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
Back to feedPost
I just open-sourced a pure Python trading engine with 261 automated tests.
I built it to prove if trading strategies actually work (most of them fail). The result is a system with zero dependencies, no lookahead bias, and strict error handling.
I don't just write scripts that work once. I build systems that don't break in production.
Need a web scraper, bot, or API integration? My DMs are open.
261 tests on a zero dependency engine is SERIOUS discipline, id be curious which strategy failed hardest
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
AI Automation Platform — SaaS Dashboard & Mobile App UI Design
✨ Smarter Workflows, Powered by AI
A futuristic AI automation platform concept that brings workflows, intelligent assistance, and performance analytics into one digital workspace. The design combines a deep navy interface, electric blue accents, and immersive orbital visuals to make complex automation tools feel intuitive and accessible.
Special attention was given to:
• Immersive dashboard composition with glowing orbital graphics and futuristic visual elements
• AI assistant interface featuring voice interaction controls, animated-inspired waveforms, and quick actions
• Organized workflow cards, automation management, and real-time activity feeds
• Clear analytics widgets with progress indicators, performance charts, and automation status controls
• Responsive desktop and mobile layouts with consistent dark-mode styling and streamlined navigation
The result is a modern SaaS experience that balances futuristic aesthetics with practical usability, giving users a clear view of their workflows, AI tools, and automation performance.
Worth a read if you're building AI support for e-commerce.
UI Trax gets the hard parts right: answers grounded in real store data, order lookups only after verification, a guard on every reply, and a clean handoff to humans with an AI summary.
Reliable AI agents come from architecture, not just prompts. This case study shows it.
#AIAgents #Ecommerce #CustomerSupport #AI
Check it out
The verification step before an order lookup caught my attention. For patient intake, I would similarly verify identity before retrieving records and limit the handoff summary to what staff need. I would also flag uncertainty rather than presenting an unverified summary as fact.
Just published a new case study: UI Trax, an AI customer agent for online stores. 🚀
Most store chatbots either follow rigid scripts or make things up. I built one that does neither.
What it does:
• Answers from real store data (products, sizes, stock, prices) through tool calls, never from guesses
• Tracks orders only after verifying the customer's phone number
• Runs a guard on every reply that blocks invented links, discounts, policies and promises
• Hands off to a human with a one-line AI summary, then goes quiet when staff join
• Works on web chat and WhatsApp, in English and Roman Urdu
Built with Python and Gemini, and tested against 1,500+ conversation scenarios.
Full breakdown with screenshots is in my portfolio. Open to projects building AI support agents for e-commerce, clinics, real estate and service businesses.
Great work on the case study!
