This is a submission for the GitHub Finish-Up-A-Thon Challenge.
https://dev.to/michael_groover_1fe970a66
Building Fix-It Fast AI has been a journey of continuous improvement. What started as a simple troubleshooting concept evolved into an AI-powered appliance and HVAC troubleshooting platform designed to help homeowners and maintenance professionals solve problems faster.
This submission highlights the progress, challenges, lessons learned, and improvements made while transforming the project into a more capable and practical tool.
I built Fix-It Fast AI, an AI-powered appliance troubleshooting platform that helps homeowners and maintenance professionals diagnose appliance and HVAC problems using AI and photo analysis.
The goal was to make repair information easier to access while reducing the frustration of searching through manuals and forums.
The platform combines AI assistance, troubleshooting guides, and a growing repair knowledge base containing hundreds of repair articles.
Live Application:
https://fix-it-fast-ai.madethis.ai
The application can help diagnose common appliance issues, provide troubleshooting guidance, and assist users through an AI-powered repair assistant.
Screenshots of the application are included below.
Fix-It Fast AI started as a much smaller troubleshooting tool.
In the beginning, the project focused on basic repair guidance and a limited knowledge base. As development continued, several challenges appeared. Equipment identification was not always accurate, OCR label recognition needed improvement, and AI responses needed more context to provide better troubleshooting advice.
To improve the platform, I continued expanding the repair database, improving appliance recognition, adding AI-powered troubleshooting assistance, and testing with real-world maintenance and appliance problems.
One of the biggest improvements was growing the knowledge base from a small collection of repair information to more than 540 repair articles covering HVAC systems, washers, dryers, refrigerators, dishwashers, stoves, water heaters, and other common household equipment.
More than 540 repair and troubleshooting articles covering HVAC systems, appliances, electrical systems, plumbing, water heaters, refrigerators, washers, dryers, dishwashers, stoves, and maintenance topics.
What started as a simple repair helper gradually evolved into a much more capable AI-powered troubleshooting platform designed to help homeowners and maintenance professionals solve problems faster and more confidently.
GitHub Copilot and other AI-assisted development tools helped speed up the development process by making it easier to brainstorm solutions, test ideas, and improve features.
While AI tools were helpful, the most valuable part of the project came from real-world maintenance experience. Years of troubleshooting HVAC systems, appliances, and equipment helped shape the repair guidance and troubleshooting logic used throughout the platform.
The combination of practical field experience and AI-assisted development allowed Fix-It Fast AI to grow from a simple concept into a useful troubleshooting tool. The experience taught me that AI works best when combined with real knowledge and hands-on problem solving.
Here are some pictures of this in action
During testing, I found that combining a photo with a description of the symptoms produced the most accurate results. This mirrors real-world troubleshooting, where both visual inspection and symptom information help narrow down the root cause.
One of the newest additions to Fix-It Fast AI is the Wiring Scan feature. Users can upload a photo of electrical components, burned terminals, disconnects, HVAC wiring, or appliance connections. The AI identifies components, flags hazards, suggests likely faults, and provides technician-style troubleshooting guidance. This feature was added as part of the effort to transform the project from a simple repair helper into a more complete diagnostic platform.
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