A shared operational intelligence system for vegetation clearance and utility arboriculture — turning individual surveys into a collaborative, predictive network.
The Mechanisation Planner translates survey data — DBH, vegetation density, terrain, access — into a defensible deployment plan, with productivity forecasts you can take into a tender.
The platform fuses HMLR, OS and LandIS datasets into a single mech-suitability score per land parcel — so the planner knows what you can actually do on the ground before mobilisation.
Pull title numbers, ownership and tenure for every parcel touched by the corridor.
2 m RMSE digital terrain model for slope, exposure and access modelling.
Soil wetness classes (W1–W4), drainage and bearing capacity for plant suitability.
Flood Zone 1–3 overlaid against access routes and compound locations.
Every parcel gets an AI-derived suitability score combining slope, soil wetness, ground-bearing rating (1–5), flood zone and land cover. Planners see at a glance which sites are go, restricted or no-go for each machine type.
Contractors, consultants and asset owners anonymously contribute and access aggregated mechanisation and productivity data from live projects.
Live productivity and access intelligence from active vegetation management cycles.
National Highways framework area data shared between regional contractors.
Possession-window data on machine performance across Network Rail environments.
Site-based clearance benchmarks across compounds, depots and laydown areas.
BNG and habitat creation projects feed back into ecological constraint intelligence.
See what's available near a site before mobilising plant from depot.
Cost and efficiency benefits compound across the framework — for contractors, utilities and infrastructure clients alike.
Find machinery already operating nearby, contractors mobilised within the same region, and shared haulage opportunities. Lower low-loader transport, fuel, idle time and double mobilisation of specialist plant.
Benchmarked productivity helps planners select the most efficient machine for the terrain, reducing unnecessary movements and overpowered deployments. Supports both cost reduction and ESG targets.
Build evidence-based pricing models, forecast machine hours more accurately and reduce contingency inflation. More competitive tenders, reduced commercial risk and better budget forecasting for clients.
Avoid incorrect machine deployment, access-related delays, underestimated vegetation density and unplanned ecological stoppages — by learning from previous jobs before work begins.
A forestry mulcher working on a National Highways verge scheme could be redeployed directly onto a nearby utility corridor project rather than returning to depot — saving both clients significant transport and mobilisation costs.
The platform supports a future model where contractors share non-sensitive operational availability and framework partners coordinate specialist plant deployment.
Regional framework areas coordinated across contractors.
Cyclical vegetation programmes synchronised across DNOs.
Possession-window plant deployment optimised regionally.
Large regional habitat & BNG schemes share data streams.
Predictive capabilities help contractors and asset owners make data-driven decisions before works commence.
Forecast clearance rates per crew, per machine, per terrain — calibrated by live framework data.
Compare actuals against benchmark performance to spot underperforming plant or operators.
Forecast environmental impact on programme by season, region and exposure.
Early warning where comparable jobs have historically slipped — flagged before mobilisation.
Forecasts likely ecological stoppages by site type, season and historical patterns.
Estimate emissions and fuel use per option — feeding directly into ESG dashboards.