Inspiration
We wanted to create a web application that helps non-technical prospective entrepreneurs get a feel for the market their business would enter and what its general profitability is based on the aforementioned market analysis factors.
What it does
The application accepts a prompt describing the user's business idea and searches the internet for information relevant to four categories: Demand, Competition, Timing, and Moat (or sustainability/longevity). This is used to generate an overall Market Sentiment for the business idea, which enables the user to answer the question: Should I use THIS idea?
Then the Sentiment score (JSON Object) is passed to the Business Model simulator. This section is dedicated to simulating profit/loss for the business over a user-selected period, considering numerous financial parameters (e.g. Initial Investment, potential loan, and routes of revenue and cost). Some of these parameters are auto-filled based on the JSON Object, such as initial startup cost or suggested avenues for revenue. All of this financial data is then compiled and displayed in a Hub-and-Spoke business model visualization. In addition to limiting the projection by time period, the user can also simulate a stop-loss exit strategy.
Finally, in a cumulative (includes initial information from first page) JSON Object from the previous step, we compare costs with reasonable deduction logic taken directly from an up-to-date Schedule C document and make suggestions on what deductions the business would qualify for. At the very end, it suggests taking this information to a real CPA for professional analysis.
To support the user during their exploration of complex finance and business logistics, we provide a "Learn" tab to reference key terms/concepts that the user might need to know, with sources linked to each section of information.
How we built it
Back-end: Python + Flask, SQL Front-end: React Framework (HTML/CSS/JS)
Challenges we ran into
Researching and gathering industry-quality information to establish our business model logic and Sentiment equation. Additionally, we ran into issues with merging branches in GitHub, where each one of us was focused on a subset of functionalities.
Accomplishments that we're proud of
We were able to compile complicated financial/accountant business logic into something that is visually and conceptually easy to understand for a non-technical audience.
What we learned
We learned different methods for merging conflicting branches. The most important thing we learned is accounting/finance industry data and how each data point interacts to form a general Business Model.
What's next for Founder's Files
The final step will be a website skeleton builder to provide a means to cut down on marketing costs and provide a platform for non-technical entrepreneurs to route transactions or include other means of revenue (ads, for example).
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