Company Performance Metrics
- Chang Chien-Wen: Vice President
eLAND stands as a leading intelligent data company in Taiwan. Specializing in cutting-edge software technologies such as AI, semantic analysis, search engine, and business data analytics, our research and development focuses on integrating big data and AI with the ambition to become a world-class software technology innovator. Since our
establishment, eLAND has continued to invest in core technology development and has obtained over 60 international and domestic patents. eLAND focuses on two core product lines—Cloud Data Analytics and AI Search Solutions—supported by proprietary large-scale databases, self-developed models, and a complete product ecosystem.
【Cloud Data Analytics】 eLAND offers two core products : OpView and fynaview. OpView is the largest social listening platform in Taiwan, powered by multiple patented NLP and generative AI technologies, it enables enterprises to monitor public opinion and track market trends. In response to the growing demand for advanced AI-driven decision support, OpView AI Agent transforms complex public opinion analysis workflows into an intuitive and interactive tool. The system employs advanced AI semantic understanding to automatically identify user intent and apply appropriate models, integrating platform data to generate instant summaries and strategic recommendations that enable rapid access to key insights.
fynaview is a financial intelligence platform powered by advanced semantic analysis. The system features AI event classification to analyze market intelligence, and utilizes knowledge graphs to trace cross-enterprise risk contagion, facilitating precise risk management and strategic planning.
【AI Search Solutions】 This series includes the AI Search platform and AI Model. By integrating data extraction, semantic analysis, and eLAND’s proprietary LLM, these products support intelligent Q&A, task agents, and knowledge management. They empower enterprises to access information efficiently, enhance customer service and internal operational productivity, and support both on-premise and cloud deployment to accelerate the practical adoption of AI applications.