With the web and cloud-enabled PSIqualicision AI, business processes can be efficiently planned and optimized using targeted evaluation of, for example, profitability and sustainability key performance indicators (KPIs).
Due to its universal nature, the PSIqualicision AI can be transferred to and used in various applications (monitoring, decision support, predictive maintenance, optimization, data analysis) and industries, including the automotive industry, metal industry, energy trading, public transport and energy suppliers.
Benefits at a Glance
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Optimized decision making Optimization and decision-making for selection and classification tasks.
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Web and cloud-enabled Installation and access via PSI Marketplace and PSI cloud at the touch of a button.
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Independency Process data analyses and forecasts across all contexts and industries.
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Integrated Didactics Comprehensible application possibilities and playful interaction through integrated dialog guidance and exercise examples (Integrated Didactics).
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Explainable AI results Explainable relationships amongst other things of profitability and sustainability KPIs.
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User acceptance Increasing user acceptance due to comprehensible AI decisions.
Features
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Qualitative Labeling Qualitative Labelling as part of the Qualicision AI framework optimizes raw business process data for machine learning applications by qualitatively assessing measurable data directly from business processes in the context of KPIs (Key Performance Indicators) and analyzing relationships based on this. In this way, an algorithmic bridge is automatically created between the unprocessed raw business process data and artificial intelligence (AI) methods, which significantly simplifies the time-consuming process of manual data analysis for labeling data.
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Qualicision Impact Matrix The input for the software essentially consists of two main components: Firstly, data streams of the business process to be analyzed are recorded and automatically converted into time series with the help of time stamps. Secondly, key performance indicators (KPIs) and their value ranges, which are to be used to analyze the business process in question, are agreed with the process owner. In addition, the value ranges of the KPIs are divided into preferred and non-preferred value ranges. Green labels stand for preferred or good signal areas, while red labels connote areas that are critical, i.e. not desirable from a process perspective.
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Visualization With the 3D force graph, you can visualize your decision support and optimization criteria as well as their preference settings transparently and comprehensibly according to their mutual impulse-giving compatibility (green) and conflict potential (red). It is also possible to create a permanent force graph. Each sphere represents a criterion here, and depending on the selection mode, connections are drawn between the spheres, which depict the interdependencies in color.
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Integrated Didactics With the integrated dialog guidance and provided exercise examples (Integrated Didactics), the user is able to understand the possible applications of the PSIqualicision AI functionalities and is presented in an almost playful way.
Typical Users
As an IT manager
With a deep technical understanding, IT managers have a keen sense for system stability and performance as well as for the configurability and integration capability of decision support and optimization systems. Reliability is one of the key quality characteristics for IT managers when it comes to software solutions.
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Web and cloud-enabled
Installation and access via PSI Marketplace and PSI cloud at the touch of a button.
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Optimized decision making
Optimization and decision-making for selection and classification tasks.
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Explainable AI results
Explainable relationships amongst other things of profitability and sustainability KPIs.
