Rig-Engineer

The intelligent hardware auditor for peak software performance.

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Inspiration

Many engineering applications technically meet system requirements on paper, yet still fail to run smoothly in real life.
A system may have 32 GB of RAM, but if only 5 GB is actually free due to background processes, heavy engineering software can crash, freeze, or perform poorly.

As engineering students, we constantly faced this problem ourselves. We wanted a way to understand how ready a system truly is to run demanding applications — not theoretically, but in practice.
That need became the inspiration for Rig-Engineer.

What it does

Rig-Engineer analyzes a computer’s real-time system readiness for engineering applications.

Instead of only checking theoretical hardware specs, it:

  • Evaluates actual available resources
  • Detects performance bottlenecks caused by background usage
  • Provides insight into whether a system can realistically run demanding software smoothly

In short, Rig-Engineer answers the question:
“Is my system actually ready to run this application right now?”

How we built it

Rig-Engineer is a desktop application built with a strong backend focus.

  • We collect live system data directly from the user’s computer
  • CPU and RAM information is dynamically tested and analyzed
  • GPU data was initially collected using the GPUtil library

When we discovered that GPUtil did not properly detect AMD and Intel GPUs, we adapted our approach and:

  • Retrieved GPU data directly from Windows via PowerShell
  • Integrated this data into our backend to ensure accurate hardware detection

This hybrid approach allowed us to overcome library limitations and ensure reliable system analysis.

Challenges we ran into

  • Hardware detection libraries not supporting all GPU vendors
  • Learning backend development for a desktop application from scratch
  • Working under tight hackathon time constraints
  • Designing a system that reflects real-world performance, not just specs

Overcoming these challenges required fast learning, experimentation, and adapting our technical approach quickly.

Accomplishments that we're proud of

  • Building a fully working and useful application in our first hackathon
  • Creating a tool that solves a real problem we personally face
  • Successfully pulling dynamic system data from the user’s machine
  • Implementing CPU and RAM performance testing ourselves
  • Designing a solid backend despite having limited prior experience

We are especially proud of the backend architecture and the fact that Rig-Engineer is something we can genuinely use in real life.

What we learned

  • Desktop application backend development
  • Collecting and processing system-level data
  • Testing CPU and RAM performance dynamically
  • Working with OS-level tools like PowerShell
  • Problem-solving under pressure in a hackathon environment

This project significantly improved our confidence and technical skills.

What's next for Rig-Engineer

We plan to continue developing Rig-Engineer by:

  • Supporting more engineering and professional software
  • Expanding performance and stress testing capabilities
  • Improving system readiness scoring
  • Continuously updating the application based on real-world use

Our goal is to turn Rig-Engineer into a tool that can be widely used in the engineering world.

Built With

  • git/github
  • gputil
  • json
  • psutil
  • pyqt6
  • python-3.10+
  • setuptools
  • speedtest-cli
  • vs-code
+ 8 more
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