- Trained AI models to accurately recognize and categorize various customer support requests from incoming emails.
- Programmed the chatbot to engage in conversations with customers to confirm intent, identity, and gather data for requests.
- Adopted a microservice approach for flexibility and scalability.
AI-powered Customer Support Automation
Training a chatbot with advanced AI models to help classify customer intent and gather data.
The Story
Our client for this project is a provider of global digital payment solutions. The company came to us looking to improve its customer support processes, with the focus on email support, reducing costs via AI-powered automation, and decreasing response time, all while integrating seamlessly with the company's existing systems.
Technology: Python, C#/.NET Core, RabbitMQ, Docker/Kubernetes, Redis, AWS EKS, AWS ECR, and AWS Elasticsearch
Challenges
Early on, we realized the system would need to handle various customer support requests accurately and autonomously. Implementing an effective natural language understanding system (intent recognition service) and seamlessly integrating AI components (such as chatbot service) were significant challenges. Ensuring data privacy compliance and seamless integration with existing systems required careful consideration.
Key Features
Hitting The Target
The outcome was a successful implementation of an AI-driven customer support automation system that significantly reduced response time and costs for our client. By automating the recognition and categorization of customer requests and enabling AI-powered chatbot interactions, the company improved the efficiency of handling customer requests. The integration of various technologies within a microservices architecture, along with the AWS cloud deployment, resulted in a streamlined and effective solution that met the company's goals.
