There is a big barrier to entering the cryptocurrency space. In addition to research and knowledge gaps in the general populice, there are technical requirements, such as having a digital crypto-currency wallet and taking an initial and/or ongoing capital investment.
How do we solve it?
What it does
Dabble allows interested parties, and crypto enthusiasts to get involved in buying and owning cryptocurrencies. Users are provided an opportunity to make small investments in their everyday lives in the form of round-up contributions. Every purchase made on a credit or debit card will be rounded up to the nearest dollar, and the difference (e.g. $0.70 on a $8.30 purchase) will be allocated to a crypto-investment portfolio for the user.
This user level fund is funneled to the Dabble analytics team, who will allocated the fiat currencies of the user into various cryptocurrencies (the selection depending on user preferences, which are selected at the beginning of the process). This will allow users to make small investments into the cryptocurrency world, with low risk in absolute loss, whilst maximizing the potential for a knowledge gain. Our team is hoping to push the knowledge and experiences of getting involved in this space to many enthusiasts or everyday people who have an interest in cryptocurrencies, but have been unable to overcome the barriers to entry.
How I built it
We consulted various friends and experts in the field to wireframe a concept. The next step is to undergo the process of data validation and processing, as well as designing an end-to-end user experience that best suits the needs of our clientele.
Our team is planning to use our diversified set of skills to streamline an all-inclusive product. We plan to use a MEAN stack and the Apache Cordova framework to create a hybrid mobile (i.e. Android and iOS) application. Our back analyses will use machine learning and deep learning algorithms (e.g. sk-learn and PyTorch) in conjunction with Twitter feed data (for sentiment analysis purposes); this will serve as our model generating tool for our token selection process.