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Dr.-Ing. Rainer Lutze, Dipl.-Inform. LuSTCon Logo

Artificial Intelligence

Within the last years, the sector of artificial intelligence (AI) has gained crucial impulses by hardware and software advances. Today, with modern graphic processors very large artificial neuronal networks (ANNs) can be executed in real time. New algorithms for machine learning within such ANNs are capable to discover also structural features from rsp. within these data by their own (deep learning). The victory of the AlphaGO ANN against the GO world champion Lee Sedol in 2016 has proven this in an impressive way.

With the new techniques of data mining and deep learning, data can be processed in principle in their native format by an ANN. The very expensive, prior manual acquisition of data models and inference rules, as required for rule-based expert systems, can be omitted. This is a quantum leap in the economic viability of such AI systems. It is also a necessary prerequisite in order to process very large data sets (big data) in the age of digitization and the internet of things (IOT).

Humanoid robot thinking on the future of AI and his role in the society
Picture credits: © phonlamaiphoto /

We have decade-long experiences in the sector of artificial intelligence. These experiences enable us to design for our customers the effective applications of AI technologies in a purposeful and cost-efficient way. For technical systems, the application targets will be a reduction of costly downtimes by demand driven, predictive maintenance. In the healthcare area, the focus is on the avoidance of health hazards and/or very fast interventions just in case. For marketing purposes, the profiling of successful customers will be utilized for a tailored promotion of other customers and interested parties.

Technology and
Innovation Management (TIM)

Only seldom, commercially successful innovations are achieved incidently. In most cases, they will be the result of a comprehensive and careful selection, assessment and elaboration of ideas and research results. We support the systematic search for, planning and elaboration of innovations - based on approved innovation patterns like the St. Gallen catalogue of business model innovations - and ditting to the specific company situation within its life cycle (J.F. Moore, 1993).

Enterprise life cycle as defined by J.F.Moore 1993
Picture credits: © Dr.-Ing. Rainer Lutze Consulting

IT Due Diligence

In the scope of asset deals, corporate mergers and acquisitions, the analysis und assessment of the IT-system capabilities and performance as well as the suitability of the IT organization for executing its business processes will have a central importance. Beside conflicting company cultures, incompatible and non-integrable IT-systems are the main reason for failing corporate mergers and acquisitions.

Our longtime experience in corporate restructuring and optimal positioning of the companywide IT helps to delimit IT risks to a minimum. Analysis and rating of the company's current situation will be intertwined with technical / organizational planning and optimization of potential fusioned corporate szenarios.

Customer involvement as critical success factor
Picture credits: © Maksim Kabakou /