Recomm-ai

Inspiration

The Restb.ai company has provided us with a client key to access their APIs. We are inspired by the content of these.

What it does

A web page has been developed that allows the user to receive suggestions for improvements to their electrical appliances based on the quality of products found in their kitchen. From there, products are filtered that are for sale that can fit the monetary quality of the client. This project has been designed in order to be able to expand it throughout the furniture sector in the future.

How we built it

It has been done using the following environments: Javascript, Nextjs, Reactjs, Nodejs and sqlite3

Challenges we ran into

The main problems have been finding a database that meets all the requirements that our app needs regarding the home appliance sector and a lot of time has been wasted creating one, from scratch, that meets all the requirements; there were problems when requesting the Digital Ocean server and this has caused us several problems when uploading photos to the cloud to be able to use them on our website.

Accomplishments that we're proud of

We are proud to have been able to finish the project in such a short time, taking into account that the proposed challenges can always be expanded and thought on a much higher scale.

What we learned

We have learned the operation, behavior and how to maintain a good connection of the API with the web interface. Basic concepts have also been learned, with the help of the talk that the company did, about machine learning.

What's next for Recomm-ai

The future of Recomm-ai is to adapt it to all real estate sectors and improve the structure of the web.

Built With

• api
• github
• javascript
• nextjs
• react
• sqlite