Retail AI Agents
Explore AssistantProfit & Cash
Continuously evaluates pricing opportunities, responding to demand while protecting margin within configured guardrails.
Keep Fresh. Keep Moving. Keep Margin.
Perishables Intelligence for Decisions That Cannot Wait.
Ithina connects demand, inventory, shelf and operational signals to help teams predict what will sell, identify where waste or stock-out risk is building, and coordinate the right action before value is lost.
Challenges
The Perishables Challenge
Perishable inventory has a moving deadline. Demand can shift, products age, and shelf availability can change throughout the day. Static replenishment rules and periodic checks make it difficult to see where inventory is becoming a waste risk or where availability is likely to suffer. Ithina brings these signals together so teams can understand the condition of inventory, anticipate what happens next, and intervene while there is still time to recover value.
Solution
Turn Perishable Signals Into Timely Decisions.
Ithina turns live operational signals into coordinated action across the perishable inventory lifecycle.
Capture signals from cameras, handheld mobile devices, inventory systems, POS and connected store environments to build a current view of product availability, shelf conditions and inventory movement.
The Reasoning Layer evaluates demand, consumption, inventory position and risk to determine what matters now and what action is most likely to protect availability and reduce waste.
The Orchestration Layer coordinates specialised Agentic AI Assistants, workflows, enterprise systems and connected devices to move decisions into execution.
Outcomes return to the intelligence layer, creating a continuous feedback loop that helps improve future recommendations, replenishment decisions and operational performance.
Capabilities
Capabilities
Demand-Aware Forecasting
Evaluate historical consumption, demand patterns and operational signals to anticipate what is likely to move before inventory becomes a problem.
Fresh Inventory Intelligence
Maintain a dynamic view of perishable inventory across locations, helping teams distinguish between available stock and inventory that is actually positioned to meet demand.
Waste Risk Detection
Identify products and inventory positions showing signs of excess or declining demand so teams can act earlier through replenishment, movement or commercial interventions.
Stock-Out Risk Prediction
Detect situations where expected demand may exceed available inventory, giving teams time to intervene before availability is affected.
Intelligent Replenishment
Combine demand, inventory and operational context to recommend replenishment quantities and timing instead of relying only on static thresholds.
Shelf Availability Intelligence
Use shelf-level observations and product signals to identify empty or understocked positions and connect them with the wider inventory picture.
Inventory Prioritisation
Help teams focus attention on the products and locations where the operational or financial impact of inaction is highest.
Closed-Loop Optimisation
Track what happened after an action and feed the outcome back into the intelligence layer, continuously improving decision quality over time.
How It Works
Perishable Signals To Timely Action.
Define the Inventory Context.
Set the operational context for products, locations, demand patterns, inventory levels and replenishment requirements.
- Product and inventory data
- Historical consumption
- Location-level requirements
Capture What Is Happening.
Combine operational data with shelf-level observations to create a current picture of product availability and movement.
- Cameras and handheld mobile devices
- POS and inventory systems
- Shelf and product conditions
Reason About What Happens Next.
Maestro evaluates multiple signals together to identify demand changes, inventory risk and potential waste before they become costly operational issues.
- Expected demand
- Available inventory
- Consumption patterns
- Risk and operational context
Coordinate the Right Action.
The Orchestration Layer brings the relevant Agentic AI Assistants, systems and workflows together to determine what needs to happen and in what sequence.
- Recommend replenishment
- Prioritise inventory movement
- Trigger workflows
- Notify responsible teams
Execute, Measure, Learn.
Actions move into the physical operation, while the resulting outcome returns to Maestro as feedback for the next decision.
Ithina Maestro
The Reasoning Layer Behind Perishable Operations.
Ithina Maestro sits between operational data, Agentic AI Assistants, enterprise systems and connected devices.
Its Reasoning Layer understands what is happening across the operation, evaluates what matters and determines what should happen next.
Its Orchestration Layer coordinates the right agents, systems and workflows to move that decision into action.
- ReasoningWhat should happen?
- OrchestrationWho or what needs to act, and in what sequence?
- ExecutionMake it happen.
- FeedbackWhat happened, and what can be learned?
Use Cases
Six Decisions That Protect Fresh Inventory.
Predict Demand Before It Peaks
Identify changing consumption patterns early and prepare inventory before demand creates availability pressure.
Prevent Perishable Stock-Outs
Surface products at risk of running out and prioritise the locations where intervention matters most.
Reduce Excess Before It Becomes Waste
Detect inventory positions where supply is running ahead of expected demand and support earlier corrective action.
Optimise Replenishment
Recommend when and how much to replenish using demand, inventory and operational context together.
Improve Shelf Availability
Connect shelf-level observations with inventory signals to identify products that are unavailable where customers need them.
Protect Margin Across Locations
Prioritise actions based on operational and commercial impact, helping teams reduce avoidable waste while maintaining availability.
Business Impact
Better Fresh Inventory. Faster Decisions. Stronger Margins.
3×
Faster Execution
10–20%
Revenue Uplift
81%
Consumer Influence Through Consistent Pricing & Presentation
Reduce Waste
Act earlier on excess inventory and changing demand before products lose value.
Improve Availability
Identify stock-out risk sooner and coordinate replenishment where it matters.
Maximise Inventory ROI
Put working capital behind the products, locations and quantities most likely to generate value.
Demand Accuracy
Improve the quality of inventory decisions with a more contextual view of demand.
Waste Reduction
Reduce avoidable losses caused by excess, delayed action and poor inventory positioning.
AI Solutions
AI That Understands the Retail Floor.
Purpose-built AI Assistants help retail teams move from scattered operational signals to clear, actionable decisions. Each Assistant is built around a specific operational decision, not a generic AI use case.
Retail AI AgentsExplore AssistantPlanogram
Monitors shelf compliance against the intended layout, identifying gaps, misplacement and rotation issues.
Retail AI AgentsExplore AssistantPromotion
Coordinates campaigns, allocates space and validates that promotions don't erode margin.
FAQ
Frequently Asked Questions
Ithina Perishables Intelligence helps organisations understand demand, inventory and shelf-level conditions so they can make faster decisions around availability, replenishment and waste.
Ithina identifies changing demand and inventory risk earlier, helping teams act before excess inventory turns into avoidable waste.
Yes. The intelligence layer can evaluate expected demand against available inventory and surface situations where availability may come under pressure.
Ithina can work with operational signals such as POS, inventory data, cameras, handheld mobile devices, shelf observations and connected systems, depending on the operating environment.
Agentic AI Assistants handle specialised operational decisions, while Maestro's reasoning and orchestration layers coordinate those agents with enterprise systems, workflows and connected devices.
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