Fewer Questions, More Answers
AI-powered chatbot for easy access to complex data

Too many repeated inquiries?
Uster's textile expertise and service knowledge are highly complex and essential for informed decisions in the daily operations of textile companies. However, this knowledge was difficult for customers to access and heavily reliant on direct inquiries to experts.
This resulted in high support efforts, recurring inquiries, and limited scalability of knowledge. Uster's goal was therefore to make their extensive domain knowledge efficiently accessible, empowering customers to make informed decisions independently while sustainably reducing the burden on support.
Client:
Uster Technologies
Textile Industry
Services:
Software Engineering
UI Design
UX Design
Centigrade implemented an AI assistant that makes complex domain knowledge accessible and significantly relieves the support team.
From Complex Knowledge to Scalable Self-Service
With the introduction of the AI assistant, Uster was able to significantly simplify and scale access to complex textile expertise.
This significantly relieves the technical service teams. The target: reduce questions to textile experts by up to 50%.
From Complex Knowledge to Scalable Self-Service
With the introduction of the AI assistant, Uster was able to significantly simplify and scale access to complex textile expertise.
This significantly relieves the technical service teams. The target: reduce questions to textile experts by up to 50%.
Structured Knowledge at Your Fingertips
With LeanScope AI as a central data and knowledge platform, we laid the groundwork for the entire service. The platform manages Uster's textile expertise in a structured way and reliably provides it to the chatbot, scalably and without manual effort for every query.

From ITMA to the Future
The Uster Chatbot officially launched at ITMA in Singapore in October 2025 – one of the most important trade fairs in the global textile industry. Since then, Uster customers have been using the chatbot almost daily.
With this foundation, the possibilities are far from exhausted. The goal is not to stop at answering questions, but to support users exactly where they need it: from context-sensitive explanations and assistance to new forms of interaction within the application.

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