An AI-driven chatbot to facilitate human-like customer communication



The Challenge

The major challenge while developing this project was to train our AI for different types of customer requests like:

  • Refunds

  • Payment resolutions

  • Subscription plan changes

and many other use cases where human intervention is a must priority.


Project Highlights

  • Learning from Human Agents

  • Information Collection

  • Dynamic Responses

  • Human-Like Communication

  • Reduce Agent Inboxes

  • Easy Server Integration


The chatbot we built provides fully automated conversations without sacrificing the human touch for customer support.

1. Bot learns from previous agent responses.

2. Bot responds like a human, adapting to user situations dynamically.

3. After, Bot can auto-respond to related questions, no matter the complexity.

Creative Designs

Technical Architecture

Leader Of The Effort

Sanjeev Verma

Exp: 20+ Years

The Subject Matter Expert

Sanjeev Verma has been actively conceptualizing and creating software solutions for the past 20 years in the IT domain. He has worked on technical leadership positions with Marriott Vacations, Disney, MasterCard, Statefarm, and Oracle. He has been a key player in developing, implementing, and monitoring Digital Solutions ranging from IoT solutions & products, Mobile and Web Development, and Digital Marketing to Full Stack Development and CMS solutions.

Why Biz4Group

Trusted Advisors

Skilled Developers for Deployment

Collaborative efforts of Subject matter Experts

On time delivery ensuring Desirable Outputs

Distinctive Quality

Offering exemplary code quality

User-friendly UI/UX

Prioritize client expectation

Continuous Assistance

24/7 Technical Support

Post Delivery Consultation

Continuous Server Monitoring

DB Clean Up

Cost Effective Customer Support Plans

Going Above & Beyond

System Generated Questions

Using advanced technologies, the system can process both raw audio and text inputs. These inputs are converted into machine language and stored in the database. The stored information is then sent to OpenAI, where it generates follow-up questions to learn more about the user and improve its training.

Generic Answer Population

The chatbot has the capability to receive questions and use the information stored in the database to create appropriate answers.

Development Life Cycle

Technology Stack