Demand Forecasting
Turn sales history and outside signals into a store-level forecast the planner can accept or adjust.
- Signal-driven adaptive forecasts
- What-if scenario simulation
- SKU-by-store decision views
Balance inventory across every store
Reduce inventory variance while cutting lost sales, spoilage, and safety stock. AI agents forecast demand by SKU and store, draft restock orders for buyer approval, and flag anomalies early.
Store 031 · SKU-2210
Storm warning
+31%
- Heavy rain alert
- 3-day lead time
- Nearby surplus found
Move stock before demand peaks
Weather scenario selected. Storm warning. Four-week demand +31%. Recommended action: Move stock before demand peaks. Transfer 240 units to Store 031.
Let's map where empty shelves cost you most
Your planners stay in charge the whole way. Try one category or store cluster first, or build on a model you already run.
01Discovery
We check your sales data and pick the products where a better forecast matters most.
Use cases that protect margin across the network
Agentic Inventory Management
Catch stockout risk early and draft the transfer or order, so the buyer only has to approve.
- Stockout-risk detection
- Transfer and order recommendations
- PO approval-flow write-back
Retail Anomaly Detection
Find the same register pattern across stores, check the camera, and hand the case to the right manager.
- POS anomaly detection
- Cross-store pattern comparison
- Camera cross-validation
Store Intelligence
Give every store one ranked list of what to do next, each item owned and dated.
- Store-level priority view
- Footfall and demand context
- Action queue by owner
Trusted with the numbers behind the plan
100+ markets
An AI hub became the global operating model
A prioritized use-case portfolio with a shared data and governance blueprint.
Confidential client80% less analyst time
Data requests moved from analyst queue to agent
An agent wrote SQL and Python, checked its own work, and asked a person when unsure.
We make sure a buyer approves every order
Human approval
Buyers approve every transfer and purchase order.
Explainability
Forecast movement stays connected to the signals that caused it.
Logging & tracing
Forecast, recommendation, approval, and outcome form one record.
Model routing
Workloads use the appropriate forecast or agent path.
Quotas
Scenario and agent activity stays inside operating and spend limits.
State management
Inventory and decision state stays current across planning cycles.
More resources
The Philippine AI Report: Executive Brief
AI adoption is widespread. Scaling it is the harder task. Explore the leadership decisions, organizational barriers, and practical priorities that help Philippine businesses move beyond pilots.
The Philippine AI Report
A national benchmark of AI adoption across the Philippines. Explore the research, the policy and talent landscape, and comparisons with ASEAN peers—with a roadmap for moving from experimentation to scaled execution.
Scaling AI Across the Filipino Retail Value Chain
A closer look at AI across Philippine retail. Discover opportunities in demand forecasting, logistics, back-office operations, and customer experience—and the barriers retailers must address to put them into practice.
