How GoodData turbocharged AI analytics with Qdrant

GoodData has transformed its analytics platform into an AI-powered solution by incorporating Qdrant's scalable vector database to overcome the limitations of traditional BI tools and large language models. Initially, GoodData faced challenges in scaling its prototype that leveraged OpenAI due to high compute costs and slow response times when attempting to load its entire semantic model into AI contexts. To address these issues, GoodData adopted a Retrieval-Augmented Generation strategy with Qdrant, which provided high performance and real-time embedding updates necessary for multilingual semantic layers. This transition enabled GoodData to deliver quick, intelligent responses and insights to its over 140,000 end customers, enhancing the platform's capability to provide real-time decision-making and advanced AI applications. Additionally, Qdrant's architecture supports GoodData's ambitions for advanced AI growth, including document-based semantic search and AI-driven search capabilities in a Kubernetes environment, marking a significant evolution in GoodData's offerings from static dashboards to dynamic, AI-driven analytics solutions.

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