accelerateKI
Service-based AI configuration support as an accelerator for AI applications in SMEs (small and medium-sized enterprises).
The potential applications of methods of artificial intelligence (AI) can be found in heterogeneous areas such as process analysis and monitoring, logistics optimisation and increasing the degree of the automation of business processes. So far, however, these high potentials have been countered by barriers to the widespread use of artificial intelligence. The central barrier in SMEs is the large amount of effort required to collect and record data, the lack of experience in statistical evaluation and pre-processing and the low level of expertise in the creation and application of data models & AI.
The accelerateAI research project addresses the barriers SMEs face when using artificial intelligence methods by researching and developing a service-based and platform-independent AI configuration support. The project aims to significantly increase the applicability of AI algorithms with the goal of lowering the inhibition threshold and development time in the use of AI in SMEs.
Use-Case Report Assistance
The company SX Semantics has developed a cloud-based software that automatically creates texts in 110 languages from classifiable content and can be used for natural communication with people. Successful areas of application are automated texts, e.g. for e-commerce portals or publishing houses. In the future, this technology will be used in the production environment to provide people with targeted information from existing IT systems. In order to interpret contextual information from data sources, those responsible have so far had to navigate through ERP/MES systems, analyse Excel tables or conduct time-consuming manual research in order to obtain an overall picture of the current situation and, if necessary, identify the causes of problems. Therefore, a chatbot with a configurable AI component will be implemented, which determines patterns between company-internal and, as necessary, also publicly accessible data and outputs them in natural language.
Depending on the design of the AI component, report assistance can be used, for example, to identify problems in manufacturing or assemtly processes more quickly, to support the selection of the most reliable delivery service or supplier, or to forecast incoming orders or returns.