RAG-Stiftung is a foundation based in Essen, Germany, established in 2007 to facilitate the transition away from subsidized coal mining in a socially responsible manner. Its primary role is to finance the perpetual mine management obligations of the RAG Corporation following the cessation of coal mining operations at the end of 2018. In addition to its financial responsibilities, RAG-Stiftung supports educational, scientific, and cultural projects in the Ruhr and Saar mining regions, specifically those related to Germany's coal-mining industry. The foundation's assets are managed by an executive team dedicated to ensuring the effective allocation of resources to achieve its objectives.
Eduneon is developing a digital platform to help schools and municipalities plan and manage digital educational change in a systematic and ongoing manner. It uses software solutions to deliver sustainable and pedagogically meaningful media education.
talpasolutions
Series B in 2023
talpasolutions a predictive SaaS analytics provider for the mining industry that helps companies optimize machine performance, reduce breakdowns, and improve safety by making data more understandable. talpasolutions makes it possible for operators and machine manufacturers in heavy industry to use machine data that would have otherwise been lost. talpasolutions concentrates on building visualization and analysis applications for the industrial internet. In the first step, large amounts of data from the machines are recorded. Comprehendable visualizations allow for different stakeholders to understand relationships based on sensor data and contextual data and to react to critical information, which would otherwise have been buried in the data transfer. In the second step the newest predictive models are applied to eliminate events such as errors and the breakdown of machines critical to the process. This increases not only the availability but also the workload of the machines. talpasolutions has built a network out of industry partners to develop solutions that stretch across various sectors and unify industry experience, data science, and workflow connectivity. Using predictive instructions our platform recognizes problems before they occur and supports users with workflow-based processes. Our applications make it possible to collect performance data from machines in order to recommend optimal fleet combinations for respective scenarios to customers. This leads to more operating hours, higher efficiency, and an improved lifetime value of the machines.
talpasolutions
Series A in 2020
talpasolutions a predictive SaaS analytics provider for the mining industry that helps companies optimize machine performance, reduce breakdowns, and improve safety by making data more understandable. talpasolutions makes it possible for operators and machine manufacturers in heavy industry to use machine data that would have otherwise been lost. talpasolutions concentrates on building visualization and analysis applications for the industrial internet. In the first step, large amounts of data from the machines are recorded. Comprehendable visualizations allow for different stakeholders to understand relationships based on sensor data and contextual data and to react to critical information, which would otherwise have been buried in the data transfer. In the second step the newest predictive models are applied to eliminate events such as errors and the breakdown of machines critical to the process. This increases not only the availability but also the workload of the machines. talpasolutions has built a network out of industry partners to develop solutions that stretch across various sectors and unify industry experience, data science, and workflow connectivity. Using predictive instructions our platform recognizes problems before they occur and supports users with workflow-based processes. Our applications make it possible to collect performance data from machines in order to recommend optimal fleet combinations for respective scenarios to customers. This leads to more operating hours, higher efficiency, and an improved lifetime value of the machines.
Signa Retail
Corporate Round in 2019
SIGNA Retail is the umbrella concern for a number of German companies established independently of one another, including The KaDeWe Group, Karstadt sports and Karstadt Warenhaus, outfitter.de, and the Joint Venture with EATALY. All five companies are led by experienced experts in the sector. With more than 20,000 personnel at more than 100 locations, SIGNA Retail achieves with these five companies a turnover of some EUR 3 thousand million per year.
Factory Berlin
Venture Round in 2018
Factory Berlin is an innovative ecosystem located in Berlin, comprising over 3,000 members from more than 70 countries. Established in 2012, it serves as a hub for tech innovators, creatives, and corporate professionals, fostering collaboration and networking within its diverse community. Factory Berlin offers a range of resources, including office space, startup labs, and various events and programs designed to facilitate connections and support early-stage startups. The organization partners with notable entities such as Riverside Studios Berlin, Sonar+D, Google for Startups, CODE University, and Hackerbay to enhance its offerings. By empowering creators and entrepreneurs, Factory Berlin aims to contribute positively to the local and global community.
Kitov
Series A in 2018
Kitov develops a platform for automated visual inspection based on artificial intelligence. It leverages visions of computers and capabilities of artificial intelligence that include deep learning, advanced robotics, and big data analytics, enabling industrial manufacturers to reduce manufacturing costs, eliminate inefficiencies and improve quality without the need for any programming expertise or expertise on automation.
RÖDER Group
Acquisition in 2014
Röder AG is a global provider of temporary zonal solutions. The company develops, manufactures, rents and sells tents and tent systems of all kinds, shape and size for events, large events and any kind of limited space requirement.
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