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AI Storyboard
AI Storyboard
Fall 2024 | Harmonizing Impact
June 2019 | Foundational Work ·
Early Career Project
Fall 2025 | Prof. Paolo Grazioli
Fall 2025 | Prof. Paolo Grazioli
Service Designer
Service Designer
Service Designer
Service Designer
Service Designer
Service Designer
Skills
Skills
Skills
Storyboarding
Storyboarding
Storyboarding
Visualization
Visualization
Visualization
Prototyping
Prototyping
Prototyping
Mapping
Mapping
Mapping
Narrative
Narrative
Narrative
Methods
Methods
Methods
Prompting
Prompting
Prompting
GenAI
GenAI
GenAI
Synthesis
Synthesis
Synthesis
Iteration
Iteration
Iteration
Consistency
Consistency
Consistency
Summary
Summary
Summary
This project explores the integration of Generative AI (DALL·E 3) to visualize the patient experience at Rhythm Therapeutic Centre, an equine therapy facility for individuals with disabilities. Beyond simple image generation, I utilized AI to craft a cohesive visual narrative, employing advanced prompting, iteration, and post-processing to accurately capture the emotional arc of the user journey.
This project explores the integration of Generative AI (DALL·E 3) to visualize the patient experience at Rhythm Therapeutic Centre, an equine therapy facility for individuals with disabilities. Beyond simple image generation, I utilized AI to craft a cohesive visual narrative, employing advanced prompting, iteration, and post-processing to accurately capture the emotional arc of the user journey.
This project explores the integration of Generative AI (DALL·E 3) to visualize the patient experience at Rhythm Therapeutic Centre, an equine therapy facility for individuals with disabilities. Beyond simple image generation, I utilized AI to craft a cohesive visual narrative, employing advanced prompting, iteration, and post-processing to accurately capture the emotional arc of the user journey.
The Process
The Process
The Process
Initial Exploration : Early prompting experiments revealed a gap in emotional resonance. While the AI generated relevant imagery, the results lacked the specific atmospheric depth required for a therapy context.
Initial Exploration : Early prompting experiments revealed a gap in emotional resonance. While the AI generated relevant imagery, the results lacked the specific atmospheric depth required for a therapy context.
Initial Exploration : Early prompting experiments revealed a gap in emotional resonance. While the AI generated relevant imagery, the results lacked the specific atmospheric depth required for a therapy context.
Descriptive Iteration : I refined the workflow by introducing hyper-specific scene descriptions. This significantly improved the emotional quality of the visuals, though character consistency remained a challenge across different frames.
Descriptive Iteration : I refined the workflow by introducing hyper-specific scene descriptions. This significantly improved the emotional quality of the visuals, though character consistency remained a challenge across different frames.
Descriptive Iteration : I refined the workflow by introducing hyper-specific scene descriptions. This significantly improved the emotional quality of the visuals, though character consistency remained a challenge across different frames.
Achieving Consistency To unify the visual narrative, I implemented advanced prompting techniques, specifically leveraging Seed Numbers. By establishing detailed character archetypes and locking the seed values, I achieved character uniformity across diverse scenes.
Achieving Consistency To unify the visual narrative, I implemented advanced prompting techniques, specifically leveraging Seed Numbers. By establishing detailed character archetypes and locking the seed values, I achieved character uniformity across diverse scenes.
Achieving Consistency To unify the visual narrative, I implemented advanced prompting techniques, specifically leveraging Seed Numbers. By establishing detailed character archetypes and locking the seed values, I achieved character uniformity across diverse scenes.
Visual Fine-Tuning To ensure high fidelity, selected scenes were polished using Adobe Photoshop’s Generative Fill, correcting minor artifacts and enhancing spatial coherence.
Visual Fine-Tuning To ensure high fidelity, selected scenes were polished using Adobe Photoshop’s Generative Fill, correcting minor artifacts and enhancing spatial coherence.
Visual Fine-Tuning To ensure high fidelity, selected scenes were polished using Adobe Photoshop’s Generative Fill, correcting minor artifacts and enhancing spatial coherence.
Final Storyboarding The finalized assets were compiled in Figma, where I integrated dialogue and interaction notes to complete the user journey map.
Final Storyboarding The finalized assets were compiled in Figma, where I integrated dialogue and interaction notes to complete the user journey map.
Final Storyboarding The finalized assets were compiled in Figma, where I integrated dialogue and interaction notes to complete the user journey map.
The Before Journey
The Before Journey
The Before Journey
The After Journey
The After Journey
The After Journey
Spoiler : I can make your team look good
Spoiler : I can make your team look good
PLVIxDesign
PLVIxDesign