Enterprise AI Background Removal Platform
Adge-Angle is an enterprise-grade AI platform that removes image backgrounds at scale for high-volume creative workflows. It pairs a high-performance inference backend with a polished glassmorphism frontend built for tough extractions like fine hair, sheer veils, and transparent glass.
<50ms
Inference Per Image
500+
Images Per Batch Session
99.2%
Edge Accuracy Score
0
Training Required for End Users
Client
Confidential
Industry
Artificial Intelligence / Computer Vision / Creative Technology
Timeline
8 Weeks to MVP
Team Size
3
Year
2024
Status
MVP
01 / THE CHALLENGE
The Challenge
E-commerce operations teams, digital agencies, and automotive dealerships process hundreds to thousands of product images daily. Manual photo clipping in Photoshop takes 5 to 15 minutes per image. Outsourcing to photo editing vendors costs $0.50 to $2.00 per image with 24 to 48 hour turnaround. Existing consumer tools like remove.bg lack batch processing, API access, and accuracy for edge cases like bridal veils, fine hair, and transparent glass.
The client needed a solution deployable in-house or via API, capable of handling 500+ images per session without quality loss, integrating into their DAM pipeline, and delivering results on par with professional manual clipping. Key requirements: sub-100ms inference per image, WebSocket progress tracking for batch jobs, and a frontend that non-technical operators could use without training.
02 / OUR APPROACH
Our Approach
AI Model Selection & Fine-Tuning
Evaluated multiple segmentation architectures on a domain-specific dataset of eCommerce, automotive, and fashion images. Selected a PyTorch and HuggingFace base model, then fine-tuned it on edge cases like hair strands, transparent objects, and complex fabric textures to beat competitor accuracy benchmarks.
High-Throughput FastAPI Backend
Built a Python/FastAPI inference server with asynchronous WebSocket support for real-time batch progress tracking. Implemented GPU-aware job queuing and a dedicated 'Studio Mode' endpoint with adjustable edge softness and confidence threshold parameters for precision work.
Glassmorphism React Frontend
Engineered a React, TypeScript, and Vite frontend with a zero-training UX. Drag-and-drop ZIP uploads trigger batch mode. Single-image uploads switch into Studio Mode with live edge-softness controls. Built with shadcn/ui and Tailwind CSS for a premium glassmorphism aesthetic.
REST API for Developer Integration
Exposed a clean, documented REST API allowing developers to integrate background removal directly into their CMS, DAM, or e-commerce platform. Pay-per-generation pricing model with API key authentication, rate limiting, and Webhook callbacks for async batch completion.
03 / ARCHITECTURE
Technical Architecture
04 / RESULTS
Results & Impact
<50ms
Inference Per Image
500+
Images Per Batch Session
99.2%
Edge Accuracy Score
0
Training Required for End Users
- Cuts 5 to 15 minutes of manual Photoshop work per image, reducing creative operations cost by around 90%
- Batch mode processes full product catalog folders of 500+ images with real-time WebSocket progress updates, no page refresh needed
- Handles difficult extractions including fine hair strands, sheer wedding veils, and transparent glass objects
- REST API integrates directly into existing DAM, CMS, and e-commerce pipelines without requiring the UI
- Studio Mode gives creative directors control over edge softness and confidence thresholds for precision work
06 / USE CASES
Use Cases
E-commerce & Retail
Automating conversion of raw product photography into catalog-ready transparent PNGs
Marketing & Advertising
Rapidly extracting fashion models for multi-channel digital ad variations
Automotive Dealerships
Replacing cluttered parking lot backgrounds with branded virtual showrooms
Real Estate
Sky replacements and clutter removal for high-end property listings
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