Selma AI Photo Workflow

This use case demonstrates how generative AI can streamline creative production—specifically product photography—by transforming multi-step manual processes into an efficient, repeatable digital workflow. It reflects the CIDM 6096 focus on applying AI to real business challenges, improving both speed and output quality.

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Overview

Traditional product photography requires:

• Physical props

• Lighting setup

• Staging

• Background changes

• Image retouching

• Multiple reshoots

This workflow is time-consuming, skill-intensive, and often expensive. Your Selma Photo Workflow demonstrates how AI reduces this process dramatically by:

• Replacing physical staging with AI-generated scenes

• Eliminating reshoots

• Allowing rapid iteration

• Preserving brand consistency

• Enabling creative experimentation without additional cost

This turns product photography into a flexible digital pipeline instead of a rigid physical one.

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What the Workflow Includes

Based on your document, the workflow walks through:

1. Image Preparation

• Capture simple, neutral product images

• Maintain consistent angles

• Ensure the product is well-lit and clearly visible

This creates a reusable “base” for all future AI-enhanced photos.

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2. Background Enhancement with AI

Using AI, you replace or augment backgrounds to match:

• Seasonal themes

• Lifestyle settings

• Social media styles

• Branding requirements

• Promotional campaigns

This eliminates physical props and set design.

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3. Style Matching

AI tools help maintain:

• Color aesthetic

• Mood

• Texture consistency

• Visual identity

This ensures every product photo aligns with the brand’s personality.

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4. Iteration & Variation Generation

Instead of scheduling new shoots, AI makes it possible to produce:

• Multiple variations

• Testing options

• Marketing layouts

• Seasonal campaigns

• A/B creative assets

…all from a single base image.

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5. The Workflow Document Creation

Evidence of Work:

Visual Summary document:

3KB

Selma_AI_Photo_Workflow.pdf

PDF

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