Nalantis developed a proprietary AI system enabling machines to understand text and natural language. Finding meaning is done by analyzing text linguistically, mapping words and expressions onto a ConceptNet and using powerful semantic pattern recognition to combine these concepts into meaningful entities. Deep Learning is used to build the ConceptNets in general, to analyze the databases to be indexed, for automatic document classification, for domain assignment, and for the generation of additional synonyms to complement the concepts. Deep Learning alone cannot be successfully deployed for text without huge amounts of training and labeled sample data. Nalantis enables unsupervised machine learning for language understanding and applied this for Local Governments to the domain of City Council Regulation and Documentation. Traditionally a massive amount of manpower (by City Officials) is needed to manually tag and index the data stack to allow for better search results. Citynet (a Nalantis Product) is a monthly subscription based SAAS app that allows Cities to simply upload their unstructured City Council Data to the Azure Cloud where its automatically and semantically indexed and made available for Natural Language Querying. Cities can also synchronize their Citynet subscription with Facebook Messenger on their City Facebook Page, automatically creating Citybot without any form of training or query (pre)modeling. The roll-out and ROI of these services is proving itself for a better and faster internal operations combined with a novel service towards citizens in terms of policy and administration disclosure. Pivot your City towards Citizen-Centric policies and position yourself as an Open Data Champion! Citynet APIs are available for Developers. Current available Language Models: Dutch. Expansion to other Language Models throughout 2019.