Efficient Ticket AI Assist for
Unparalleled Employee Experience
Increase employee engagement and boost productivity
Ticket AI Assist automatically classifies, routes, and resolves tickets across multiple domains such as IT, HR, Facilities, Finance, and Legal in order to provide faster agent resolutions while also providing auto-resolution capabilities via self-service, thereby increasing case deflection.
It integrates with all leading ticketing systems such as ServiceNow, Atlassian Jira, and BMC to provide AI-powered recommendations based on knowledge articles, similar tickets and cases, and next-best actions.
Boost Agent Efficiency
Reduce agent effort by efficiently routing tickets and auto-populating fields for faster agent response
Improve ESAT and Productivity
Reduce Mean-Time-to-Resolution (MTTR) by deflecting routine and repetitive requests
Reduce Support Costs
Provide significant cost savings by automating routine and repetitive requests, while also improving user experience
Auto-Triage and Prediction
Classify and route tickets to the right support agent based on category, sub-category, case type, root cause and urgency
Recommended Resolutions
Provide suggestions based on similar tickets and cases, past ticket history, knowledge articles, resolution notes, and next best actions
Auto-Resolve Tickets
Resolve employee requests across multiple channels without any human intervention for increased efficiency
Customizable UI Widget
Access information easily with fully embedded and customizable UI widget within ticketing systems such as ServiceNow, BMC, Atlassian Jira and more
AI Workflow Execution
Create guided AI workflows to automate classification, routing and subsequent resolution of tickets to reduce resolution times
Real-Time Reinforcement Learning
Improve recommendations and prediction accuracy by utilizing the AI to learn from past tickets, historical conversations, knowledge base articles, and agent notes
Agent Coaching
Provide agents with real time feedback based on similar tickets resolved by other agents and suggestions on next best actions
