Idea
Agentic AI platform that proactively supports contact center agents in real time to improve efficiency and customer satisfaction
Research Paper
Core Innovation
This paper presents Agentic AI as a goal-driven, autonomous system that proactively supports agents by dynamically adapting to conversation context and triggering modular workflows. Unlike prior reactive or rule-based AI tools, Minerva CQ maintains evolving context and integrates multiple real-time capabilities to reduce agent cognitive load and improve customer experience.
Market Size (TAM)
$20–50B TAM for AI-powered customer experience platforms; $2–10B SAM from contact centers and enterprise support teams. Driven by increasing demand for automation and improved CX metrics.
Potential Customers & Pain Points
- Contact Centers Struggling with High Average Handling Time
- Customer Support Teams Facing Low First-Call Resolution
- Businesses Experiencing Poor Customer Satisfaction
- Enterprises Needing Real-Time Agent Assistance
- Companies Using Fragmented Support Systems
Business Model
SaaS subscription model targeting contact centers and enterprises with tiered pricing based on usage and features
Competitive Landscape
- Genesys
- NICE inContact
- Five9
Implementation Challenges
- Integration with legacy contact center systems
- Real-time processing scalability
- Agent adoption and trust in AI assistance
Validation Strategy
- Deploy pilot programs with select contact centers to measure AHT and CSAT improvements
- Collect agent feedback to refine workflows and AI accuracy
- Scale deployments across multiple industries to validate generalizability
Research Paper Overview
Redefining CX with Agentic AI: Minerva CQ Case Study
Summary
This paper introduces Minerva CQ, an Agentic AI system deployed in voice-based customer support that proactively assists agents by identifying customer intent, triggering workflows, maintaining context, and adapting dynamically to conversation state. It integrates real-time transcription, intent and sentiment detection, entity recognition, contextual retrieval, dynamic profiling, and partial summaries to reduce cognitive load and improve agent efficiency and customer experience. Deployed in live production, Minerva CQ demonstrates measurable improvements in average handling time, first-call resolution, and customer satisfaction.