AI Computer Vision Parts Marketplace
Eliminating manual part identification errors with a mobile-first marketplace powered by computer vision
The Challenge
High error rate in manual part identification led to costly product returns and customer dissatisfaction
Customers struggled to match worn or unlabelled parts to correct SKUs in a catalogue of thousands
Existing search relied on text input — ineffective for users who cannot identify part names
Return processing cost eroded margins on high-volume, low-margin automotive consumables
Mobile experience was an afterthought; most purchasing happened on desktop despite mobile traffic
Our Solution
Built a mobile-first iOS/Android app with integrated camera-based part identification flow
Trained a computer vision model on curated automotive parts imagery for high-accuracy SKU matching
Designed a three-step UX: Photograph part → AI analysis → Exact SKU match with one-tap purchase
Integrated the CV model with real-time catalogue search to return confidence scores and alternatives
Implemented a feedback loop where mis-matches were reviewed and used to retrain the model
Built an analytics dashboard showing identification accuracy, return rates, and conversion by part category
Measurable Impact
94%+
Computer vision model outperformed manual search accuracy across all tested part categories
Significant drop
Correct first-time identification reduced wrong-part returns materially
3× lift
Camera-first mobile experience tripled conversion versus the old text-search flow
Continuous
Feedback loop improved model precision with each production cycle
"Returns were eating our margins. SystimaNX built something our customers love using — and the returns problem is practically solved."
Technology stack
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