This repository contains a MongoDB-powered retail store demo designed to illustrate how MongoDB can enhance the modern e-commerce experience and can be easilly be integrated with modern technologies to enhance the shopping experience for the customer. The demo highlights various features that serve as a reference architecture for developers looking to integrate MongoDB into retail solutions.
Built with modern technologies, this demo is continuously evolving with new features added over time. Some features are developed in collaboration with MongoDB partners to create cutting-edge, scalable e-commerce solutions.
This README will guide you through the steps and prerequisites needed to replicate the demo in your own environment. Since some features require third-party services or specific configurations, the README is organized to help you focus on the features that interest you most. Each feature has its own dedicated section to guide you through the setup process, ensuring a smooth and streamlined experience.
Customers have higher expectations than ever before, they expect seamless shopping experiences. To meet these evolving needs, retailers must work with modern flexible technologies that are able to scale and update as their requirements do. This demo includes key features that reflect the needs of a contemporary retail environment, such as AI-powered agentic chatbot, omnichannel ordering, and more. The demo integrates various technologies and services that work together to create a seamless shopping experience. MongoDB’s flexible, scalable, and performance-oriented data model supports the backend infrastructure.
In this demo, users will be able to explore how MongoDB optimizes data management and enhances system performance in a retail environment, while also facilitating the integration of AI technologies and systems—such as Dataworkz on the agentic RAG chatbot feature—by storing complex, rich data structures that merge operational and AI data. The solution serves as a practical guide for developers interested in implementing similar architectures in the retail industry, showing how MongoDB canbe leveraged to solve common challenges faced in modern e-commerce applications.
Let’s get started! To follow along smoothly and run this demo in your own environment, make sure you have the following tools:
- MongoDB Atlas Account. Create an Atlas account at https://cloud.mongodb.com
- Install Node. This will be required to install the node modules which contain all the necessary packages to run our demo.
- Install Git. This will be required to clone the demo repository.
Depending on the feature or features you wish to run you might need additional instals.
Today’s shoppers want quick, accurate answers. With this microservice the retailer can support customers at any point in time through an Agentic RAG chatbot. This Agent is context aware of the business policies as well as the user’s order history and preferences, delivering the customer with the answers they need without waiting on hold or navigating complex menus.
See the full step by step README to run this microservice from your own environment in the demo.
Customers expect a seamless shopping experiences that blend online and offline seamlessly. To meet these evolving needs, retailers must offer convenient options like Buy Online, Pick Up In Store (BOPIS) and home delivery. This microservice will allow you to create a new order selecting your desired shipping method.
See the full step by step README to run this microservice from your own environment in the demo.
Tech Stack:
- MongoDB Atlas Account
- Node
Comming soon!
Prashant Juttukonda - Principal
Rodrigo Leal - Principal
Genevieve Broadhead - Global lead, retail solutions
Angie Guemes – Developer & Maintainer
Florencia Arin – Developer & Maintainer
This demo was made possible with the contributions of:
Sachin Smotra – Contributed to Agentic RAC chatbot
Sachin Hejip – Contributed to Agentic RAC chatbot