Inspiration
The concept for Rentinder was driven by the need to streamline the rental process, making it easier for landlords to find reliable tenants and for tenants to find their ideal homes. Recognizing the efficiency of the swipe-based selection process in other applications, we saw an opportunity to apply this approach to the rental market, enhanced with AI to improve matches based on detailed preferences.
What it does
Rentinder utilizes a swipe-based interface to allow users to quickly browse and select potential rental properties or tenants. It incorporates an LLM to offer intelligent interactions, such as answering queries about listings and providing personalized recommendations, aiming to make the search process more intuitive and efficient.
How we built it
We developed Rentinder using the MERN stack for a robust, scalable web application. MongoDB is used for data storage, Express.js and Node.js for backend services, and React for a responsive frontend. An LLM integration through enables advanced natural language processing for user interactions and content generation.
Challenges we ran into
Integrating LMMs while maintaining performance was challenging, requiring optimizations to handle real-time data processing. Developing an effective matching algorithm that accounts for diverse user preferences and improves with user feedback also presented a significant challenge.
Accomplishments that we're proud of
Successfully integrating the LLM to enhance user interaction and creating a functional, AI-enhanced matching system are our key accomplishments. These elements combined have significantly improved the efficiency and user experience of the rental matching process.
What we learned
We gained insights into the complexities of AI integration within web applications, particularly in natural language processing and developing algorithms that adapt to user behavior and preferences. We also refined our skills in the MERN stack and AI application in real-world scenarios.
What's next for Rentinder
Future plans include refining the AI features, improving the matching algorithm based on user feedback, and expanding the platform's capabilities, such as adding image recognition for property verification. Our goal is to continue enhancing Rentinder to meet the evolving needs of the rental market.
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