Overview

The client is a prominent automobile-selling company in the USA, specializing in online sales of second-hand cars. With a reputation built over the last decade and a half, the client’s business model has made it the preferred choice for millions of customers looking to sell their cars online. The company is dedicated to providing a fully automated service scheme for online car buying procedures, ensuring a hassle-free customer experience.

Technical Stack

  • AWS Sagemaker
  • AWS ECS
  • Python
  • Keras
  • Nodejs
  • React
  • Postgres SQL
  • Industry

    eCommerce

  • region
  • Region

    USA

  • project-size
  • Project Size

    Non- Disclosable

Highlights

Parallel GPU Processing

Advanced Image Recognition (CNNs)

Microservices Scalability

Real-time Processing Optimization

Challenges & Solutions

The growing dataset of car images poses scalability challenges, affecting the system's ability to handle increased processing demands.

  • Solution: We adopt a microservices architecture, allowing the system to scale horizontally by distributing tasks across multiple instances, ensuring seamless scalability as the dataset expands.

The existing image recognition algorithm struggles with accurately identifying car boundaries, leading to inconsistencies in the editing process.

  • Solution: Our AI integration engineers integrated advanced deep learning models, such as convolutional neural networks (CNNs), to enhance image recognition accuracy and ensure precise identification of car boundaries for effective masking.

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Core Features

  • Agile Workflow Integration
  • Modular Augmentation Pipeline
  • Intelligent Image Naming (NLP)
  • CI/CD for Image Editing Algorithms
  • no.-of-resources
  • No. of Developers

    06

  • time-frame
  • Time Frame

    December 2021 - Ongoing

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