Case Study: Ulteig improves infrastructure engineering workflows with Roboflow vision AI

Ulteig leverages Roboflow to power vision AI across 45 gigawatts of solar and storage projects

Ulteig, a leading infrastructure engineering and consulting firm, sought to leverage new technologies like machine learning to enhance its services for large-scale energy and utilities projects. One specific challenge involved finding a cost-effective way to gather granular, real-time data on sunlight irradiance across solar fields, which traditionally required expensive specialized devices. To develop and deploy these vision AI solutions, Ulteig partnered with Roboflow.

Using Roboflow's end-to-end platform, Ulteig accelerated its vision AI development. The team utilized Roboflow's role-based annotation tools, cloud model training, and Active Learning to efficiently create highly accurate datasets and train models without investing in expensive hardware. They also employed Roboflow's Workflows to design multi-step logic chains for automated image analysis. This allowed Ulteig to develop innovative solutions, such as a model to monitor cloud coverage and infer irradiance levels, which is crucial for optimizing battery storage operations and delivering enhanced value to their clients.

Ulteig