This documentation outlines the capabilities and operational logic of an Agentic AI-powered IT Support Agent designed to process and resolve end user requests submitted through AIW chatbot. The agent emulates human support behavior by dynamically managing multiple scenarios and branching pathways to ensure each IT support request is addressed efficiently and accurately.
Key features include:
Intelligent evaluation of service request catalogs to determine the best channel for data collection (chatbot or application link) based on catalog complexity.
Adaptive, context-aware conversations that collect information, validate inputs, and handle errors gracefully.
Support for a wide range of IT support scenarios, including access requests, asset-related issues, and approval workflows.
Real-time user identity verification, permissions checking, and respectful interactions throughout the support process.
System resource awareness to maintain performance under varying loads or constraints.
By following these principles, the Agentic AI support agent ensures high coverage, timely resolution, and a seamless user experience comparable to skilled human support staff, while maintaining strict security and auditability standards.
1. Request Ingestion
Agent receives requests via chatbot.
Natural language processing is used to determine user intent and scenario type.
2. Scenario Evaluation
The agent evaluates the scenario, checks for applicable catalogs, and identifies required user/data inputs.
For simple scenarios, the agent collects data conversationally; for complex ones, it redirects users to appropriate forms or workflows.
3. Parallel & Non-Linear Processing
Agent can handle multiple requests concurrently and manage branching conversation flows.
Supports interruptions and returns to prior context as needed.
4. User Interaction Model
Follows a step-by-step dialogue, prompting for additional information when necessary.
Validates user responses in real time and requests corrections or clarifications.
5. Security & Compliance
Enforces user identity verification and stringent permission checks before proceeding.
Sensitive actions or data accesses are gated according to company policy.
6. Adaptive Behavior
System factors (CPU/GPU load, API limits, throttling) are monitored and agent adapts flow accordingly.
Example: Queuing, Informing user of delays.
If a process cannot continue, the agent explains the situation and escalates, or guides the user to an alternate channel.
7. Closure and Feedback
Upon resolution or completion, the agent confirms the action, provides links or confirmations, and optionally collects user satisfaction feedback.