Client
Private Client
Timeline
Custom build & handoff
Built by
thehsquares
Project Overview
An AI-powered vision system that detects and segments objects in camera feeds, tracks them across frames, and surfaces inventory insights — built for private operational use in retail and warehouse environments.
The Challenge
Manual inventory checks were slow, error-prone, and couldn't scale across locations. The client needed automated object detection and tracking that could identify products, monitor shelf levels, and flag discrepancies without a public web product.
Our Solution
We built a detection-and-segmentation pipeline with multi-object tracking, custom class training for their inventory SKUs, and analytics outputs for stock visibility — delivered as a private system integrated with their internal workflows.
Our Approach
Use-case Mapping
Defined detection classes, camera angles, and inventory KPIs for warehouse and shelf monitoring.
Model & Tracking Build
Implemented detection, segmentation masks, and frame-to-frame tracking for consistent object IDs.
Analytics Handoff
Connected vision outputs to inventory reports and alerting logic for the client's ops team.
Services Delivered
Key Deliverables
- Custom-trained detection model
- Segmentation & tracking pipeline
- Inventory event analytics module
- Internal integration documentation
- Model retraining guide
Key Features Built
- Real-time object detection and instance segmentation
- Multi-object tracking across video frames
- Inventory count and shelf-level monitoring
- Configurable alerts for stock anomalies
- Private deployment for internal operations only
Impact & Results
- Automated inventory visibility without manual shelf audits
- Scalable detection pipeline adaptable to new product classes
- Delivered for private ops — no public live site required
- Foundation for warehouse and retail analytics expansion
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