Facebook’s Artificial Intelligence Research (FAIR) has hosted the bAbI QA tasks challenge since 2014 to encourage the research community to build machines that have the capability to process Natural Language. The challenge has been segregated into twenty distinct tasks that assess various distinct capabilities displayed by humans. The tests include complex tasks such as co-reference resolution, time and space reasoning, path navigation, size reasoning etc. DataVal is proud to claim that it has been able to build the core NLU engine that successfully completed all the tasks with 100% accuracy using a single common framework. DataVal NLU Core Engine is able to process the task without using large training datasets but by semantically training the vocabulary based on real world knowledge. This unique approach of DataVal provides the capability to build customised processing engines that can be used across different domains.