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Strategic partnership for AutoStore AI robotics

Hörmann Intralogistics is expanding its AutoStore portfolio and increasing the efficiency of its intralogistics projects through the targeted use of AI-based robotics solutions. The system integrator is working with Sereact to take automation in AutoStore systems to the next level with picking robots. Customers will benefit from higher process speed, more flexibility and even more efficient warehouse logistics.

"Our customers increasingly expect more powerful and easy-to-integrate automation solutions. With Sereact's AI technology, we can meet precisely these requirements and offer companies new opportunities for more efficient warehousing and picking processes," explains Tom Walther, Head of Robotic Solutions at Hörmann Intralogistics.

Sereact's solutions give AutoStore systems more intelligence and autonomy. By using zero-shot learning, picking robots can recognize and grasp new objects without prior programming or data input. Incoming goods, picking and returns processes are thus fully automated. The high flexibility and simple implementation of the software enables seamless integration into existing warehouse management and control systems such as the "HÖRMANN intra Logistics System" (HiLIS).

"Sereact's technology impressed us with its high flexibility and seamless integration into existing systems," says Walther. "This increase in efficiency is what makes the solution so valuable to us."

In addition to optimized process reliability, the integration of smart robotics reduces error rates and increases productivity. Companies can use automation to cushion personnel requirements in growth phases and use existing resources more efficiently.

Sereact Lens creates transparency in inventory management

For Sereact, the partnership also represents a decisive step in the further development of warehouse automation. "With Hörmann Intralogistics, we have a strong partner at our side who shares our vision of fully automated logistics," says Ralf Gulde, CEO of Sereact. "Together, we are bringing AI-supported robotics to where it creates real added value - in highly automated systems such as AutoStore, which benefit from intelligent picking and precise inventory control."

In addition to optimizing pick-and-place processes, Hörmann also relies on Sereact Lens, an AI-supported solution for inventory and quality control. The platform enables real-time monitoring of stock levels and automatically detects faulty or incorrectly positioned items. This prevents process disruptions and significantly increases transparency within the warehouse. The combination of intelligent robotics and automated inventory control takes AutoStore integration to a new level.

A milestone for automation

"We see enormous potential for AI-based robotics in warehouse automation and, in Sereact, we have a partner whose technology complements us perfectly," emphasizes Walther. Sereact is regarded as a technology leader in AI robotics with a large number of well-known references. The first joint projects are already demonstrating the success of the partnership. Further customer solutions are being planned.

"This cooperation shows that AI in logistics is no longer a vision of the future, but is already creating tangible competitive advantages today," adds Gulde. "By joining forces, we are making automation even more powerful - more efficient, more flexible and more economical than ever before."

About Sereact

Embodied AI for robotics: Sereact was founded by Ralf Gulde (CEO) and Marc Tuscher (CTO). The Stuttgart-based total solution provider develops AI-supported robotics solutions that are used in various industries and application areas by leading customers in Europe and the USA. The AI software gives robots visual and motor skills, enabling them to perceive their environment and develop intelligent strategies to perform a variety of physical tasks. From the precise handling of individual objects to the management of complex logistics and manufacturing processes, the systems analyze and solve unknown situations in real time. This enables the detection of anomalies, the optimization of processes and the setting of new standards in flexibility and efficiency for autonomous systems.