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Case Study

Rent Intelligently

AI-powered platform streamlines tenant selection for landlords, providing accurate, automated predictions, enhancing efficiency and rental experience.

The Story

The platform uses AI-driven models to streamline tenant selection for landlords. By integrating AI with business logic, the system predicts the probability of a tenant meeting the landlord’s conditions. Python scripts and machine learning models assess tenants from a pool, helping landlords shortlist the most suitable match based on customized criteria.

The client is an innovative platform that simplifies rental experiences by using AI technology, helping landlords find the ideal tenants based on personalized conditions, ensuring smarter, safer, and seamless property management.

Testimonial

Amit Jangid

Founder & CTO

Challenges

  • > Generating realistic, uniform, and correlated training data encompassing all assessment features.

  • > Identifying the best regression models to predict tenant suitability accurately.

  • > Ensuring smooth model deployment and automating backend workflows to deliver results efficiently.

The Solution

The solution involved synthesizing and validating training data to ensure feature variance and correlation for accurate predictions. Multiple AI models, including Random Forest, CatBoost, XGBoost, and neural networks, were implemented to enhance accuracy. Models were deployed on Google Cloud Platform (GCP) Vertex AI, utilizing Kubeflow Pipelines for seamless integration. Automated workflows were set up with Cloud Scheduler and Cloud Build, ensuring regular data processing and model retraining every four hours for continuous optimization.

The Outcome

The platform enabled landlords to receive accurate, data-driven tenant assessments via automated email updates. The streamlined processes reduced manual effort, improved decision-making, and enhanced overall platform efficiency. With continuous integration and robust pipelines, the system delivered smarter, faster, and more reliable rental matching services.

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