WishGuard AI

Inspiration

User saves a Product as a favourite or in the Website Cart for a duration without action and

no sales conversion is happening for the eCommerce web shop

Background:

A user, Alice has been browsing an online fashion retailer's website and saved a particular dress as a favourite. The web shop aims to convert this interest into a sale using generative AI- driven strategies

.## What it does Use case:

Generative Ai strategizing the techniques to improve the conversion of the B2C Ecommerce web shop with targeted hyper-personalised Marketing to the clients. Functional Pre-requisites state:  The eCommerce web shop is live and taking orders from the B2C clients.  The shop owners are struggling with 'Wishlist Abandonment' & 'Cart Abandonment' challenges.  The access to the data of the 'Wishlist' & 'Cart' could be shared with 3rd party SaaS tools with compliance

.## How I built it

High-level technical requirements:  Chrome extension for our application that will allow access to the web shop data like Cart and Wishlist for the users.  OPTION 1: The user data, Product data can be fetched by the extension seamlessly reducing any effort of additional data upload to start. OR  Option 2: We create a central hub for the backend to extract the details of the Wishlist and Cart using the API's provided by the shop owners.  React based frontend SaaS application with the approach taken as (OPTION 1 OR OPTION 2). o User onboarding requirement for the options will be a back-end admin for our application.  Data-base architecture with TiDB Cloud clusters  Reporting and analytics with the TiDB  Generative-AI enablement end points to extract suggestions and trigger communication to the clients.  Scaling and deployment approach of the MVP

Challenges I ran into

Accomplishments that I'm proud of

What I learned

What's next for WishGuard AI

Built With

• amazon-web-services
• bedrock
• chrome
• claude3
• fastapi
• langchain
• llm
• react