Inspiration
As a homeowner in Atlanta, I’d spent hours Googling repair tutorials, chasing contractor quotes, and forgetting filter replacements—frustration led me to build a tool that centralizes home care. I wanted something that spoke to fellow homeowners, blending practicality with the DIY spirit we value.
What it does
AI Home Maintenance Pro streamlines home upkeep: AI analyzes photos to diagnose issues & link to tutorials, seasonal checklists adapt to your climate, local pro matching with quote comparisons, and a home inventory to track assets, warranties & energy use.
How we built it
We started with user research (talking to 20+ homeowners) to map pain points. Frontend: React for intuitive UI matching home improvement brand aesthetics. Backend: Python/TensorFlow for AI image recognition; AWS for hosting; PostgreSQL for device/warranty data. Integrated Google Maps API for contractor geo-filtering.
Challenges we ran into
Calibrating AI image diagnosis for diverse home issues (e.g., subtle pipe leaks vs. obvious drywall cracks) took months of testing with real homeowner photos. Also, aligning seasonal checklists to 5+ climate zones across the US required precise ZIP-to-climate mapping logic.
Accomplishments that we're proud of
Our AI diagnostic tool hits 85% accuracy for common home issues; beta users reported 40% less time spent on maintenance planning; the seasonal checklist feature reduced missed tasks by 50% in user trials.
What we learned
User-centric design isn’t just about features—it’s about matching homeowners’ workflows (e.g., simplifying onboarding by pre-filling logical default data). We also learned that localizing tools (climate, contractor data) is make-or-break for adoption.
What's next for This project
We’re adding smart home device sync (e.g., HVAC usage data to auto-adjust maintenance reminders) and a pro verification system for even more trusted contractor matches. We’ll also expand regional climate data to cover more European markets.
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