Price is what you pay. Value is what you get. These lines by Warren Buffett inspire you to invest in something that is valuable. Every day you are invested is a day that your money is working for you and despite the economy's ups and downs, the stock market has consistently proven to be a good place to invest your disposable cash and save for your future. But one question that comes in everybody's mind is how to get started with stock investment hassle free? To alleviate the risk and complexities and to make the process easy for beginners, we provide an application which help them to invest money with ease and to ensure a financially secure and stable future.

What it does

It provides you a relatively painless way to invest in stocks if you are a beginner. The idea is to take a portion of your-daily transaction amount which you set in the application and invest it in to the stocks. The investment takes place in a round robin fashion where you set the stocks you want to buy and the amount of money you want to invest. Once that amount exceeds, it will automatically place order and you are good to go.

Say you want to invest $2,000 and put it into the stock market without burning a hole in your bank account right away. This application helps you to save daily say 10% of your daily expenses and put them in to stocks.

How I built it

We used docker to spin up the Mongo DB instance. From end is built using Angular JS, HTML, Bootstrap. We used Java Spring Framework to build the REST APIs and as the underlying language to design the whole application.

Challenges I ran into

  1. Packaging the application for deployment on AWS.
  2. Integrating routers in AngularJS.
  3. Keeping the application simple and easy to use.
  4. Managing the nested objects in mongoDB.


Spring Framework


Amazon Web Services documentation:




Accomplishments that I'm proud of

It works well and looks good.

What I learned

  1. Learned to connect different components and the power of REST API's.
  2. Learned how to package the app and deploy it on AWS Cloud.

What's next for Tradify

We aim to integrate machine learning models to help the user in choosing the right stocks to invest and to gain most out of the investment.

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