The cloud-based asset inspection software platform from Scopito is designed to support autonomous smart analytics data management and reporting for infrastructure inspection operations. At NestGen 2025, members of the company’s team demonstrated how the organization is utilizing drone captured data to train AI models to generate accurate and accessible reports for their customers.
“Our goal is that in the future, you can click a button and the inspection is done. Then the report and analysis are done in one click,” said Dani Keller, VP of Sales at Scopito. “We are moving there in big strides.”
During the session “Smart Analytics & Data Management for Automating Infrastructure Inspections,” Keller reported that, when his company first started, their team would fly drones for infrastructure inspections and capture thousands of photos. Those photos would be loaded onto an SD card and provided to the client. It would then take hours for photos to load on the client’s side, making this an inefficient process. Recognizing that rapid response is crucial for minimizing risk, not just financial loss, Scopito began to explore ways to leverage AI to dramatically improve data management efficiency.
Fast forward to today, Scopito has increased their efficiencies for their clients and themselves. Now, as explained during NestGen, each drone-captured image is automatically uploaded to their project on the cloud and is accurately placed on the map of the inspection site. Users have the ability to pinpoint a specific area on the infrastructure asset to further analyze it, determine what the issue is, and what the solution is.
Their software, Keller asserted, allows users to make annotations on inspection photos, which can later be utilized to create an AI-driven workflow capable of analyzing all the photos and identifying problem areas. Keyboard shortcuts allow users to quickly annotate common issues found on structures. Once annotations are made, the software compiles them into a work order, streamlining the process.
At NestGen, Keller described how users can also filter the images to focus on specific problem areas, such as filtering by the severity of the issues or identifying particular defects, like lightning strikes on powerlines. This filtering capability enhances efficiency by narrowing down the data and enabling the generation of targeted reports. The system allows users to customize filter properties according to their organization's severity assessment guidelines.
For example, if the company considers a missing part a level 3 severity whereas a crack might be a level 1 severity, they can program that into their filters which will later be reflected in the reports. This granular control ensures the system reflects the company's unique priorities and risk assessments.
With the addition of this type of one-click solution, Keller explained, inspections can happen at a faster rate with less time between flights, data management, and getting the reports and work orders in the client’s hands. By minimizing downtime, assets like solar farms, wind turbines, and powerlines are better maintained and are less likely to suffer from damage that causes widespread outages.
“This is huge for our team because it means they don’t have to manually shift through thousands of images and it allows our end users to track asset health overtime to prevent failures from happening”, explained Ravid Barash, CMO at Kronos Group, who uses Scopito software for inspections.
These tools and capabilities are part of larger effort to build a library of common issues noted among inspection images that become the building blocks for training the AI platform. Scopito is testing to see if the data meets the criteria to eventually reach full automation. This shift would give time back to staff to run more inspections and to get out in the field to fix issues before they turn into problems, creating both measurable and intangible value.
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