The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
From an idea to a working Figma plugin. 🎨🚀
I've been working on something exciting: Acquire Color, a Figma plugin that extracts colors from images and turns them into structured color systems.
The idea was simple, but bringing it to life has been a learning experience.
I used AI to help me build it, and along the way, I experienced a few ups and downs.
The challenges:
Getting AI to understand my exact vision.
Refining the UI when the initial results weren't what I wanted.
Figuring out how to structure primitive and semantic color systems.
Debugging, iterating, and rethinking certain parts of the experience.
The wins:
Turning my idea into a working prototype.
Exploring Figma plugin development.
Learning to collaborate with AI more intentionally.
Developing a clearer vision of what the product should become.
One thing I've learned is that building with AI doesn't mean everything happens automatically.
You still need to think through the problem, make decisions, guide the process, and refine the output.
I'm still improving Acquire Color, but seeing the idea take shape is a win in itself.
A little progress is still progress. And I'm enjoying the process of becoming a better designer and builder.
What has your experience been like building with AI?
#Contra #BuildInPublic #ProductDesign #Figma #AI
Title: SmartAI Factory: AI-Powered Industrial Machine Monitoring
Factory downtime is expensive, and most teams only find out about a problem after a machine fails. For my Final Year Project, I built SmartAI Factory, a platform that lets teams see problems coming and fix them early.
It streams live temperature, vibration, and current data from industrial machines to a real-time dashboard that flags anomalies as they happen. An Autoformer-based AI model then forecasts machine behavior 15, 30, 45, and 60 minutes ahead, each with a confidence score.
What I built:
Live monitoring dashboard with anomaly-marked charts and status badges
AI forecasting across 4 time horizons
Secure device onboarding: unknown machines stay Pending until an admin approves them
Per-machine alert thresholds with in-app and email notifications
Role-based access, user management, and light/dark mode
My role: Full-stack development, UI/UX design, and AI model integration, end to end.
Result: A complete predictive-maintenance workflow, from onboarding a device to getting an alert, in one clean interface.
Open to freelance work on AI dashboards, IoT monitoring systems, and full-stack web apps. Let's talk.
