An LLM-Powered Agentic Orchestration System for Automated Cross-Tool Ticket Management in Enterprise Environments
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Updated time:2026-07-22 16:08:59 Views:16
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Abstract
Mid-to-large enterprises often struggle with fragmented workflows spread across tools like Slack and Jira leading to delays, miscommunication, and rising operational costs. With the average ticket resolution time exceeding four hours and requiring multiple human touchpoints, the need for a smarter approach is clear. The Enterprise Context Engine (ECE) was built to address exactly that. It is an AI-powered system that brings together a multi-agent architecture including a Triage Specialist, Problem Solver, and Workflow Manager to automatically classify, route, and resolve incoming tickets without constant human intervention. When the AI is unable to resolve an issue after three attempts, it escalates seamlessly to a human team, ensuring nothing falls through the cracks. What sets ECE apart is its emphasis on empathetic, proactive communication keeping users informed and supported throughout the process. The system targets a measurable outcome: reducing average resolution time by more than 40%. By bridging the gap between rigid RPA tools and conversational AI, ECE delivers a scalable, enterprise-ready solution for managing complex, cross-tool business processes.
Keywords
AI Agents, Multiple Agent System, Large Language Models, Retrieval-Augmented Generation.
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