We build spatial models that rank sites, risks and options against the criteria you set. Each result shows its inputs and weights, so planners and engineers can defend the choice to a board, a donor or the public.
Imagery: Sentinel-2 cloudless 2023 by EOX IT Services, modified Copernicus Sentinel data (CC BY 4.0). Terrain: SRTM via AWS Terrain Tiles. Roads and buildings: © OpenStreetMap contributors (ODbL).
3
multi-hazard risk assessments: Astore, Nushki and Budalas
30+
projects delivered across climate, GIS, AI and ESG
1.5MW
hydropower facility screened for flood, slope and seismic hazards
1,045km²
of land affected by the August 2025 floods, measured from radar
Each service turns a planning question into a model with clear criteria, so the answer can be checked, repeated and updated when conditions change.
Candidate sites scored on slope, access, hazards, land use and rules, so the shortlist is based on evidence.
Hazard, exposure and vulnerability combined into risk zones for districts and sites, the method behind our MHVRA work.
What if models that test a flood level, a new road or a land use change before anyone commits money.
GIS based EIA support: baselines, sensitive receptors and impact zones mapped and modeled for project approval.
Interactive tools that put risk layers, models and indicators in front of officials, like our Astore portal.
Machine learning that finds patterns across hazard, terrain and climate data, then predicts where risk is likely to rise.
Spatial decision support suits choices that are costly to reverse: where to build, what to protect first and how to spend a limited budget.
Risk zones and priority lists that help district officers decide where to place shelters and spend mitigation funds.
Hazard screening around plants, intakes and transmission routes, like our assessment of the 1.5 MW Budalas facility.
Route and site options compared on terrain, hazards and environmental limits before design work is locked in.
Suitability and scenario models that show where a city can expand safely and which areas to keep open.
A model is only as useful as the trust people place in it. We build that trust by agreeing criteria with you before running any numbers.
We write down the choice, who makes it, the options and what success looks like.
Decision statement
Hazard, terrain, land use, population and asset layers collected and checked for gaps.
Evidence layers and gaps
Criteria, weights and thresholds set in workshops with your technical staff.
Signed off criteria
Suitability, risk or scenario models run, tested for sensitivity and checked against known events.
Ranked results and maps
Results explained in plain terms, with the model and data handed over for reuse.
Briefing, model and data
We choose the data source and the software to fit the job, then deliver in formats your team can open.
Tell us the decision, the area and the deadline. We will suggest the criteria, the data needed and a clear way to model it.
