AI-Powered Creative Automation System

Overview

Creative teams lose days on manual marketing asset production, with inconsistent brand use, multi-platform resizing, and weak product-identity control. The system automates the pipeline from brief to delivery: it uses Computer Vision for design analysis, automated prompt engineering, fine-tuned generative models, smart one-to-many resizing (Saliency Maps), and ControlNet for product fidelity, with automated brand and compliance checks—cutting production from days to minutes while keeping full brand consistency.

Achievements

The system successfully automated multi-platform asset generation (Instagram, YouTube, Display Ads) while maintaining 100% brand consistency. It implemented automated Delta E color accuracy checks and structural conditioning to ensure pixel-perfect product fidelity. The solution scaled asset production significantly, allowing for high-volume batch processing without increasing manual labor costs.

Responsibilities

• Developed a Computer Vision layer for style recognition, pattern extraction, and compositional analysis of existing brand assets.
• Designed a proprietary fine-tuning pipeline (Full-parameter tuning) for brand-specific generative models and implemented structural conditioning (ControlNet/IP-Adapters).
• Built a smart resizing module using Saliency Maps to preserve focal points and ensure platform-specific safe zone compliance.
• Created an automated multi-level validation system for prompt optimization and brand safety (negative prompting, logo integrity, and legal compliance).

Technologies Used