---
title: "Shopping Cart and Inventory Management Agent Architecture"
source: Panaversity Learn Agentic AI
source_url: https://github.com/panaversity/learn-agentic-ai
licence: Apache-2.0
domain: agentic-ai
subdomain: panaversity-agentic
date_added: 2026-04-25
---

# Shopping Cart and Inventory Management Agent Architecture

Let’s design a **Shopping Cart and Inventory Management Agent** for an e-commerce platform. This agent will manage the shopping cart, track inventory in real-time, suggest actions based on stock levels, and notify staff or customers as needed. It will also allow staff to manually request inventory adjustments or promotions, optimized by the agent before approval. I’ll include additional automation features and identify where **Large Language Model (LLM) intelligence** can enhance functionality. First, I’ll outline the requirements, then detail the implementation using **event-driven architecture (EDA)**, **three-tier microservices architecture**, **stateless computing**, **scheduled computing (CronJobs)**, and **human-in-the-loop (HITL)**.

---

### Requirements for the Shopping Cart and Inventory Management Agent

#### Functional Requirements
1. **Shopping Cart Management**:
   - Allow customers to add/remove items to/from their cart.
   - Check real-time inventory availability before adding items.
   - Notify customers if items are low stock or out of stock with alternatives.

2. **Inventory Management**:
   - Track inventory levels across warehouses or stores using product IDs.
   - Suggest restocking, redistribution, or markdowns based on stock levels.
   - Notify staff of inventory issues (e.g., low stock, overstock).

3. **Action Approval and Execution**:
   - Allow staff to approve, modify, or reject suggested inventory actions (e.g., "Restock 50 units").
   - Execute approved actions (e.g., update inventory, notify suppliers).

4. **Manual Staff Requests**:
   - Enable staff to request inventory adjustments (e.g., "Transfer 20 units to Store A") or promotions (e.g., "Discount overstocked items").
   - Agent optimizes requests (e.g., prioritizes nearby stock, suggests discount rates) and seeks approval.

#### Additional Automation Requirements
5. **Dynamic Pricing**:
   - Automatically adjust prices based on demand, stock levels, or competitor data.
6. **Order Fulfillment Optimization**:
   - Suggest optimal warehouse or store for order fulfillment based on proximity and stock.
7. **Customer Recommendations**:
   - Suggest related products or alternatives when items are unavailable.
8. **Returns Processing**:
   - Automate return requests, restock returned items, and notify staff if quality checks are needed.

#### Non-Functional Requirements
1. **Scalability**: Handle multiple customers, products, and warehouses.
2. **Real-Time**: Reflect inventory and cart changes instantly.
3. **Reliability**: Ensure accurate stock tracking and order processing.
4. **Usability**: Provide intuitive interfaces for customers and staff.
5. **Efficiency**: Minimize stockouts and overstocking.

#### User Stories
- As a customer, I want real-time stock updates in my cart to avoid unavailable items.
- As a staff member, I want inventory suggestions to manage stock efficiently.
- As a manager, I want automated pricing and fulfillment to boost sales and reduce costs.

---

### Implementation Using the Defined Architecture

#### Architecture Overview
- **Three-Tier**: Presentation (UI for customers/staff), Business Logic (agent processing), Data (cart and inventory data).
- **EDA**: Events drive cart updates, inventory actions, and notifications.
- **Stateless Computing**: Scalable processing of tasks.
- **CronJobs**: Periodic stock checks and analytics.
- **HITL**: Staff approve critical actions.

---

#### Components and Workflow

##### 1. Three-Tier Architecture
- **Presentation Layer**:
  - **Customer UI**: Web/mobile app for browsing, adding to cart, and viewing recommendations.
  - **Staff Dashboard**: View inventory, cart issues, suggested actions, and submit requests.
  - Notifications (e.g., email, app alerts) for customers (out-of-stock) and staff (low stock).
- **Business Logic Layer**:
  - **Cart Agent**: Manages shopping carts, checks inventory, and suggests alternatives.
  - **Inventory Agent**: Tracks stock, suggests restocking/redistribution.
  - **Pricing Agent**: Adjusts prices dynamically.
  - **Fulfillment Agent**: Optimizes order fulfillment.
  - **Request Optimizer**: Optimizes manual staff requests.
  - **HITL Coordinator**: Manages approval workflows.
- **Data Layer**:
  - Stores:
    - Cart data (customerId, productId, quantity).
    - Inventory (productId, stock, location, price).
    - Action logs and approval status.
  - Tools: Database (PostgreSQL), cache (Redis) for real-time data.

##### 2. Event-Driven Architecture
- **Event Types**:
  - `CartUpdate`: Item added/removed from cart.
  - `InventoryUpdate`: Stock level changes (e.g., sale, restock).
  - `InventoryActionSuggested`: Action proposed (e.g., "Restock 100 units").
  - `PriceAdjustmentSuggested`: Dynamic price change proposed.
  - `FulfillmentSuggested`: Optimal fulfillment location proposed.
  - `HumanReviewRequired`: Approval needed.
  - `HumanResponseReceived`: Staff approves/modifies/rejects.
  - `ActionExecuted`: Action completed.
- **Event Bus**: RabbitMQ for event routing.
- **Workflow**:
  1. `CartUpdate` → Cart Agent checks stock → `InventoryUpdate` if needed.
  2. `InventoryUpdate` → Inventory Agent suggests restock → `InventoryActionSuggested`.
  3. `HumanResponseReceived` → Action executed → `ActionExecuted`.

##### 3. Stateless Computing
- **Cart Processor**: Stateless service (Lambda) processes `CartUpdate`, checks stock, suggests alternatives.
- **Inventory Processor**: Stateless function tracks stock, emits `InventoryActionSuggested`.
- **Pricing Processor**: Stateless service adjusts prices, emits `PriceAdjustmentSuggested`.
- **Fulfillment Processor**: Stateless function optimizes fulfillment, emits `FulfillmentSuggested`.
- **HITL Handler**: Stateless service manages approvals.
- **Action Executor**: Stateless function executes actions (e.g., updates stock, sends orders).

##### 4. Scheduled Computing (CronJobs)
- **Stock Checker**: Hourly scan for low/overstock → `InventoryActionSuggested`.
- **Price Analyzer**: Daily job analyzes demand/competitors → `PriceAdjustmentSuggested`.
- **Returns Processor**: Daily job processes returns, updates inventory → `InventoryUpdate`.

##### 5. Human-in-the-Loop (HITL)
- **Inventory Actions**: `InventoryActionSuggested` (e.g., "Restock 50 shirts") → Staff approves → `ActionExecuted`.
- **Price Adjustments**: `PriceAdjustmentSuggested` (e.g., "Discount jeans 20%") → Staff approves → Price updated.
- **Manual Requests**: Staff requests "Transfer 10 units" → Request Optimizer suggests source → Staff approves → Transfer executed.

---

#### Areas for LLM Intelligence
1. **Customer Recommendations (Business Logic - Cart Agent)**:
   - **Use Case**: Suggest alternatives or related products when items are out of stock (e.g., "Try this similar jacket").
   - **LLM Role**: Analyze product descriptions and customer preferences to generate natural, context-aware suggestions.
   - **Implementation**: LLM processes `CartUpdate` with low stock, adds suggestions to customer UI.

2. **Customer Notifications (Presentation Layer - Customer UI)**:
   - **Use Case**: Craft personalized out-of-stock or low-stock messages (e.g., "Sorry, the blue shirt is out, but here’s a great alternative!").
   - **LLM Role**: Generate friendly, persuasive text for notifications.
   - **Implementation**: LLM enhances `InventoryUpdate` notifications.

3. **Staff Action Explanations (Business Logic - Inventory/Pricing Agents)**:
   - **Use Case**: Explain suggested actions (e.g., "Restock due to 80% sales spike this week").
   - **LLM Role**: Translate data (e.g., sales trends) into readable insights for staff.
   - **Implementation**: LLM adds explanations to `InventoryActionSuggested` or `PriceAdjustmentSuggested`.

4. **Manual Request Optimization (Business Logic - Request Optimizer)**:
   - **Use Case**: Optimize staff requests with context (e.g., "Discount overstocked hats—suggest 15% based on slow sales").
   - **LLM Role**: Analyze request intent and inventory data, suggest refinements.
   - **Implementation**: LLM enhances `HumanReviewRequired` with optimized options.

---

#### Detailed Implementation

##### Step 1: Shopping Cart Management
- **Tech**: E-commerce API (e.g., Shopify).
- **Flow**:
  - Customer adds shirt (ID #456) → `CartUpdate {customerId, productId}`.
  - Cart Processor checks stock (5 left) → Updates UI, suggests "Hurry, only 5 left!" (LLM).

##### Step 2: Inventory Management
- **Tech**: Inventory Processor (stateless).
- **Flow**:
  - Shirt stock drops to 2 → `InventoryUpdate {productId, stock}`.
  - Inventory Agent suggests "Restock 50 units" → `InventoryActionSuggested` → LLM: "Due to high demand this week".

##### Step 3: Dynamic Pricing
- **Tech**: Pricing Processor with ML/LLM.
- **Flow**:
  - Overstocked jeans → `PriceAdjustmentSuggested {productId, discount: 20%}` → LLM: "Clear inventory before new season".
  - Staff approves → Price updated.

##### Step 4: Order Fulfillment
- **Tech**: Fulfillment Processor.
- **Flow**:
  - Order placed → `FulfillmentSuggested {orderId, warehouse: "Store B"}` → Staff approves → Order shipped.

##### Step 5: HITL for Approvals
- **Tech**: Dashboard + HITL Handler.
- **Flow**:
  - `HumanReviewRequired {task: "Restock #456"}` → Staff approves → `ActionExecuted`.

##### Step 6: Manual Requests
- **Tech**: UI + Request Optimizer with LLM.
- **Flow**:
  - Staff: "Discount slow movers" → LLM suggests "10% off hats" → `HumanReviewRequired` → Approved → Discount applied.

##### Step 7: Automation Features
- **Recommendations**: LLM suggests "Add socks" → Added to cart UI.
- **Returns**: Customer returns shirt → `InventoryUpdate` → Restocked after quality check.

---

#### Example Workflow
1. **Cart Management**:
   - Customer adds shoes → `CartUpdate` → Stock low → LLM: "Only 3 left, consider these boots!" → Added to UI.
2. **Inventory Action**:
   - Shoes drop to 1 → `InventoryActionSuggested: "Restock 20"` → Staff approves → Stock ordered.
3. **Dynamic Pricing**:
   - Overstocked jackets → `PriceAdjustmentSuggested: "15% off"` → Staff approves → Price updated.
4. **Manual Request**:
   - Staff: "Transfer 10 shirts" → Optimizer: "From Warehouse C" → Staff approves → Transferred.

---

### Benefits
- **Real-Time**: EDA ensures instant cart and inventory updates.
- **Scalable**: Stateless services handle high traffic.
- **Engagement**: LLM enhances customer experience.
- **Efficiency**: Automation optimizes stock and pricing.

### Challenges
- **LLM Precision**: Suggestions must align with inventory and customer needs.
- **Integration**: Requires seamless cart-inventory sync.

This Shopping Cart and Inventory Management Agent enhances e-commerce with automation and LLM intelligence, improving efficiency and customer satisfaction.
