inovex and partners impress in German federal government AI competition

‘Service-Meister’ project proposal secures financing

(Karlsruhe, 20.09.2019) The German Federal Ministry of Economics and Technology has decided which initiatives for innovative application of artificial intelligence are currently particularly worthy of funding. A project proposal in which the IT service provider inovex is involved was selected as successful in the preceding AI innovation competition. The aim of the ‘Service-Meister’ proposal is a digital service ecosystem that will put small and medium-sized businesses in particular in a position to integrate external partners for services, as well as to further train their own staff in a targeted way with AI support. The platform project will start on 1 January 2020 and be developed to be ready for production by 2022.

‘AI speedboat’ with KROHNE and inovex

Behind the project proposal is an interdisciplinary federation of IT research and IT services companies, coordinated by the eco Association. Within this consortium, together with KROHNE, one of the leading international providers of process measurement technology, inovex is building a so-called ‘speedboat’, which implements a self-contained sub-project. This will involve adding AI functionalities to the existing KROHNE IoT platform, in order to provide the KROHNE service technicians with broad access to auxiliary AI systems and establish an open B2B platform economy. The KROHNE platform, currently without AI and B2B components, is already used by hundreds of customers in the water/waste water industry and is to be expanded to up to 10,000 companies worldwide.

Added-value services through innovative AI modules

The new AI modules that are to be developed include, among other things, visual depiction of sensor data and AI methods for detection of malfunctions, as well as recognition of trends, forecasts and anomalies. As well as the sensor data, documentation of the systems can also be stored on the platform. Modules for semantic information retrieval with context information should be able to provide answers to routine enquiries by the technicians. These also include identification of similar service cases in the archive through the use of the differential diagnosis method.
By the end of the duration of the project, a standardised platform, which should become increasingly established in the sector, will be implemented. On the basis of this, an ecosystem with Service-Meister modules, which can be monetised through user licences via the KROHNE platform, is to be created. In this way, KROHNE and inovex are covering a whole range of innovation fields that were considered within the scope of the innovation competition: predictive analytics, AI-supported ticket creation and allocation, service chatbots, AI-supported service reports, and AI-based report evaluations and feedback loops.

Technological set-up and agile approach

Through virtualisation and container technologies such as Docker and Kubernetes, as well as corresponding interfaces, inovex will make it possible for the existing platform to also operate innovative AI modules. A microservices architecture with standardised interfaces (REST, gRPC) allows flexible use of AI modules depending on the use case. Many years of experience from previous agile data science projects are going into the development of the AI applications. On the one hand, inovex makes use of established open-source frameworks (TensorFlow, PyTorch, Scikit-Learn, etc.) to develop the corresponding AI modules and applications, and on the other hand, KROHNE, inovex and the KROHNE customers will work together with agile methods. This technological-methodical set-up ensures that every AI module covers the greatest possible intended purpose and can be as effective as possible, as the AI applications based on them can be appropriately, simply and cost-efficiently implemented.

About the ‘Service-Meister’ project proposal

A fundamental shift in value creation from products to services is taking place in German industry. New business models that require the use and marketing of the company-internal ‘service knowledge’ of small and medium-sized German companies are in demand. However, the required ‘service knowledge’ of industrial systems goes beyond that of individual service technicians and even that of some companies. Along with a lack of specialist staff, small and medium-sized German companies are faced by the huge challenge of ensuring their advantage in the provision of services in the coming years.
To support those companies in these matters, Service-Meister will develop an AI-based service platform across systems, departments and companies for small and medium-sized German businesses. An important intermediate target is to make staff who have received less training capable of providing complex services, with the help of digital advisers such as AI-based service bots and smart services. As a second intermediate target, the provision of digitised service knowledge on a single platform should make cross-company scalability of service possible. This will create a service ecosystem to combat the lack of specialist staff in Germany and make small and medium-sized German companies competitive in the long term.

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inovex GmbH
Jörg Ruckelshauß
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