– High accuracy, flexible introduction method heralds innovation in matching experts in research and industry
Intellisys (CEO Eunyoung Park), an AI-based business automation and data intelligence company, announced on the 10th that it has launched 'Xpert Search', an intelligent expert search solution that combines large-scale language models (LLM), augmented search generation (RAG), and customized recommendation technologies.
Expert Search is an advanced talent search solution that precisely matches the most appropriate experts for complex questions that include specialized terms and technical concepts in each field, such as industry, academia, and the public sector. In particular, unlike existing systems that rely on keyword-based searches or standardized history filtering, it applies next-generation RAG technology that comprehensively analyzes structured and unstructured data such as papers, research results, and news articles, providing high accuracy and reliability.
According to Lee Sang-goo, CTO of Intellisys and professor of computer engineering at Seoul National University, “While existing talent matching systems were limited to simple filtering centered on structured data, Expert Search combines semantic analysis and AI recommendation technology based on a three-dimensional understanding of researchers to produce differentiated results.”
Eunyoung Park, CEO of Intellisys, said, “Expert Search is not simply recommending famous people, but its core competitiveness is precisely presenting the most suitable expert for a specific question,” and added, “We are currently conducting a pilot operation targeting about 20 universities, and we are in discussions with 4-5 universities for formal introduction.” She added, “As the possibility of its use in various fields such as industry-academia cooperation, technology consulting, and public network construction is confirmed, actual demand is also rapidly increasing.”
Intellisys is solving complex problems faced by enterprises and institutions based on generative AI, augmented search generation (RAG), and multi-agent. We plan to dramatically improve the knowledge exploration capabilities of enterprises and institutions by connecting the right people to the right places through expert search while focusing on applying enterprise generative AI to solve real business problems.
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