Projects

A central focus of the AI Progress Center is direct cooperation with industrial companies: Feasibility studies (Quick Checks) and projects to develop initial prototypes (Exploring Projects) of AI applications. In addition, consortium projects and innovation networks are aimed at cross-company exchange.

High speed picking

The analysis of the patient journey at Klinikum Stuttgart identifies AI applications to optimize care, increase employee satisfaction and improve economic and ecological criteria.

Information extraction from medical publications

It was evaluated how the preparation of marketing authorization dossiers (core dossiers) can be supported by the extraction of information from medical studies.

Instant calculation of CNC components

Algorithms learn from existing production data and CAD geometries, estimate component complexity in real time, improve cost transparency, automate costing and relieve teams of manual assessments and time-consuming customer communication on a day-to-day basis.

Intuitive label editor for AI applications

The AI Progress Center's intuitive label editor optimizes the labeling process through structured workflows and automation features, increasing efficiency and ease of use.

AI-supported sales forecast

An AI-supported sales forecast analyzes historical sales data and external factors to predict future sales figures more accurately and enable data-based decisions.

AI anomaly detection with limited data sets

Research on AI anomaly detection with limited data sets aims to develop and test efficient methods for identifying anomalies in various industries despite data scarcity.

Jewelry image AI-based image recognition

AI-based valuation of returns when renting out valuables

In the sharing economy, efficient returns pose a major challenge. This can be largely automated through the use of AI.

AI-based appointment optimization by predicting appointment bookings, no-shows and cancellations

An AI prototype uses traffic light logic to suggest the preferred time slots for scheduling appointment requests in order to achieve the most efficient capacity utilization possible. This is based on past appointment data and takes into account no-shows and appointment cancellations.

AI modules for industrial software solutions

AI building blocks for industrial software solutions AI Explorer Initial situation EVO develops software for the manufacturing industry with a focus on SMEs and mid-sized companies. EVO's software spectrum includes the building blocks for the end-to-end digitalization of the...

AI bending tool selection

Creation of a labeled data set for the regression of quality parameters with a neural network. AI-supported tool selection and automated machine parameterization enable efficient, low-disruption production and shorter delivery times.