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This is a fintech platform and landing page built to bridge algorithmic trading with user-friendly web interfaces. Developed using Lovable, the system showcases real-time market scanner metrics and highlights automated MT5 signal integration for hands-off trade execution.
"Strong concept. For a fintech platform like this, presenting real-time data clearly while keeping complex trading workflows easy to understand is what builds user confidence.
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
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Built not just to save ideas, but to bring users back to the product ✨
Most note taking apps solve only one problem: helping users capture something quickly.
But the real growth challenge comes later.
Users collect voice notes, images, links, and unfinished thoughts, but rarely return to them. The archive keeps growing while its value barely increases.
That is why we built the experience around one retention loop:
Capture. Connect. Rediscover. Continue.
Continue Thinking brings users back to unfinished ideas.
Connected Ideas reveals relationships between notes, voice recordings, and references.
Resurfaced Thoughts brings older content back at the right moment.
As a result, the product works not as passive storage, but as a living personal knowledge system that creates a real reason to return.
Full case study ↓
#MobileAppDesign #UIUXDesign #IdeaCaptureApp #VoiceNotesApp #NotesApp #KnowledgeManagement #ProductDesign #RetentionDesign #GrowthDesign #UXDesign #iOSDesign #SecondBrainApp
I like that the focus is on retention, not just capture. The products people keep using are usually the ones that help users rediscover value, not just store more information.
Launch pricing is coming to an end.
Wire Me is currently available for $39, but it'll be $69 starting next week.🚀
Thanks for all the support so far :)
Live preview
Just checked it out great job, man!
Built this one for an e-commerce customer behavior project - 18,000+ customers, segmented using RFM (Recency, Frequency, Monetary) analysis.
The interesting part wasn't the segmentation itself, it was what it revealed: nearly 22% of customers were "at risk" of churning, and most businesses wouldn't know that until those customers had already stopped buying.
This is the kind of insight that's usually sitting in your order data already, it just needs the right lens. Happy to take a look at your numbers if you're curious what's hiding in yours.
Tools used: Power BI, SQL, Python (Pandas, Scikit-learn for clustering)
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