An AI-powered helpdesk to manage thousands of public inquiries efficiently, improving response times and service quality
An intelligent helpdesk platform designed to manage thousands of public inquiries efficiently, improving response times, service quality, and operational transparency.
Built on the secure, scalable foundation of Microsoft Azure, leveraging Azure Analytics, App Modernization, and AI capabilities.
a. Smart Categorization Integrated with Azure AI services to automatically classify tickets by topic, urgency, and department.
b. Multi-Channel Capture Azure App Service, API Management, and Logic Apps enable integration with email, WhatsApp, social media, web forms, and internal systems — consolidating all inquiries into a unified dashboard.
c. Massive Load Handling Azure Kubernetes Service (AKS) and scalable cloud infrastructure automatically adjust resources during peak volumes without performance degradation.
d. Case History View Azure SQL Database or Azure Cosmos DB securely stores interaction history for complete case visibility and faster resolution.
a. Suggested Responses Azure OpenAI Service generates contextual response recommendations based on previous tickets and knowledge base content.
b. Knowledge Base Search Azure AI Search enables fast, intelligent retrieval of SOPs, regulations, and FAQs.
c. Keyword & Sentiment Detection Azure AI Language performs sentiment analysis and key phrase extraction to identify urgent or sensitive cases.
d. Escalation Alerts Azure Functions and Logic Apps trigger automated workflows and real-time alerts for high-risk or SLA-breaching tickets.
a. Real-Time Dashboard Power BI connected to Azure data services provides live monitoring of ticket status, SLA compliance, and team performance.
b. Volume Analysis Azure Synapse Analytics and Azure Data Lake analyze historical data to identify trends and forecast peak periods.
c. Custom Reports Dynamic reporting tailored for management, audit, and regulatory requirements using Power BI.
d. Category Insights Advanced analytics and machine learning models uncover recurring issues and improvement opportunities.