[SeeStone]
AI-Powered Fashion Buying Platform

B2B Optimised Seasonal Buying Product

Timeline: 7 months (ongoing)

Tools: Figma, FigJam, Slack, Atlassian, Framer

Role: Branding & UX/UI Designer

[Overview]

SeeStone is a B2B buying platform designed for fashion retailers to optimise seasonal purchasing decisions using AI.

Fashion buyers traditionally rely on spreadsheets, manual analysis, and instinct when planning seasonal orders. This process is time-intensive and often leads to over-buying, unsold inventory, and heavy markdowns.

SeeStone was created to streamline this workflow - transforming complex data into clear recommendations so buyers can make faster, more confident decisions.

[The Problem]

Fashion buying is both creative and analytical. Buyers want to focus on curating collections and building a strong seasonal narrative. However, a large portion of their time is spent manually analysing spreadsheets to determine:

• size curves
• sales velocity
• stock levels
• seasonal demand

This manual process is slow, error-prone, and difficult to scale across multiple product categories.

The challenge was to design a product that could:

• reduce manual analysis
• surface key insights quickly
• support strategic buying decisions
• feel intuitive to fashion industry users

[Discovery & Research]

To better understand the workflow of fashion buyers, I conducted:

• stakeholder workshops
• user interviews with industry buyers
• competitor analysis of existing buying tools
• affinity mapping to identify patterns in behaviour and pain points

The goal was to uncover how buyers currently plan seasonal purchases and where the biggest inefficiencies occur.

[Key Insights]

Research revealed several consistent challenges:

Spreadsheet fatigue: Buyers were spending days analysing large datasets in Excel before making purchasing decisions.
Limited visibility of patterns: While the data existed, it was difficult to quickly identify trends across categories, sizes, and seasons.
Time spent on analysis reduced creative thinking: Many buyers expressed frustration that data processing was consuming the time they would prefer to spend curating collections.

These insights shaped the direction of the product.

[Design Strategy]

Based on these findings, the design strategy focused on:

• transforming complex data into clear visual insights
• reducing manual decision-making steps
• creating a dashboard that surfaced the most important information first

Because the platform was targeted at fashion industry users, it was also important that the visual design felt aligned with the aesthetic sensibilities of that industry.

This required balancing a data-heavy product with a brand identity that resonated with fashion professionals.

[Product Design]

The final product centres around an AI-driven dashboard that translates complex buying data into actionable insights.

Key features include:

• visualised size curve recommendations
• seasonal demand forecasting
• simplified decision flows for purchase confirmation
• integrated digital moodboard and seasonal planning tools

The dashboard design focuses on clarity and hierarchy, allowing buyers to quickly assess product performance and purchasing recommendations.

Throughout the process I developed:

• low-fidelity wireframes
• high-fidelity prototypes
• interaction flows for testing
• interface components for developer handover

[Outcome]

The final platform streamlines the seasonal buying process by replacing manual spreadsheet analysis with clear visual insights.

This enables buyers to make faster purchasing decisions while focusing more time on the creative aspects of their role - curating collections and shaping seasonal strategy.

The project also established the visual identity and product foundations for the SeeStone platform as it continues to evolve.

[Reflection]

This project reinforced the importance of balancing data-heavy functionality with an interface that feels intuitive and visually aligned with its industry. Designing for fashion buyers required understanding both analytical workflows and the creative mindset of the user.