Inspiration

With the rise of meme stocks taking over the minds of gen-z, vast amounts of young people are diving into the world of finance. We wanted to make a platform to make it easy for young people to choose stocks based on what matters most: the environment.

What it does

Loraxly speaks for the trees: it aggregates realtime stock data along with articles about the environmental impact a company has on the world. It then uses OpenAI's powerful GPT-3 api to summarize and classify these articles to determine if the company's environmental impact is positive or not.

How we built it

Figma, React, Javascript, Kumbucha, Python, Selenium, Golang, goroutines, Cally, firebase, pandas, OpenAI API, Alphavantage stock api, Doppler, rechart, material-ui, and true love.

Challenges we ran into

some goroutines being ahead of others, fixed this with channels. article summaries not making since, we had to be more granular with our article selection. the chart was tough to setup. we didn't get going until saturday afternoon.

Accomplishments that we're proud of

getting things working

What we learned

alphavantage api has some major rate limiting.

What's next for Lorax.ly

Adding a trading function and creating an ETF comprised of environmentally friendly companies that people can invest in.

Built With

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