About this Project
This project focuses on designing an AI-powered Call Center Web Application that automates outbound calls, collects qualified leads, and schedules meetings automatically. The goal was to eliminate manual calling, reduce operational effort, and create a seamless experience for sales teams and administrators through thoughtful UI/UX design. The system allows users to upload call lists, define calling schedules, and let an AI Agent handle conversations, lead qualification, and meeting booking, while keeping admins informed via real-time email notifications.
Problems
Based on common call center workflows, several critical user problems were identified. Manual outbound calling consumes a significant portion of agents’ working hours, reducing overall efficiency. Managing large call lists is often stressful and prone to human error, leading to missed or incorrect follow-ups. As a result, leads are frequently lost, duplicated, or poorly tracked across different systems. Meeting scheduling further complicates the process, as agents must switch between multiple tools to complete a single task. Additionally, administrators lack real-time visibility into booked meetings and overall performance. There is also no centralized system to effectively monitor AI activity or call performance. Together, these issues negatively impact productivity, team motivation, and overall business outcomes.
Solving UX & Design Challenges
Designed a step-by-step guided workflow instead of complex multi-form screens
Kept one primary action per screen to reduce cognitive load
Used a dashboard-first approach to give users immediate insights after login
Simplified information hierarchy to support non-technical users
Clearly communicated AI activity and call progress to build user trust
Balanced automation with manual overrides to maintain user control
Solving Development Challenges
Proposed a modular system structure to support scalability and future features
Designed workflows that can handle large call lists efficiently
Planned real-time updates for calls and meetings within the dashboard
Structured AI interaction points to allow smooth integration with backed systems
Ensured the UI supports future analytics and reporting expansion
Solving AI Challenges
Designed AI behavior to initiate, manage, and close conversations autonomously
Integrated AI lead qualification logic into the call flow
Automated meeting booking based on user intent detection
Reduced manual data entry by syncing AI outputs directly to the dashboard
Style Guide
We developed a comprehensive style guide for Advance Marketing, emphasizing a vibrant and engaging visual approach. Green was selected as the primary color due to its strong associations with growth, success, and reliability.
