Storm Damage Map

Rapid satellite and drone analytics pinpoint grid asset damage after severe storms, accelerating repairs and minimizing outage duration.

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How does it work?

Utilities often face lengthy manual inspections and safety risks when assessing widespread grid damage after severe storms. AI-driven geospatial analytics automates damage detection from satellite and drone imagery, delivering rapid, actionable maps to prioritize repairs.

Rapid Damage Detection: Our AI models analyze high-resolution satellite and drone imagery to identify damaged poles, lines, and equipment within hours. This reduces assessment time from days to mere hours, enabling faster decision-making.
Enhanced Safety: Remote damage assessment removes the need for crews to navigate unsafe, storm-affected areas for initial inspections. It minimizes exposure to live wires, debris, and flooding, improving overall crew safety.
Repair Prioritization: Damage severity and location data feed into automated prioritization algorithms to rank repair tasks by criticality and accessibility. Field teams receive focused work orders, optimizing resource allocation and reducing downtime.
Cost Efficiency: Automating inspection workflows cuts manual surveying costs by up to 50%, according to industry benchmarks. Reduced field hours and travel lower operational expenses while maintaining comprehensive coverage.
Comprehensive Coverage: The platform processes imagery across thousands of square kilometers, ensuring no damaged asset is overlooked. High revisit rates from multiple data sources guarantee up-to-date assessments.
Seamless Integration: Damage detection outputs integrate directly with existing GIS, OMS, and asset management systems via standard APIs. This ensures consistent data flow and simplifies dashboarding and reporting.

Frequently asked questions

Have a different question and can’t find the answer you’re looking for? Reach out to our support team by sending us an email and we’ll get back to you as soon as we can.

How does this AI-based assessment compare to manual inspections?: Automated analytics deliver results in hours versus days for manual surveys and minimize human error. While manual crews provide ground-level details, AI assessments offer rapid, high-level overviews to guide targeted field work.
Why is this solution popular among utility operators?: Utilities favor it for accelerating outage restoration and optimizing resource deployment after storms. Its integration with GIS and real-time mapping tools has driven widespread adoption to improve reliability metrics.
Can I use only drone data instead of satellites?: Yes, the platform supports both drone and satellite imagery and can blend multiple sources for higher resolution or broader coverage. Users often combine drone data for local detail with satellite data for area-wide context.
What are the limitations in urban or forested areas?: Dense canopy cover and complex urban structures can obscure grid assets in optical imagery, potentially reducing detection accuracy. Combining multispectral or LiDAR data and periodic ground-truthing helps to mitigate these challenges.
How often can damage assessments be updated after a storm?: Update frequency depends on imagery availability—satellites offer daily to weekly revisits, while drone flights can be scheduled on demand. The system automates data ingestion and processing as soon as new imagery arrives.
Are there alternative tools for grid damage assessment without AI?: Non-AI alternatives include manual drone inspections and hotline reporting, which are more labor-intensive and slower to scale. AI automates detection and mapping, reducing inspection time and subjectivity compared to traditional methods.

Geospatial AI Platform

Intelligence

AI & foundation models

Deep-learning and foundation models turn raw imagery into ready-to-use insights, so you ship answers instead of training pipelines.

Experience

Conversational workflow

Ask questions in plain language and the platform responds with charts, visualizations, and next step suggestions.

Speed

GPU-accelerated cloud

Cloud-native architecture spins up on-demand GPU clusters that scale from a single scene to global archives—no manual ops, no bottlenecks.

Data

Any sensor, any format

Optical, SAR, drone, IoT, vector or raster—ingest, fuse, and analyze without conversion headaches.

Visualization

Insight you can see

Real-time 2D / 3D maps and export-ready plots make results clear for engineers, execs, and clients alike.

Boost your productivity. Experience Geospatial AI.

Turn satellite, drone, and sensor data into clear, real-time insights using powerful AI – no complex setup, just answers you can see and act on.

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