diff --git a/qdrant-landing/content/blog/case-study-deutsche-telekom.md b/qdrant-landing/content/blog/case-study-deutsche-telekom.md index 9a4c2a02c..607d2bd7b 100644 --- a/qdrant-landing/content/blog/case-study-deutsche-telekom.md +++ b/qdrant-landing/content/blog/case-study-deutsche-telekom.md @@ -39,7 +39,7 @@ This insight led to the formation of [LMOS as an open-source Eclipse Foundation ### Why Deutsche Telekom Had to Rethink Its AI Stack from the Ground Up -The team started its journey in June 2023 with a small-scale Generative AI initiative, focusing on chatbots with customized AI models. Initially, they used LangChain and a major vector database provider for vector search and retrieval , alongside a custom Dense Passage Retrieval (DPR) model fine-tuned for German language use cases. +The team started its journey in June 2023 with a small-scale Generative AI initiative, focusing on chatbots with customized AI models. Initially, they used LangChain and a major vector database provider for vector search and retrieval, alongside a custom Dense Passage Retrieval (DPR) model fine-tuned for German language use cases. However, as they scaled, these issues quickly emerged: