Ai Rento Soft
LANCER
Lancer:
<= 2 resources OR <=3 weeks effort OR <=$3000 USD
Growth:2 - 4 resources AND upto 4 months OR
upto $30000 USD
Enterprise:Everything else
(Development)
Project Description
An auto-rental company, Ai Rento, aiming to streamline vehicle check-in and checkout, approached Oodles to automate damage detection using AI. With a growing fleet and increasing rentals, the client needed a reliable way to compare pre- and post-rental car images and minimize human error. The platform enabled an API-based solution for real-time vehicle damage detection from uploaded images.
Scope Of Work
The client faced operational delays and inconsistencies due to manual vehicle inspections. They needed an automated image comparison tool to detect dents and scratches reliably. The solution focused on API development, image processing, and AI model integration, ensuring accuracy, speed, and cost-efficiency in damage assessments across rentals.
Our Solution
To solve this, an AI-powered API was developed for image-based car damage detection. The solution used a pre-verified public dataset from Kaggle to train a lightweight model that detects visible dents and damages from uploaded images. The API was designed to integrate with the rental platform's existing workflows and help the team generate damage reports instantly.
Key features include:
- Dent and Scratch Detection: The model identifies and highlights visual damage between two images.
- Kaggle Dataset Integration: Used the Hamza Manssor dataset to train the model on real-world car damage examples.
- Real-time Image Processing: Enables fast and automated image comparisons for before-and-after scenarios.
- Cost-Optimized Deployment: Delivered within 3 days, keeping server-side model training costs minimal and client-controlled.
- API Integration: Built for seamless plug-in with rental operations.
Share Your Requirements