AI-Driven Product Customization Platform

Creative Director | Product Strategy, Interactive Design, UX Systems

KEY CONTRIBUTIONS

AI-Driven Personalization

  • Integrated generative AI to enable dynamic, behavior-driven interfaces with real-time 2D customization.

  • Designed adaptive UX patterns that support personalized user journeys, enhancing creative expression and engagement.

  • Created scalable interaction logic that adjusts based on user behavior, supporting long-term product growth.

Real-Time Systems Thinking

  • Built interaction frameworks that scale across real-time environments, supporting seamless transitions and responsive microinteractions.

  • Integrated motion as a core element of the product architecture, aligning motion logic with broader product goals.

  • Used real-time data to optimize system performance, reduce cognitive friction, and improve user retention.

Interaction System Design

  • Developed real-time interaction systems that reduce cognitive load and guide users through complex customization workflows.

  • Created foundational UX architecture for multi-step interactions, integrating responsive feedback loops for intuitive navigation.

  • Designed adaptive, context-aware interactions that support personalized user journeys, enhancing creative expression and engagement.

DESIGN STRATEGY

The Ablo.ai design system supports a seamless, scalable user experience for AI-driven fashion creation. It includes a comprehensive set of font styles, color palettes, and reusable components, allowing for rapid prototyping, consistent brand experiences, and efficient design-to-development handoffs.

This system is designed to reduce cognitive load, speed up prototyping, and ensure visual consistency across all product surfaces, supporting the broader Ablo.ai mission of democratizing fashion design.

Components

  • Top Navigation

  • Sub Menus

  • Buttons

  • Visual Cards

  • Input Fields

  • Interactive Elements

  • Design Tokens: Font sizes, spacing, color tokens for rapid scalability

User Journey – From First Interaction to Product Mastery

AI Model Creative Training & User-Centric Styles

Recognizing our users weren't designers, we focused on providing intuitive starting points instead of complex prompts. Collaborating with a UX researcher, we analyzed current fashion trends and user needs to develop curated style categories (e.g., Kidult, Line Art, Pixel, Monochrome). This system empowered users to generate high-quality, brand-aligned results with simple selections, significantly reducing cognitive load and enhancing creative confidence.



I led the creative direction for training our customized Stable Diffusion XL model, specifically leveraging LoRA (Low-Rank Adaptation) techniques. This was crucial for shaping Ablo.ai's unique aesthetic output:

Strategic Dataset Curation: I prepared and curated extensive image datasets that served as the AI's foundational learning material. This involved strategically sourcing diverse visual references (from the web) and generating new ones (using ComfyUI) to align the AI's output with our desired aesthetic (e.g., minimal forms, nostalgic textures, sculptural silhouettes, and our specific 'Kidult' or 'Line Art' styles).

Workflow for Dataset

For instance, to achieve our distinct 'Line Art' style, I personally generated a dedicated training dataset in ComfyUI, which was then used to train a specific LoRA model. This was a critical step in programming the AI's visual vocabulary.

Custom Model Deployment: This iterative process culminated in the deployment of our custom-trained LoRA models alongside the base Stable Diffusion XL, enabling our platform to generate consistent, brand-aligned outputs at scale.

Semantic Training & Captioning Guidance: I partnered closely with engineers to translate subjective creative concepts like 'soft,' 'playful,' or 'edgy' into actionable AI learning parameters. This included providing guidance on detailed image captioning (leveraging LLMs for description), ensuring the AI accurately interpreted and categorized stylistic nuances within the dataset. This defined how the AI would understand and reproduce specific visual languages for both txt2image and img2img generation.

Workflow for Dataset

Defining the Brand Identity for ABLO.AI

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Result & Impact

  • Reduced Cognitive Load: Faster onboarding and higher first-session success rates.

  • Higher Retention: Increased return visits and user engagement through context-aware guidance.

  • Scalable Design System: Developed reusable frameworks that reduced time-to-market for new features.

  • Business Growth: Achieved 20% increase in user engagement through personalized, real-time interaction models.

  • Social Impact: Built a community of 235K+ followers across platforms, creating an active, recurring user base with high engagement rates.

  • Recognition: Featured in Elle, Vogue Business for innovative use of AI in digital product design.

  • Ecosystem Impact: Positioned Ablo.ai as a critical piece in the larger Space Runners ecosystem, connecting product creation (Ablo.ai), digital engagement (Spaceverse), and ownership (Digital Collectibles).