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I design AI-powered agent experiences for Agent AI by Kore.ai, including the agent widget, coaching playbooks, smart responses, and performance dashboards. I work closely with product, engineering, and AI teams to turn complex AI capabilities into intuitive, scalable tools that improve agent efficiency and customer interactions.
Role:
UI Designer
Industry:
Conversational AI platforms
Duration:
Ongoing
Challenges
Designing for real-time pressure: Agents work fast during live conversations, so interfaces must be instantly clear, non-distracting, and actionable.
Balancing AI power with simplicity: Turning complex AI outputs (LLMs, sentiment, recommendations) into UI that feels helpful—not overwhelming or confusing.
Trust & explainability: Helping agents understand why the AI is suggesting something, so they trust and actually use it.
Measuring UX impact: Tying design decisions to measurable outcomes like handle time, agent efficiency, and CSAT.
Adoption & behavior change: Encouraging agents and managers to rely on AI tools without disrupting existing workflows.
My Approach
Discovery Phase
User-first research: Understand agent workflows, pain points, and real-time needs through observation and interviews.
Competitive Analysis: Studied competitor websites and best practices in music band websites to identify key features and design elements.
Problem framing: Define key challenges like cognitive overload, AI trust, and workflow integration.
Design and Development
Context-aware UX: Design interfaces that prioritize critical information and reduce distractions during live conversations.
Progressive disclosure: Surface AI suggestions gradually, only when relevant.
Human-in-the-loop design: Ensure agents retain control over AI recommendations.
Explainable AI UX: Provide clear context and cues to help agents understand AI suggestions.
Modular & scalable components: Create reusable, customizable UI elements for enterprise clients.
Cross-functional collaboration: Work closely with product managers, engineers, and AI teams to balance design intent with technical feasibility.
Testing and Iteration
Userbility Testing : Validate design decisions with agents and stakeholders.
Iterative refinement: Continuously improve features based on feedback and data.
Performance measurement: Track metrics like efficiency, adoption, and user satisfaction to guide design improvements.
Results
As the designer for Agent AI at Kore.ai, my work has helped shape a real‑time AI assistant that drives measurable improvements in agent productivity, customer satisfaction, and operational efficiency for large enterprises globally; today, organizations such as eBay, Florida blu, Met Life, Citibank, Axis Bank, and many other Fortune 2000 companies leverage Kore.ai’s conversational AI technologies to enhance service delivery and support workflows, demonstrating how intuitive AI‑assisted design can transform contact center experiences and agent performance.
Future Plans
Advanced AI Capabilities: Integrate more sophisticated generative AI and LLM-driven insights to provide agents with deeper context, predictive recommendations, and automated summarizations.
Community Building: Expand fan engagement through live streaming events, virtual meet-ups, and enhanced social media integration.
Conclusion
I have contributed to creating an AI-powered assistant that transforms the way contact center agents work, making customer interactions faster, more accurate, and more satisfying. By designing intuitive interfaces, coaching tools, smart responses, and performance dashboards, I have helped enterprises like Axis Bank, eBay, AMD, and Boardwalk REIT improve efficiency and agent productivity. Looking ahead, Agent AI aims to expand its AI capabilities, omnichannel support, and personalized experiences while delivering actionable insights and seamless integrations—continuing to empower agents and enhance customer experiences globally.
