Fashion design today is bottlenecked by fragmented tools, inaccurate visualization, and costly sampling cycles. Designers constantly switch between sketches, Photoshop mockups, and complex 3D software that take months to learn, yet still struggle to create visuals that truly match production quality. Visualizing fabric drape, testing prints, or adjusting Pantone colors often means juggling multiple tools, long sampling loops, and expensive prototypes.

To solve this, I helped design Desara - an AI-powered 3D fashion design platform that makes product visualization precise, controllable, and production-ready, without the usual 3D complexity. I was part of the journey from 0 → 1, shaping the core product experience.

Fashion design sits between art and production. Traditional visualization tools and physical sampling create friction, cost, and delays in the design-to-production process. Designers are forced to compromise between creative control, speed, and accuracy, which slows iteration and increases costs and waste.

Through in-depth interviews with fashion designers, production teams, and students, combined with observation of real workflows and prototype testing, we uncovered several key insights about 3D visualization and AI-assisted design:

Key Insight: Designers and teams wanted an intuitive, fast, and precise visualization tool that reduces sampling cycles while giving creative control at the garment attribute level. They wanted to focus on brand and design decisions, not technical 3D workflows or prompt engineering.

How might we enable fashion designers and teams to quickly go from concept → photoreal 3D visualization → production-ready design, while giving precise control over every garment attribute, without requiring months of 3D training or relying on unpredictable AI outputs?

Style Studio is a single-screen, modular 3D workspace that helps designers create production-ready garments in minutes. Select a lifelike model, pick a silhouette, apply fabrics and prints, fine-tune every detail (including Pantone inputs), pose and light the model, and view updates instantly, no rendering delays.

The interface is simple and familiar, intuitive drag controls, sliders, and a sidebar asset library, designed to feel like the creative tools designers already use.

Start by choosing a lifelike model from the library and selecting a base garment. In this case, a suit. Our auto-fitting system maps the garment to the 3D model using a material mapping layer for accurate drape and proportion.

Each standard garment (suits, dresses, jackets, etc.) is fully customizable. Edit collars, lapels, pockets, and vents effortlessly. Designers can also upload their own garments in OBJ or CLO formats for complete flexibility

Access a rich library of fabrics, prints, and colors, or upload your own. Apply materials to any garment attribute, sleeve, pocket, or front panel. For fine-grained creative control. This allows designers to experiment freely with combinations while maintaining production-level precision.

Finalize the design by experimenting with pose presets, lighting setups, and environment backdrops. One-click harmonization adjusts lighting and tone for each scene.

Render photoreal 4K outputs in under 20 seconds, capturing every fabric detail, color, and Reflection. ready for manufacturing or marketing use.

Problem: The initial prototype, developed for testing and demos in early 2023, supported only a single global print/fabric applied to the entire garment. While it allowed basic color and print controls, designers quickly found this approach too restrictive. They needed granular creative control. For example, using different fabrics for sleeves or the back, or applying different print scales and placements for specific zones like pockets or collars.

Solution: After validating the prototype concept, we redesigned the entire tool with a stronger brand identity, improved UI, and a focus on designer flexibility. The new version introduced a zone-based attribute editor that enabled per-zone print controls (scale, rotation, repeat) with intuitive drag-and-drop interactions. Additionally, curated silhouettes and fabric presets streamlined the starting workflow, helping designers begin projects faster and with greater creative freedom.

Pilots with 10+ institutional and brand partners (including the London School of Fashion) showed measurable improvements across design-to-production. Designers iterated faster, tested more variations, and produced production-ready visuals without relying on time-consuming samples.

Measurement was based on project timestamps (cycle time), sample order records (samples per style), PostHog logs (render/generate counts), and production cost baselines for sampling budgets.

Next up: real-time collaboration, richer techpacks, higher-fidelity material simulations, and batch colorways for multi-SKU workflows.

Fashion designers are deeply protective of their creative intent, how a garment drapes, how a print lands on a pocket, how colors interact in real light. Many are skeptical of 3D tools or AI because they fear losing the tactile connection to fabric and the craftsmanship behind design.

During early research, we found that while some designers preferred the physical process, most were open to exploring digital tools as long as those tools didn’t compromise their creative control. The key insight: adoption happens when technology augments creativity, not automates it.

And that insight helped us focus on precision, control, and seamless integration rather than flashy automation. This balance of creative freedom + technical accuracy led to strong adoption and positive feedback.