How Kakao Built an AI-Powered Internal Service Desk with Qdrant

Kakao, a leading South Korean technology company, developed an AI-powered internal service desk called Service Desk Agent to streamline employee access to internal systems, APIs, and operational procedures, leveraging Qdrant as its primary vector store. The system is built as a Retrieval-Augmented Generation (RAG) platform, integrating semantic and keyword searches to handle complex queries across diverse data types, including technical documentation and historical inquiry data. Qdrant was chosen for its hybrid search capabilities, combining dense and sparse vectors through Reciprocal Rank Fusion, and for its operational fit with Kakao's infrastructure, supporting deployment on Kubernetes and allowing self-hosting. The system's architecture includes automated indexing and metadata filtering, enhancing search quality and response time, which has significantly reduced the support staff's workload and improved employee satisfaction by providing faster access to internal knowledge. As the dataset grows to approximately 1 million vectors, Kakao plans to expand the system's capabilities with features like multimodal search and deeper GraphRAG integration, positioning Qdrant as a crucial component for scalable, AI-driven knowledge access within the company.