Building Enterprise Q&A Systems A Practical Guide to Personalization and Privacy

Enterprise Question-Answering (Q&A) systems have emerged as critical components in modern business infrastructure, revolutionizing how organizations manage and utilize their information assets. These systems integrate sophisticated retrieval mechanisms with advanced language models while maintaining robust privacy frameworks. The implementation encompasses multiple architectural strategies, from large-scale model training to hybrid retrieval-augmented generation frameworks, each offering distinct advantages for enterprise deployments. Through the integration of domain-specific understanding pipelines and dual-index retrieval strategies, these systems achieve superior query comprehension and response accuracy. The Plan-Act framework facilitates effective coordination between retrieval mechanisms and language models, while comprehensive security measures ensure data protection through multi-layered access controls and isolation strategies. The incorporation of automated governance tools and continuous compliance monitoring establishes a foundation for secure, scalable enterprise Q&A deployments. These systems demonstrate remarkable effectiveness in handling diverse business domains, from IT support to HR queries, while maintaining stringent privacy standards and regulatory compliance.

Authors

Publication Details

Journal
International Journal on Science and Technology
Published
2025-04-02
DOI
https://doi.org/10.71097/ijsat.v16.i2.3072
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

Building Enterprise Q&A Systems A Practical Guide to Personalization and Privacy

Nitish Ratan Appanasamy -
International Journal on Science and Technology
Big Data and Business Intelligence
article

Building Enterprise Q&A Systems A Practical Guide to Personalization and Privacy

Nitish Ratan Appanasamy -
article en

Abstract

Enterprise Question-Answering (Q&A) systems have emerged as critical components in modern business infrastructure, revolutionizing how organizations manage and utilize their information assets. These systems integrate sophisticated retrieval mechanisms with advanced language models while maintaining robust privacy frameworks. The implementation encompasses multiple architectural strategies, from large-scale model training to hybrid retrieval-augmented generation frameworks, each offering distinct advantages for enterprise deployments. Through the integration of domain-specific understanding pipelines and dual-index retrieval strategies, these systems achieve superior query comprehension and response accuracy. The Plan-Act framework facilitates effective coordination between retrieval mechanisms and language models, while comprehensive security measures ensure data protection through multi-layered access controls and isolation strategies. The incorporation of automated governance tools and continuous compliance monitoring establishes a foundation for secure, scalable enterprise Q&A deployments. These systems demonstrate remarkable effectiveness in handling diverse business domains, from IT support to HR queries, while maintaining stringent privacy standards and regulatory compliance.

International Journal on Science and TechnologyVol. 16(2)
Openalex Percentile: Top 90%
Big Data and Business Intelligence
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