Case Study - Automatic Retouching of Studio Images

Overview

In the highly competitive e-commerce space, high-quality images are crucial for conversions. Our client, a leading online marketplace, relied on professional editors to manually retouch studio images before publishing them. This manual process, while ensuring quality, was costly and limited scalability. We were engaged to develop an AI-powered pipeline that could automate image retouching, ensuring consistency and professional quality at scale.

Challenge

The challenge was twofold:

1. Technological Feasibility – Ensuring that AI models could accurately replicate the work of professional editors, maintaining the high-quality standards required for the platform.
2. Scalability – Deploying a solution capable of handling thousands of images per day, seamlessly integrating with existing workflows.

Given these complexities, a staged approach was critical to managing risk while delivering measurable business value.

Solution

Phase 1: Proof of Concept (PoC)

• Conducted an initial feasibility study on a small but representative dataset.
• Trained and validated computer vision models to perform key retouching tasks (e.g., exposure correction, background refinement, and detail enhancement).
• Engaged key stakeholders early to align on quality expectations and ensure business buy-in.

Phase 2: Incremental Deployment & Optimization

• Adopted a lean approach, gradually expanding coverage by targeting subsets of the product catalog.
• Prioritized low-hanging fruit (categories with straightforward retouching needs) to deliver early wins.
• Iteratively improved model performance, addressing challenges in complex image subsets with diminishing returns.

Phase 3: Full-Scale Deployment

• Technology Stack: Utilized a combination of CNN-based models, generative models, and classical image processing algorithms to achieve high-quality results.
• Scalability Solutions: Handled the large volume of 4K resolution images by leveraging a cluster of cloud instances to efficiently process predictions.
• Deployment: Successfully deployed the solution in Google Cloud Platform (GCP), serving thousands of requests per day.
• Quality Control & Edge Case Handling: Implemented a QC (Quality Control) process with a smart sampling mechanism to review and correct problematic cases. These corrections were used for continuous model retraining and improvement.

Results

• Cost Savings: Reduced manual editing costs by $0.40 per item, leading to $2 million in annual savings.
• Scalability: Enabled the client to scale image processing without a proportional increase in costs.
• Operational Efficiency: Reduced turnaround time for image processing, improving time-to-market for new listings.
• Consistent Quality: Ensured images met professional editing standards, maintaining brand integrity.
• Additional Benefits: Other internal services relying on high-quality retouched images were able to leverage the automated pipeline, allowing them to receive images sooner, faster, and at a greater scale.

Key Challenges & Lessons Learned

• Complex Image Characteristics: Some challenging features required generative AI techniques to enhance and refine.
• Stakeholder Engagement: Our ability to navigate the organization and involve the right stakeholders at the right time was crucial to getting insights, refining requirements, and ultimately securing buy-in for the project.
• Business Impact Beyond Cost Savings: The improvements also enhanced workflow efficiency for multiple teams, accelerating the company’s overall operations.

Key Takeaways

This project highlights our ability to tackle complex AI challenges with a strategic, risk-mitigating approach. By starting with a well-scoped PoC and incrementally scaling, we delivered a high-impact AI solution that not only automated a costly process but also unlocked new growth opportunities for our client.

Our expertise in computer vision, AI deployment, and MLOps allowed us to transform a manual workflow into an AI-driven, scalable operation, reinforcing our commitment to delivering cutting-edge AI solutions that drive measurable business value.