CASE STUDIES
AI Video Analytics for Error-Free Put-to-Light Operations
The client
A leading logistics and supply chain provider handling large-scale e-commerce fulfilment across multiple facilities. With high daily throughput, accuracy and speed at Put-to-Light bagging stations are critical to meeting service commitments.
The Challenge
Put-to-Light stations rely heavily on manual accuracy. Even a single mis-bagged parcel can disrupt downstream sorting, delay dispatches, and inflate operational costs.
The client needed a solution that could:
- Monitor Put-to-Light workstations automatically.
- Detect human errors in real time.
- Alert operators instantly.
- Record incidents for audits and training.
- Integrate seamlessly with existing CCTV systems.
Manual checks weren't fast enough, consistent enough, or scalable across high-volume sites.
The Solution
An AI-driven video analytics system was deployed to monitor each Put-to-Light wall. The solution uses the client’s existing CCTV network and edge devices to analyze video feeds in real time, detect errors, and trigger immediate alerts. Using AI and deep learning, the system:
-Tracks parcel scans and bag selections.
-Identifies incorrect placements instantly.
-Alerts operators on the spot.
-Logs every event with timestamps and images.
-Provides dashboards for supervisors and quality teams.
All analytics run locally for low-latency responses, and insights are streamed to the central console for visibility across all stations.
Key Features and Benefits
Real-Time Error Detection
Instantly identifies mis-bagged or mis-placed items.
Operational Accuracy
Reduces manual oversight and improves first-time-right performance.
Seamless Integration
Works with existing CCTV cameras — no additional infrastructure needed.
Faster Response
Edge processing ensures immediate alerts to station operators.
Complete Traceability
Every error is logged with images and timestamps for audits and training.
Scalable Model
Easily deployable across additional Put-to-Light stations and facilities.
Impact
- The AI video analytics system transformed Put-to-Light operations from reactive checks to proactive quality control.
- Operators corrected mistakes instantly, manual verification dropped significantly, and the overall speed and accuracy of the bagging line improved.
- The success of this deployment demonstrates how intelligent video analytics can eliminate human error in fast-paced logistics environments, improving throughput, reducing costs, and elevating service reliability.
Cut Sorting Errors and Speed Up E-com Fulfilment
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