Inspiration
The inspiration for this project came from the fact that a few of my friends did not like the terms of their lease and weren't particularly happy with their situation. This happens to millions of people around the world, who don't have the expertise and experience to look for the fine print that can ruin the fun of independence.
What it does
SuiteLife analyses your lease agreement and summarises the terms. It checks for any potential issues with the lease and recommends action items to improve the lease conditions. It has a built-in 'fairness score' that evaluates how far the leasing agreement deviates from the 'standard lease'. Additionally, it utilizes the users location to give more relevant responses, that are applicable to the province the user resides in.
How we built it
- Flask: we used Flask for the backend, we used MongoDB for the database and Gemini API for the analysis
- Front End: We used HTML, CSS, Bootstrap, Google Fonts, and Jinja2 for the front end.
Challenges we ran into
- Debugging the AI Client and the structured response took a few hours, we had to try multiple different AI models and APIs before we had a successful break.
Accomplishments that we're proud of
- We are very happy with the way this project looks, from a front-end perspective and we also love how useful it is to us personally.
What we learned
- Fix your posture when you code for more than 5 hours at a time.
What's next for SuiteLife - Find. Love. Rent.
- Instead of using the Gemini API, we hope to train the model using our own network and data.
Log in or sign up for Devpost to join the conversation.