Project Info

Rentora

Devpost

"Rent Now"

Inspiration

The inspiration behind Rentora stems from the challenges we faced when searching for off-campus housing ourselves. We recognized the need for a platform that simplifies the entire rental process, from application to property selection.

What it does

Rentora is a comprehensive platform designed to streamline the off-campus rental experience for students. It helps users in creating compelling rental applications, leverages AI for property matching, and offers rental-related information.

How we built it

Python: Used for backend tasks, including server-side logic, data processing, and integration with AI algorithms. JavaScript (JS): Employed for frontend development to create an interactive and dynamic user interface. CSS: Utilized for styling and formatting the website to ensure an appealing and user-friendly design. OpenAI: Integrated to implement advanced AI capabilities, such as natural language processing and recommendation systems. Google Cloud Firebase: Used for backend services, including database management, user authentication, and data storage. Google Maps API: Integrated for location-based services and property mapping features, enhancing the user experience. Flask: Employed as a Python web framework to build the backend server, handle HTTP requests, and serve API endpoints. NodeMailer: Used for sending email notifications and communications to users, enhancing the platform's functionality.

Challenges we ran into

During the development process, we faced challenges in optimizing the AI algorithms for accurate property matches. We also ran into challenges when trying to properly build the rental application.

Accomplishments we're proud of

We're proud of our AI-driven property matching and the easy rental application builder.

What we learned

We learned the significance of leveraging technology to solve problems that affect us and our peers. We also learned to develop in Python and connect it to a React website.

What's next

In the future, Rentora aims to expand its services to cover a wider range of universities and offer additional features, such as integrated payment solutions and enhanced property management tools.

Analysis

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Metric

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only
  • CSSIn code
  • ExpressIn code
  • FirebaseIn code
  • HTMLIn code
  • JavaScriptIn code
  • Next.jsIn code
  • OpenAIIn code
  • ReactIn code
  • Tailwind CSSIn code
  • TypeScriptIn code
  • FlaskClaimed
  • PythonClaimed

10 of 12 appear in the indexed code. 2 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

472 KB

Source files

92

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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