THE PROJECT
A model of the tree
we’re actually looking at.
CrannAI began with a simple but difficult question: can an individual scanned tree be reconstructed through a plausible growth history, then used to explore what could happen next?
WHY BUILD IT
Tree science, arboriculture and digital development.
CrannAI is being developed from professional arboricultural work alongside GIS, CAD, LiDAR and software development. The aim is not to replace professional judgement, but to make individual-tree evidence easier to measure, test and reason about.
The long-term research direction is a digital tree whose structure develops year by year and can be compared with real observations. The commercial platform is the infrastructure that lets specialised tree systems become usable products without compromising that research standard.
That means keeping measured information separate from estimates, recording what a model actually used, and being explicit about uncertainty and validation.
THE VISION
Measure it.
Reconstruct it.
Then test change.
LiDAR and quantitative tree structure can provide a measured reference. A growth engine can then attempt to explain how structure could have developed and explore plausible future trajectories under stated conditions.
Separate commercial modules can use the same underlying discipline: Report Intelligence should be able to show which evidence supported a draft; LiDAR tools should preserve provenance; growth outputs should carry model/version information rather than being presented as certainty.
CrannAI Suite provides the shared account, security, API, job, knowledge and usage infrastructure around those products.
See the platform architecture ↗