Cloistered Knowledge Capture and Retrieval: Offline LLMs and Vector Search for Enterprise

In an era of rapid technological advancements, Artificial Intelligence (AI) has proven to be an invaluable tool for enhancing various aspects of human life. This research paper delves into the potential impact of cutting-edge AI technologies on business by integrating them into a knowledge management system. The aim of this study is to explore how these innovations can contribute significantly to empowering businesses, facilitating their growth, bolstering their competitiveness in the marketplace, and provide resilience against staff mobility. This paper examines recent advancements in Generative Transformers, Vector Databases, and Large Language Models to support the development of a novel, secure system for the capture, storage, and retrieval of knowledge—purpose-built for business-focused knowledge management. It implements and evaluates a system that challenges a sanitized version of an actual business dataset consisting of 595 documents to a set of 40 actual business enquiries. The accuracy, trustworthiness and response time of the system is evaluated with a thorough review of its limitations and recommendations for future work.

Authors

Institutions

Publication Details

Published
2025-05-14
DOI
https://doi.org/10.1109/sist61657.2025.11139171
Primary Topic
Data Mining Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cloistered Knowledge Capture and Retrieval: Offline LLMs and Vector Search for Enterprise

Serengul Smith, Can Başķent, Clifford De Raffaele, Stephen J. Hall
Data Mining Algorithms and Applications
article

Cloistered Knowledge Capture and Retrieval: Offline LLMs and Vector Search for Enterprise

Serengul Smith, Can Başķent, Clifford De Raffaele, Stephen J. Hall
article en

Abstract

In an era of rapid technological advancements, Artificial Intelligence (AI) has proven to be an invaluable tool for enhancing various aspects of human life. This research paper delves into the potential impact of cutting-edge AI technologies on business by integrating them into a knowledge management system. The aim of this study is to explore how these innovations can contribute significantly to empowering businesses, facilitating their growth, bolstering their competitiveness in the marketplace, and provide resilience against staff mobility. This paper examines recent advancements in Generative Transformers, Vector Databases, and Large Language Models to support the development of a novel, secure system for the capture, storage, and retrieval of knowledge—purpose-built for business-focused knowledge management. It implements and evaluates a system that challenges a sanitized version of an actual business dataset consisting of 595 documents to a set of 40 actual business enquiries. The accuracy, trustworthiness and response time of the system is evaluated with a thorough review of its limitations and recommendations for future work.

Middlesex University London (GB)
Openalex Percentile: Top 66%
Data Mining Algorithms and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.