Infovista, the global provider in network lifecycle automation, announced the availability of its Artificial Intelligence Model (AIM), the commercially available AI-based propagation model that changes the way wireless networks can be planned and optimised. "Operators are at different stages within the 5G rollout, but the majority are still faced with the massive task of selecting, testing and commissioning new sites," says Regis Lerbour, VP product & R&D, RAN engineering at Infovista. "Our AI-based propagation model, successfully introduced to our customers at Infovista RAN Summit, is, by design, cloud-ready and scalable to increase agility and the ability to adapt the network more dynamically, thus offering a way to automate and accelerate the planning and roll-out of 5G networks." Infovista's AIM has been built around state-of-the-art machine learning frameworks such as TensorFlow to focus on training and inference of deep neural networks. The project utilised over 10 million data points collected by the company during the last 15 years and spans multiple sub-6 GHz and millimetre wave bands, geographic locations, antenna heights, weather conditions, seasonal foliage variations and hundreds of additional variables across urban, mixed and rural environments. The AI-model predictions have been extensively validated against real-world measurement sampling data and are proven to deliver network plans that are 25% more accurate compared to those delivered using traditional propagation models.