Demand forecasting and replenishment
Forecast at store and SKU level, identify risk, and draft replenishment actions for planner approval.
- Store and SKU forecasts
- Weather and payday scenarios
- Planner-approved revisions
Every store signal should lead to a better next move
Protect availability and give store teams time back. Swarm connects demand, inventory, store conditions, and customer conversations so retail teams can see what changed, decide what matters, and act while the opportunity is still live.
Retail operations
Start with the store decision that costs you most
Define the business case before choosing the model. Start with one workflow, agree what success looks like, and connect it to the systems and people who own the outcome.
01Discovery
Choose one category or store cluster. Trace the cost of stockouts, manual shelf checks, or unanswered service requests before selecting the pilot.
Four operating loops worth connecting
Store and shelf intelligence
Detect shelf gaps, queue conditions, and operational exceptions from existing visual infrastructure.
- Image-based shelf checks
- Stock and planogram evidence
- Assigned store actions
Customer and tenant service agents
Resolve routine questions and transactions, then escalate complex requests with useful context.
- Grounded product answers
- Availability and order context
- A clear human handoff
Content and offer personalization
Create on-brand variations and match the next message or offer to customer and store context.
- Consented customer segments
- Stock-aware offer ranking
- Campaign approval before release
Built on work already delivered
Selected work across document, analytics, and operational systems. These examples include adjacent industries; their results describe the linked engagement, not a forecast for your business.
We make sure your teams stay in control of every store action
Human approval
Buyers approve replenishment and pricing changes. The system prepares the action and its supporting evidence.
Consent boundaries
Customer messages and offers respect consent, channel preferences, and the purpose for which data was collected.
No facial recognition
Shelf and queue monitoring focuses on operational conditions, with privacy boundaries agreed before deployment.
Logging & tracing
Record the inputs, checks, proposed action, and reviewer response so the team can reconstruct what happened.
Human escalation
Uncertain or incomplete cases go to an assigned person with the context needed to take over.
Data retention
Agree what is stored, where it is processed, and when it is deleted before connecting production data.
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.
