Project Scope
MARKET: Australia |
INDUSTRY: Retail |
CATEGORY: AI Productivity Tools |
TAGS: #RetailAI #SmartStore #SmartWarehouse |
The Context: Moving Beyond Manual Retail Operations
Retail operations often rely on manual processes across warehouses and stores—limiting speed, accuracy, and visibility.
Mathews Liquor, an Australian retail chain, aimed to modernize its operations by transitioning from labor-intensive workflows to an AI-powered, data-driven system.
The goal was to improve operational efficiency, reduce errors, and gain real-time visibility across warehouse and in-store environments—without increasing staffing levels.
The Challenge: High Effort, Limited Visibility, and Reactive Decisions
The existing operational model created multiple constraints:
- Labor-intensive workflows: Manual pallet counting and verification required significant time and staffing
- High error rates: Inconsistent checks led to packing errors and limited traceability
- Lack of real-time insights: No visibility into inventory movement, customer behavior, or anomalies
- Reactive operations: Decisions were based on delayed or incomplete data
The Solution: AI Productivity Tools Across Warehouse and Store
Success Software implemented a suite of AI-powered tools to automate workflows and enable real-time operational intelligence.
Smart Warehouse: Automated Inventory & Workflow Control
A system for real-time inventory tracking and operational accuracy
- AI-powered SKU detection and pallet counting
- Automated updates to warehouse management systems (WMS)
- Image-based verification for auditability and accuracy
- Reduced manual handling and faster processing
Smart Store: Customer & Product Intelligence
A system for understanding in-store behavior and optimizing performance.
- Customer tracking, footfall analysis, and movement patterns
- Heatmaps to evaluate store layout effectiveness
- Product interaction tracking and anomaly detection
- Data-driven insights for merchandising and store optimization
Unified Dashboards: Real-Time Decision Intelligence
A centralized view across warehouse and store operations.
- Real-time monitoring of operational performance
- Alerts for anomalies and operational issues
- Consolidated insights across locations and workflows
- Faster, more consistent decision-making across teams
The Result: Faster Operations, Lower Costs, and Better Decisions
The implementation delivered measurable improvements across operations:
- 50% reduction in staffing needs while increasing throughput
- Pallet processing time reduced from 2 hours to 45 minutes
- Store layout efficiency improved from 50% to 80% using behavioral insights
More importantly, Mathews Liquor transitioned from reactive operations to a proactive, data-driven retail model.
Delivery Model and Execution
Team Structure (18 specialists)
- 1 Project Lead
- 1 DevOps Engineer
- 2 Technical Architects
- 1 Business Analyst
- 6 Software Engineers (BE/FE)
- 4 AI Engineers
- 3 QA Engineers
Approach
- Full implementation across warehouse and store systems
- Integration with existing platforms (WMS and store operations)
- Continuous optimization based on real-time data
Technology Stack
- AI & Processing: Python, NVIDIA DeepStream, NVIDIA Triton
- Platform: Vizion AI Core
- Cloud & Infrastructure: Azure
- Database: PostgreSQL
- Streaming & Messaging: RTSP, RabbitMQ
- Tools: GitLab, Jira, Microsoft Teams
Ready to move faster? Let’s build what works.
Ready to move faster? Let’s build what works.
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Ready to move faster? Let’s build what works.
