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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM52986

DocuSense AI: Document AI conversational platform using GenAI.

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM52986

Volume:

9 |

10 |

Oct 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM52986

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

JM

Jyoti Madake

KR

Kritika Raina

AK

Akanksha Kamble

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Abstract

In modern academic, legal, and business settings, users frequently encounter the problem of reading extensive documents in PDF format. This problem is resolved by DocuSense AI, which powers a sophisticated web application with Generative AI, allowing users to engage with their documents using natural language queries. Built with Python, Lang Chain, and Llama 3.3, the application transforms static documents into interactive and intelligent dialogues. The system generates vector embeddings of the PDFs for quick querying, while the frontend interface is user-friendly and consists of HTML, CSS, and JavaScript. PostgreSQL is employed for secure username and password registration. DocuSense AI is tailored for students, scholars, and working professionals to enhance their comprehension and productivity. Literature reviews support the implementation of Generative AI in conjunction with semantic search and layout-aware models in the analysis of documents centred around human users. This solution changes the way documents are engaged with—making the process quicker, smarter, and more efficient.

KEYWORDS

Generative AI Llama 3.3 Lang Chain PDF Querying Natural Language Processing Document Summarization AI Chatbot Document Interaction.

Cite This Article

Jyoti Madake, Kritika Raina, Akanksha Kamble, "DocuSense AI: Document AI conversational platform using GenAI.," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 10, Oct 2025. https://doi.org/10.55041/IJSREM52986

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Publication Date

11/9/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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0

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4

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5

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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