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I specialize in AI-driven visual creation, focusing on high-end product imagery and short-form video concepts for modern brands.
My work combines creative direction, branding, and generative AI tools to produce visually striking content for industries like beauty, fashion, and footwear. I explore how composition, texture, lighting, and storytelling can elevate product identity and create emotional engagement.
Using AI not just as a production tool, but as a creative partner, I develop unique concepts, campaign visuals, and experimental designs that help brands stand out in a fast-evolving digital landscape.
Open to collaborations in product visualization, creative campaigns, and AI-powered content production.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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My Creative AI Video Workflow:
Claude for creative ideation, Google Whisk for visual references, Flora for motion prototyping, then Runway or Veo 3 for final footage generation.
Each tool handles a specific stage of the pipeline, prototype cheap, generate strategically, then bring it all together in After Effects. The real skill isn't using AI for everything, it's knowing when traditional methods still win.
great flow! i haven't tried google whisk yet but looks promising!
Lately I've recognized this direction on the rise and been inspired to create a collection of 18 images blending the Classical Art - Renaissance oil painting mastery with digital pixel/ASCII aesthetics, Classcii. It is a mix of centuries, a modernized and futuristic direction of the classic.
Each image is crafted around a specific tension, the classical figure or scene rendered in full oil mastery, while the digital/ASCII layer intrudes at a specific point.
Using the @Contra Labs ecosystem to choose the most adequate Ai models from the Creative Arena Leaderboard, I wanted to briefly share my personal taste and evaluation on the outputs these models generated, based on the benhchmark methodology.
For the imagery references I used Seedream 5 Lite and Google Nano Banana 2, whereas for the Image to Video I used Kling 3.0 and Veo 3.1 Fast.
In terms of Visual quality & aesthetics overall I would rank them fairly simillar with Seedream having a slight edge on the composition, specfically achieving more symmetrical outcomes featuring center alignment and a better use of whitespace, opposed to Nano Banana 2 where the use of rule of thirds is more prominent, making it visually in comparison less balanced.
Considering the Prompt adherence & accuracy, I find both models very much aligned, having Nano Banana 2 more intensified use of asscii / pixels across all outcomes, which according to my minimal taste I would rank this a weakness rather than a strong side.
Finally, in terms of Motion Realism I would unanimously rank Kling 3.0 as the better option here, considering the fluidness and physics consistency among majority of the elements in the reference. Additional advantage will be the ability to perform better at no prompt insertion compared to Veo 3.1 fast.
You can download the collection here.
Super work
What if you could turn a simple product into a cinematic ad?
Creating high-end product commercials usually requires a full team, expensive equipment, and complex editing.
So I built Cinematic Product Reveal: AURA — a simple AI workflow that transforms any product into a cinematic advertisement.
Starting from a basic product image, the system generates a structured visual story:
Atmosphere (void & tension)
Energy build
Product reveal
Final cinematic impact
No actors. No studio. Just a clean, repeatable system.
In this demo, I used a simple perfume image and turned it into a sci-fi luxury commercial.
The best part?
This workflow can be reused for any product — fashion, tech, sneakers, and more.
🎬 Watch the workflow in action above.
This is really well done.
What I like most is that it doesn’t just look cinematic , it also feels like a workflow someone could actually build on and reuse. That makes it much more valuable than a one-off result.
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