eLand Details Practical Playbook for Building Enterprise AI Agents

As generative AI becomes more widespread, turning the technology into real productivity has become a key challenge for businesses. Taiwanese semantic analysis and search technology provider eLand Information says successful AI Agent adoption depends on building proprietary knowledge bases and knowledge graphs. These tools can address the “hallucinations” common in large language models and are particularly important in finance and manufacturing, where decisions demand high precision.

In a July 2026 interview, eLand Information General Manager Li-Wei Yang shared practical strategies for building enterprise AI Agents. He said the company’s AI Search Platform has been successfully deployed to help insurers provide precise claims guidance and enable manufacturing engineers to use AI to interpret components and manuals. The platform can integrate tens of thousands of internal corporate documents and deliver precise answers within milliseconds, helping businesses turn AI into productivity.