Background

A large manufacturing conglomerate with multiple facilities in Taiwan and overseas employs thousands of staff across its operations. Over years of operation, the organization had accumulated vast knowledge assets — including technical documents, standard operating procedures (SOPs), quality management records, and customer service cases. However, these resources were scattered across departmental file systems, email inboxes, and paper archives, creating severe knowledge silos.

New employees spent excessive time searching for the technical documents and operating procedures they needed, while the departure or retirement of senior staff often meant the permanent loss of valuable institutional knowledge. The organization urgently needed an intelligent knowledge management system capable of consolidating dispersed knowledge and providing employees with fast, convenient access.

Challenges Faced

• Hundreds of thousands of technical documents scattered across different systems and departments, with no unified search portal
• Traditional keyword search cannot understand query semantics, causing employees to frequently fail to find the documents they actually need
• Documents exist in diverse formats including PDF, Word, Excel, presentations, and scanned images, making unified processing difficult
• Cross-department knowledge sharing mechanisms are weak, with different departments repeatedly reinventing solutions to the same problems
• Tacit knowledge held by senior employees is difficult to transfer, and talent attrition leads to knowledge gaps
• Document access permissions must be enforced across departments in compliance with enterprise information security policies

Industry Solutions

The company deployed LargitData's RAGi enterprise AI engine — a Retrieval-Augmented Generation platform — to establish a company-wide AI-powered knowledge management system. Leveraging advanced RAG technology, RAGi enables employees to interact with the enterprise knowledge base through natural language queries.

Implementation Overview

• RAGi Enterprise AI Decision Platform: centrally import documents from all departments to establish an enterprise-grade AI knowledge base
• Natural Language Query Interface: employees can ask questions in everyday language, and AI automatically retrieves relevant documents and generates precise answers
• Multi-Format Document Processing: supports automatic parsing and indexing of PDF, Word, Excel, PowerPoint, images, and other document formats
• Access Control System: configure document access permissions by department and role to ensure information security
• Source Citation Annotation: every AI-generated answer is annotated with the source document and paragraph it references, ensuring full traceability

RAGi Enterprise AI Retrieval-Augmented Generation Engine →

Implementation Results

• Average time for employees to locate technical documents reduced from 30 minutes to 5 minutes, an 85% efficiency improvement
• Successfully imported over 200,000 cross-department documents, establishing the company's most comprehensive knowledge asset repository
• Over 3,000 AI queries per month, making the platform an indispensable tool for employees' daily work
• New employee training period shortened from 3 months to 2 months, accelerating talent development
• Cross-department knowledge sharing rates have improved significantly, with a marked reduction in redundant problem-solving
• Senior employees' professional expertise has been successfully digitized and preserved, reducing knowledge risk from talent attrition