Navigating Enterprise Constraints: Building a Hybrid Multi-Modal Mobile Intelligent App

Publication Date

1-1-2024

Document Type

Conference Proceeding

Publication Title

Proceedings - 2024 IEEE Intelligent Mobile Computing, MobileCloud 2024

DOI

10.1109/MobileCloud62079.2024.00008

First Page

1

Last Page

7

Abstract

The promise of artificial intelligence (AI) has prompted various industries to explore how it can enhance their businesses and improve customer experiences. However, the practical deployment of AI services faces challenges due to internal infrastructure limitations, data policies, and network restrictions. In this paper, we present our current project - a solution designed to empower mental health centers with AI tools while adhering to stringent data and network constraints. Our approach involves deploying AI services and data within internal enterprise networks, while the customer-facing mobile app resides in the public cloud. We introduce a custom AI agent system that monitors requests from the public cloud, enforces data access policies, schedules GPU computing resources, and performs model inference. All computations and raw data storage remain confined within the enterprise network. Additionally, we develop a comprehensive multi-modal AI services app, encompassing semantic search, data indexing, document and summarization, question-answering, and translation services for multilingual users. Administrative users have the ability to correct AI-generated data and contribute to continuous model refinement. Our solution serves as a blueprint for enterprises facing similar restrictions.

Funding Number

2148353

Funding Sponsor

National Science Foundation

Keywords

AI, Healthcare, hybrid cloud, mobile AI services, private deployment

Department

Computer Engineering

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