This was a Minimum Viable Product built using Instance Segmentation. Frontend was built on React Web framework. Backend developed using FastAPI and database on PostgreSQL. We used Tensorflow Keras for deep learning and used Mask RCNN for Instance Segmentation to mask the vehicle damage output. Before passing the image to the main module our damage detector engine would do some quality control to ensure that vehicle image is authentic and used some additional Third Party API's to fetch the vehicle details from their database which would be helpful in estimating the damage claim cost... The project was built on nodejs express app and PostgreSQL database provided REST API's which interacted with Web (React) and App (Android & IOS). Used redis for message broker service like sending mass emails for appointments. Used Google Cloud Storage for storing the user media. This backend was deployed by me on google cloud's cloud run as microservices on serverless architecture... I have been..