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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM54902

Noteflow AI

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM54902

Volume:

9 |

12 |

Dec 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM54902

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

KKE

Kannammal K E1

BKMS

Bharath Kumar M S2

DDG

Dharani Daran G3

KKS

Kavin Krishna S4

KS

Kamali S5

MA

Maajida A6

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Abstract

NoteFlow AI is an intelligent note management and study companion application designed to simplify learning through automated organization and AI-powered assistance. The platform enables students to manage diverse academic materials— including documents, presentations, PDFs, and multimedia content like YouTube links—within a unified digital library. Built using modern frameworks and integrated with powerful AI models such as Gemini and Vertex AI, NoteFlow AI intelligently classifies study files into subjectbased folders, eliminating the need for manual sorting. Beyond organization, it enhances revision efficiency by generating concise summaries, short notes, and multiple-choice questions (MCQs) directly from user materials. A contextual chat interface allows users to ask questions and receive accurate, document-based responses using Retrieval-Augmented Generation (RAG) techniques. Prioritizing privacy and performance, NoteFlow AI processes data securely while offering a seamless and interactive learning experience. Altogether, it transforms unstructured study content into a personalized, accessible, and intelligent learning ecosystem.

KEYWORDS

AI study assistant intelligent note management automated organization document summarization MCQ generation contextual Q&A Gemini integration RAG model privacy-focused learning personalized study app.

Cite This Article

Kannammal K E1, Bharath Kumar M S2, Dharani Daran G3, Kavin Krishna S4, Kamali S5, Maajida A6, "Noteflow AI," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 12, Dec 2025. https://doi.org/10.55041/IJSREM54902

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Publication Date

6/11/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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Review Report (Confidential)
Copyright Form (Office)

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Article Views

0

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3

Total downloads since publication

Geographic Reach

5

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This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.

Conflict of Interest

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

Funding Information

No funding information available for this research.

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