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Groundbreaking AI-powered platform visualises wireless assets

Talon Aerolytics, a leading innovator in SaaS, Digital Twin capture services and AI technology, has announced ha its groundbreaking cutting-edge AI-powered computer vision platform enables wireless operators to visualise and analyse network assets using end-to-end AI and machine learning. These advancements are set to transform the wireless telecommunications landscape and provide unprecedented value to carriers, contractors and the eco system of partners working to deploy cellular tower sites across the Globe.

Harnessing the power of machine learning and quality control processing, the new offerings have been meticulously developed to address the most pressing challenges faced by the wireless telecommunications sector. By intelligently combining data analytics, predictive modeling, and autonomous decision-making, these solutions aim to revolutionize the way carriers and tower owners validate asset inventory deployed on any site.

The key capabilities of Talon’s AI-powered platform include:

Leveraging the power of predictive analytics, Talon’s AI engine has already been deployed to recognize assets on over 30,000 towers with an incredible 96% AI accuracy score.

Utilizing advanced machine learning algorithms, Talon was able to review and highlight discrepancies on these assets. 

This resulted in hundreds of thousands of dollars of potential savings on this project.

“Our team has worked tirelessly to develop these products with the aim of enabling carriers and their engineers the ability to validate tower asset inventory with increasing accuracy,” said Rod Dir, CEO of Talon Aerolytics. “

In addition to their powerful capabilities, Talon’s AI-powered offerings have been designed with a strong focus on user-friendliness and seamless integration with existing systems. This ensures a smooth transition for organizations adopting these innovative tools.



Source: https://www.eenewseurope.com/en/groundbreaking-ai-powered-platform-visualises-wireless-assets/

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