Abstract :RemoteOps: AI-Powered Workflow Management Hub Is An Intelligent Web-based Platform Designed To Streamline And Automate Workflow Management Using Artificial Intelligence. The System Provides A Centralized Environment For Creating, Assigning, Tracking, And Managing Tasks And Workflows, Helping Organizations Improve Productivity And Operational Efficiency. AI-based Features Can Analyze Workflow Information, Prioritize Tasks, Identify Delays, And Provide Intelligent Recommendations To Support Faster Decision-making. The Application Uses Node.js For Backend Development And React For Building A Responsive And Interactive User Interface. Users Can Create Projects, Assign Tasks, Define Priorities And Deadlines, Monitor Workflow Progress, And Receive Status Updates Through A Centralized Dashboard. AI Capabilities Can Assist In Task Prioritization, Workflow Optimization, And Identifying Potential Bottlenecks Based On Available Project Data. The Proposed RemoteOps System Aims To Reduce Manual Workflow Management Efforts, Improve Team Coordination, Increase Task Visibility, And Support Efficient Remote Operations. By Combining Artificial Intelligence, Workflow Management, Node.js, And React, The Platform Provides A Scalable And User-friendly Solution For Organizations Seeking To Manage Distributed Teams And Business Processes Effectively. Keywords: Artificial Intelligence, Workflow Management, Remote Operations, Task Automation, Project Management, Node.js, React, Workflow Optimization, Task Prioritization, Bottleneck Detection. |
Published:22-8-2025 Issue:Vol. 25 No. 8 (2025) Page Nos:571 - 577 Section:Articles License:This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. How to CiteB. BHAWANA, RAYAGADA NEEHARIKA, YENUGUTALA HARIKA, TAMIRE VAMSI KRISHNA, VADAPALLI ANAND RAJU, THOTA PARAMESH, REMOTEOPS AI: INTELLIGENT WORKFLOW MANAGEMENT AND TASK AUTOMATION PLATFORM , 2025, International Journal of Engineering Sciences and Advanced Technology, 25(8), Page 571 - 577, ISSN No: 2250-3676. |