sensors, mission files
Secure transfer and normalisation
Mission · location · time · sensor
Geospatial analysis and computer vision
Analyst workspace
Human operational response
Human-led
03Flagship use case
A search can generate enormous amounts of imagery, video, location data, telemetry, and repeated observations of the same ground. The hard part is not collecting more. It is turning what was collected into something an analyst can understand quickly.
The aim is that significant observations surface sooner, and that every one of them can be traced back to the frame it came from. Decisions stay with the responders.
04How Dimlang is built
No finding without its source. Every observation opens to the frame, position, time, and sensor it came from.
Models narrow what an analyst must inspect. Review, judgement, and every operational decision remain human.
Designed for private cloud, on-premises, edge, and disconnected environments, under the operator's control.
For government, research, technology, public-safety, and search-and-rescue organisations.
