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Developed a Software Discovery Bot using Python and Streamlit to automate software lookup and inventory management. The application allows users to search software packages, retrieve metadata from centralized repositories, and generate reports for deployment and compliance tracking. Designed to improve software packaging workflows, reduce manual effort, and streamline IT asset management processes.
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Would have shared a free one that I built if you were a Rive user😂
Issue 01 of The Leak Report is out.
Most AI advice aimed at small businesses is written for companies that do not look like yours. It assumes a data team, a backlog of clean records, and someone whose job is to own the rollout.
In a 5–50 person service business, the person evaluating AI is usually also the person quoting jobs, chasing payment, and covering for whoever is on leave. That is not a smaller version of an enterprise problem. It is a different problem.
Inside: the four workflows that quietly leak money, the one distinction that decides whether a project works, four tests a first project has to pass, and what it costs — published, because a quote request wastes your time.
It is deliberately unexciting. The most valuable thing in these pages is a test that sends some projects back.
Highly professional AI for business integration! Explaining machine learning models through clean UI is brilliant.
I engineered a custom desktop application for the ClubGG poker platform, focused on automation, real-time table interaction, and intelligent seat recognition.
The application dynamically detects active poker tables, identifies player positions, adapts to different table layouts (3-max, 5-max, and 6-max), and provides a responsive interface for interacting with the game environment in real time.
The project required combining frontend development, desktop application engineering, UI automation, DOM inspection, coordinate mapping, and performance optimization to create a smooth and highly responsive user experience.
What I Built
• Dynamic poker table detection
• Automatic seat recognition and positioning
• Multi-table layout support (3, 5 & 6 players)
• Responsive desktop interface
• Real-time game state interaction
• Coordinate & screen mapping system
• High-performance automation logic
• Clean, scalable application architecture
Technologies Used
Electron
JavaScript / TypeScript
Node.js
HTML5 & CSS3
Desktop Automation
DOM Inspection
Real-Time UI Rendering
Performance Optimization
Project Highlights
✔️ Automated table recognition
✔️ Intelligent seat positioning system
✔️ Multi-layout compatibility
✔️ Fast and responsive desktop application
✔️ Production-quality architecture
✔️ Optimized for reliability and scalability
This project demonstrates my expertise in desktop application development, automation engineering, browser technologies, and building complex software that interacts with real-time systems while maintaining speed, accuracy, and reliability.
GREAT JOB 👍