Trees form an integral part of our environment and world around us and is often used as a measure to determine vegetation health and sustainability. Metrics such as tree counts make up the functional attributes of a vegetation zone and are often used as an assessment measure to manage and minimise the impact on biodiversity from clearing and development works. Conducting tree counts has typically been executed in a very manual, often expensive manner that can be open to human error and safety concerns, particularly in remote and distance locations that are difficult to access. Advancements in machine learning technologies have presented a number of opportunities for companies to simplify these types of activities and provide businesses with a way to utilise resources elsewhere. Decipher has developed a machine learning application with an embedded tree counting algorithm that can automatically detect and count trees across an area. After implementation and some initial ground truthing, the application learns to better conduct these counts over time, allowing users to gather insights remotely and simplify this monitoring and reporting process. Utilising our tree counting framework, Decipher can also produce additional customised algorithms to suit your business utilising imagery.