Aichor.ai is a platform designed to help teams build, deploy, and monitor machine learning models more intuitively through a unified web interface. My task was to design and engineer the entire UI layer — building a scalable design system and implementing it in production using Next.js, Tailwind CSS, and shadcn/ui.
Case Study
Aichor - Building a next Gen AI Platform
Design Engineering
Brand Identity Design
60
2022 - Present
The challenge was to turn Aichor’s complex product vision into a cohesive coded design language that worked seamlessly for both designers and engineers. I needed to build consistency without limiting flexibility, ensuring performance, accessibility, and unity across all interface elements.
I started by identifying key user flows and refining the visual structure through quick prototypes. Once the foundation was clear, I brought the designs to life using Next.js, Tailwind, and shadcn/ui. Working iteratively, I documented, tested, and refined each component to ensure design and development stayed perfectly aligned.
The process began with exploring visual themes and layout systems that aligned with the brand’s AI focus. I collaborated closely with designers and developers to translate these ideas into reusable components using Tailwind CSS and Framer Motion, ensuring consistency, responsiveness, and smooth interactions across the app.
The focus was on building a robust foundation before expanding to full pages—starting with atomic components, then assembling them into patterns and templates. Design and development ran in parallel, with constant validation through coded prototypes.
Execution centered on speed and reusability: I defined tokens and themes early, built out base components, and progressively layered complexity, ensuring each element was responsive and accessible.
As components matured, I integrated them into the Next.js structure, connecting data and state logic to make the UI fully functional.
The design system became the backbone of the entire interface. It
unified colors, typography, spacing, and motion through Tailwind
tokens, while shadcn/ui provided a flexible architecture for
component variants. Each element—whether designed or coded—followed
shared principles of clarity, consistency, and accessibility. The
result was a design language that looked cohesive in Figma and
behaved identically in production.
Every pixel is built with user's feedback in mind
Every feature in AIchor is shaped by real feedback, helping us build a tool people actually enjoy using every day.
"Boosted our team's efficiency instantly."
"Smart, fast, and incredibly intuitive."
"Game-changer for daily productivity."
The result was a scalable, production-ready UI that accelerated development, improved visual harmony, and strengthened collaboration between designers and engineers. The system now supports rapid iteration and a consistent experience across all of Aichor’s machine learning tools.