What is RoundCall?
RoundCall is a platform that makes call center employee training more effective and interactive. Employees can improve themselves by practicing through tests, videos, and AI-powered customer simulations. Trainers can assign tasks to students, track their progress, and provide feedback. The platform is designed to help employees communicate effectively with customers and make call center processes more efficient.
Purpose of the RoundCall
This project has been developed to make the training processes of call center employees more effective. Call center staff must undergo continuous training to improve their customer relations and problem-solving skills. Traditional training methods are often time-consuming and ineffective. This project aims to enhance training efficiency by creating an interactive training platform for call center employees.
The platform enables users to improve themselves through tests, practice with various scenarios, and simulate real customer dialogues with AI-powered chatbots. Additionally, a built-in evaluation system will track users' progress and identify areas for improvement. As a result, call center employees will become more proficient in customer relationship management, ultimately enhancing service quality.
Core Functions
1.Instructor Module
- Instructors can log into the platform to create training materials and tests.
- They can assign tasks to students and track their development progress.
- They can evaluate student performance and provide feedback.
- By analyzing test results, they can help address areas that need improvement.
2. Student Module
- Students can enhance their skills through various tests and interactive training materials.
- By completing tasks assigned by instructors, they can increase their points and success levels.
- They can practice real customer scenarios using an AI-powered chatbot.
- Through videos and interactive lessons, they can expand their knowledge base.
3. AI-Powered Chatbot
- Developed to teach call center employees how to interact with customers.
- Creates scenarios that mimic real customer interactions, allowing employees to practice.
- Analyzes user responses and provides feedback on correct and incorrect approaches.
- Generates real-time scenarios to accelerate the learning process for call center employees.
4. Feedback and Evaluation System
- Instructors can provide personalized evaluations to identify students' strengths and weaknesses.
- Automatic performance analysis enables an objective assessment of employee development.
- Test results can be analyzed graphically to offer personalized recommendations for students.
- Self-assessment tools allow students to track their personal development.
Technical Requirements
Technology Stack:
- Frontend: Next.js (A React-based framework used to create a dynamic user interface.)
- Backend: FastAPI (Chosen to build a fast and asynchronous API structure.)
- Database: MongoDB (Used for data storage and user information management.)
- Artificial Intelligence: Gemini was used for the generative AI-based chatbot integration.
Development Process:
- Conducted in-depth research on call center training systems and employee roles.
- Identified necessary features for the project through brainstorming and analysis.
- Defined key components such as frontend, backend, database, and AI integration during development.
- Selected the technology stack and started development.
- Designed and completed the database structure while developing the backend and frontend.
- After finalizing the database structure, we reconsidered our backend technology and held a discussion.
- As a result of the discussion, we decided to rewrite our backend using FastAPI.
- Performed various tests to ensure the system operates without errors.
- Added an AI-powered chatbot to enhance user experience.
- Established instructor and student roles to structure the platform.
- Optimized call center training processes with the AI module and test scenarios.
Source Codes
RoundCall-Chatbot-Prototype (At first we produced the project as a prototype, we organized the remaining developments in the backend, if you want to examine it in more detail, you can look at the chatbot in the backend.)