Machine Learning technology helps validate job completion as Telent continues in its mission for improved productivity


Telent has enhanced its SOLO application, with Machine Learning (ML) technology, enabling it to build ultra-fast broadband infrastructure projects at scale and with predictable quality by providing digital information and photo evidence of completed work packages.

The SOLO technology uses images captured via smart phones to validate job completion. The work is inspected and verified via the images with the support of ML technology, which are then stored for future reference.

This software will ensure Telent can increase visibility of building sites, infrastructure, and planning processes for works to be completed to the highest quality possible. Furthermore, SOLO can display predictive working indicators for added visibility and real-time management. The data flow is capable of scanning an image across multiple workstreams within a few seconds, increasing efficiency, throughput and time-effectiveness.

Ric Welsby, Managing Director, Telent Infrastructure Services said: “This is a very exciting time for Infrastructure Services, and this demonstrates how we are adapting technology to enable us to build fibre networks at scale with consistent, predictable high quality. As we continue to trial innovative new products and utilise such impressive resources, we expect to see an increase in our quality service and productivity across our business in the forthcoming months.”

Telent has branched out through ML, to create a software solution that aims to improve the SOLO service experience through a cost-effective form of Artificial Intelligence (AI). Following a successful proof of concept using ML, the new functionality is now in full production use and includes enhancements that enable predictive maintenance, complex image scanning and consistent updates based on programming automation for future reference.

The ML and AI type solutions utilised by Telent propel the SOLO application to new heights beyond simple database, forms and reporting. This presents substantial potential for further application use going forward, allowing Telent to continuously improve real-time quality, visibility and productivity of service, as well as safety of its workers.

Senior Business Systems Analyst Hari Yenumula, responsible for SOLO’s photo validation technical requirements reported a predictive accuracy of more than 95%, when the system is run 24/7. SOLO went live earlier this year and has since automatically scanned millions of images without human intervention. Due to these impressive results, the SOLO application has now been fully deployed at Telent and is set to handle higher volumes in the future.

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