Digital and Social Sensing

Listen to customers across communication channels in real-time and analyze interactions using machine learning (ML) algorithms and artificial intelligence (AI). Identify context to initiate back-end processes and drive appropriate actions for meaningful responses and faster resolutions.

Features

• AI-driven Learning - Supervised ML models based on neural networks to determine intent, classification, and sentiments. Natural language processing and named entity recognition for extracting relevant information - Ready-to-use, language-agnostic ML models for different verticals
• Multi-channel Interactions - Anytime, anywhere engagement with customers in their preferred communication channels - Unified, single-stream interactions across all connected networks to enable monitoring of incoming messages
• Case Routing and Prioritization - Auto-routing of customer queries, complaints, etc. to relevant departments - Prioritizing cases based on urgency, customer requirements, agents’ skill sets, and workload
• Automated Response and Engagement - Delivering automatic, personalized, and contextual responses instantly - Tracking and reviewing historical customer interactions and events for a holistic view
• Monitoring, Reporting, and Insights - Comprehensive and customizable dashboards, graphical charts, and reports with active, on-demand, and predictive analysis - Auto-generated insights to enable real-time decision making and to improve customer experience
• Platform APIs - Out-of-the-box REST APIs for quick integration with on-premise, cloud, and hybrid-deployed systems
• Integration with existing IT systems and business applications for seamless information flow