Permission AI: A Secure Multi-Modal Architectural Framework for Intelligent Digital Assistance

P, Sivasakthi.

doi:https://doi.org/10.55041/ijsmt.v2i5.021

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PERMISSION AI: A SECURE MULTI-MODAL ARCHITECTURAL FRAMEWORK FOR INTELLIGENT DIGITAL ASSISTANCE

AUTHORS:

Sivasakthi. P

Mentor

Dr.T R NISHA DAYANA

Affiliation

Vels Institute of Science,Technology And Advanced Studies (VISTAS)

DOI: 10.55041/ijsmt.v2i5.021

CC BY 4.0 License:

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract

Modern conversational AI platforms face two critical challenges: the high latency of multi-modal inference and the inherent privacy risks of unmanaged data access. This paper presents Permission AI, a secure architectural framework that integrates permissionbased access control with highperformance vision analysis. By leveraging NVIDIA GPU acceleration for visioninstruct models (Llama 3.2 Vision) and a JWT-secured Node.js backend, the system provides a low-latency, private environment for intelligent digital assistance. Our implementation demonstrates that localizing permission logic and accelerating vision inference can reduce end-to-end response times while maintaining a robust security posture for sensitive user queries.

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This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.

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