Case Study: Linde achieves faster multilingual knowledge retrieval with STX Next’s AI-powered RAG platform

Linde speeds knowledge retrieval in seconds with STX Next

Linde, a leading global industrial gases and engineering company, faced a significant challenge in efficiently accessing its vast and fragmented collection of internal technical and operational documents across multiple languages. To streamline this knowledge retrieval process and allow employees to get reliable answers quickly, Linde partnered with STX Next to build a custom AI-based knowledge-retrieval platform.

STX Next implemented a secure Retrieval-Augmented Generation (RAG) solution hosted on Microsoft Azure. This system provides employees with immediate, accurate, and source-cited answers in natural language, breaking down language barriers by supporting multilingual queries. The results for Linde included significantly faster search times, broader global information access, and improved decision-making, all while ensuring data sovereignty and building a scalable, sustainable knowledge infrastructure.

Linde