Landslide Risk Scoring

Pioneering Landslide Risk Assessment with Cutting-Edge AI

Unlock the potential of satellite data and AI to revolutionize how we understand and mitigate geotechnical risks.

Discover how our Landslide Scoring AI model transforms risk management, ensuring the safety of assets and communities with unparalleled accuracy and insight.

Geotech Risk Scoring​

Our AI model rapidly evaluates landslide risks and opportunities using satellite and geotechnical data, guiding clients in prioritizing and protecting key assets.

Landslide Risk Management

Our AI identifies high-landslide-risk areas, enabling clients to focus mitigation and optimize resource allocation for preemptive engineering solutions.

Geotech Risk Scoring​

Our AI model analyzes satellite imagery, weather, and geotechnical data to quickly and objectively assess both landslide risks and potential opportunities near key assets.

It prioritizes areas for protection based on risk level, helping clients make informed decisions to plan development projects and infrastructure investments (e.g. roadways, factories, power plants)  with reduced landslide risks. 

Safeguard Critical Assets

Assets can be more protected by the client by preparing engineering interventions to areas with high scores for a landslide.

Create New Business Strategies

The client will be able to derive new data-driven insights based from satellite imagery, weather, and geotechnical data.

Landslide Risk Management

Our AI model can analyze data and pinpoint areas with a high probability of landslides, allowing clients to prioritize mitigation efforts and resource allocation.

By identifying high-risk areas through our model, the clients can optimize resource allocation for engineering intervention before a landslide can occur.

Optimized Resource Allocation

Strengthens the new customer onboarding process with scored KYC data, incorporating ADI’s POI dataset for an additional layer of risk assessment.

Citizen safety and crop preservation

Affected people can be informed on the new insight regarding areas that have high landslide risk.


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