The 24 Vision System Dashboard is a modern, desktop-first platform built for automotive teams to efficiently manage, tag, and analyze high volumes of component imagery. Designed with speed, clarity, and precision in mind, it brings together advanced filtering, intuitive tagging, and a clean, grid-based interface that mirrors real-world workflows.
By combining engineering-grade functionality with a refined, approachable design language, the tool empowers teams to make faster, more accurate decisions at every stage of vehicle design and production.
Problem
Automotive manufacturers and design teams work with thousands of high-resolution component images during vehicle design, prototyping, and quality control. These assets often come from multiple sources, camera angles, and stages of production. Without a centralized and intuitive tool, the process of categorizing, comparing, and validating images becomes slow, inconsistent, and prone to human error. This can lead to delays in approvals, miscommunication between teams, and increased production costs.
Insight
Teams don’t just need to store and label images — they need a visual-first workflow that reflects the way they physically work with components in a design studio or production environment. A good tool should make large datasets feel approachable, allow for fast filtering and precise tagging, and give instant context to every image without overwhelming the user.
Solution
The 24 Vision System Dashboard is a desktop-first web application designed to transform how automotive teams manage and interact with component imagery.
Key features include:
Image Selection Interface — A clean, grid-based gallery optimized for rapid scanning, comparison, and selection of assets.
Smart Tagging Tools — Intuitive, color-coded selection boxes that allow users to identify specific components and link them to triggers, conditions, and operational outcomes.
Advanced Filtering — Search and sort by class, item group, camera angle, and other metadata to quickly locate specific images.
Design Approach
Visual Hierarchy — A minimalist, high-contrast layout keeps attention on the imagery, with controls positioned where users naturally expect them.
Consistency — Reusable UI components and a unified icon set ensure predictability across all workflows.
Interaction Patterns — Tagging and filtering tools were designed to work with minimal clicks, reducing repetitive tasks and decision fatigue.
Color Coding — A carefully chosen palette was used for tagging states to help users quickly distinguish between categories without needing to read labels.
The interface balances a professional, engineering-ready look with enough visual refinement to feel modern and approachable.
Research & Discovery
Conducted interviews with engineers, designers, and quality control teams to map their current workflows.
Observed how physical part inspections were done in real environments to replicate that speed and clarity in a digital format.
Audited existing tools to identify bottlenecks and recurring UI frustrations.
Wireframing & Prototyping
Created low-fidelity wireframes to explore layout and filtering logic.
Developed interactive prototypes in Figma to test tagging and filtering speed.
Iterated on the selection box interaction to make it feel natural and responsive.
Testing & Refinement
Ran usability sessions with target users to validate flow efficiency.
Adjusted color usage and spacing to reduce visual fatigue over long work sessions.
Introduced quick action shortcuts based on power-user feedback.
Outcome & Results
The new 24 Vision System Dashboard reduced the average image selection and tagging time by over 40%, giving teams more bandwidth to focus on problem-solving rather than admin work. The tool eliminated redundancy in asset reviews, improved communication between design and QA teams, and brought a unified visual language to the entire process.
By integrating advanced filtering, visual tagging, and context-aware interfaces into one platform, the system turned a fragmented, manual workflow into a streamlined, insight-driven experience.
