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Five Challenges That Can Be Solved with Generative AI Enterprise Search

Introducing how local LLMs are utilized in various industries and the results companies are achieving, based on specific examples.

The document discusses "Five Challenges That Can Be Solved with Generative AI Enterprise Search." It introduces issues such as the enormous amount of time employees spend searching for information, which decreases operational efficiency, and the challenge of cross-system searches due to internal information being dispersed across multiple systems. Additionally, it explains the challenges faced when implementing local LLMs and their solutions. Please take a look. 【Contents】 ■ Introduction ■ Five Challenges That Can Be Solved with Generative AI Enterprise Search ■ For Those Who Want to Utilize Generative AI Enterprise Search While Protecting Confidential Information ■ Conclusion *For more details, please download the PDF or feel free to contact us.

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【Details of the Publication】 ■ Five Challenges Solved by Generative AI Enterprise Search - Wasted time in collecting vast amounts of information - Insufficient accuracy of search results - Difficulty in integrating dispersed information - Barriers to managing multilingual information - Concerns about information security and privacy *For more details, please download the PDF or feel free to contact us.

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Five Challenges That Can Be Solved with Generative AI Enterprise Search

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