Way of Working
DATAbility was built to help businesses scale and grow. We empower you with cross-industry know-how and agile development teams.
Are you interested in how DATAbility can work with you?
The innovative SMART Data approach combines engineering domain knowledge of systems with AI technologies.
DATAbility merges classic engineering methods and analog expert knowledge with AI and Machine Learning.
We adapt (AI) algorithms and data models to your needs, taking into account the product and process knowledge you have built up. But there is even more: the results are transformed into comprehensible recommendations for action to support your decisions.
The combination and processing of data from different sources creates completely new possibilities. These include, for example, maintenance logs, images, videos, sensor recordings and other sources in addition to transactional information. The combination of existing data with, for example, weather and environmental data builds new information services.
The focus is on examining individual behaviour and current needs. By further interpreting the insights gained in the predictive analysis as a basis for action, data flows are better understood. In addition, influences or customer feedback can be evaluated to optimise future offers.
Artificial intelligence tools enable novel processing of these data and sources and allow value-added use of the knowledge generated from the analysis for the automation of tasks in your daily operations.
Leveraging data-driven insight, we tailor solutions to precisely meet your business needs. From meticulous forecasting to adaptable planning, we ensure your capacity aligns seemlessly with market demands. Our commitment to continuous improvement guarantees that your sales plans evolve alongside your growth aspirations.
Historical data, real-time information, statistical models and methods from the field of data mining and machine learning can be used to generate insights into current and future process and data characteristics. For example, methods for regression and classification such as algorithms for neural networks, Markov chains, decision trees or support vectors are used.
The AI technologies and functions used can be adapted to the individual data situations and needs of providers, operators, municipalities and user groups.
Start with our free workshop to identify opportunities and risks of your specific use cases in advance.