The success and the utility of Artificial intelligence is directly linked to data. A typical child will create on average 100 meaningful learning inputs a month that can be providing parents real-time, accurate and research-validated insights about their child's academic progress. With this data machine learning algorithms can begin to identify and unlock trends within the data . The more data inputted the more capable the algorithms will be in providing insights and analyses. Examples of the type of insights over time will include : short-term gap analyses; demonstrating how your child's performance fares with curricular learning outcomes. In the medium term, report trends about your child’s progress; bench marking it against national and global data. In the longer term, and as more data is provided and machine learning algorithms are trained, a complete personalised learning journey tailored and optimised to an individual child's learning patters
