diff --git a/source/includes/images/industry-solutions/rfid-product-architecture-2.svg b/source/includes/images/industry-solutions/rfid-product-architecture-2.svg
new file mode 100644
index 00000000..8e277bc7
--- /dev/null
+++ b/source/includes/images/industry-solutions/rfid-product-architecture-2.svg
@@ -0,0 +1 @@
+
\ No newline at end of file
diff --git a/source/includes/images/industry-solutions/rfid-product-architecture.svg b/source/includes/images/industry-solutions/rfid-product-architecture.svg
new file mode 100644
index 00000000..ba644b5b
--- /dev/null
+++ b/source/includes/images/industry-solutions/rfid-product-architecture.svg
@@ -0,0 +1 @@
+
\ No newline at end of file
diff --git a/source/solutions-library.txt b/source/solutions-library.txt
index 82483d71..dd4f1201 100644
--- a/source/solutions-library.txt
+++ b/source/solutions-library.txt
@@ -313,6 +313,15 @@ kick-start their projects.
Enable real-time order tracking and management across all
retail channels using MongoDB Atlas.
+ .. card::
+ :headline: Real-Time Product Tracking
+ :url: https://deploy-preview-236--docs-atlas-architecture.netlify.app/solutions-library/retail-asset-rfid-retail/
+ :icon: mdb_custom_aggregation
+ :icon-alt: Atlas mdb_custom_aggregation icon
+
+ Learn how to build a real-time inventory management system
+ with RFID and MongoDB Atlas.
+
Gen AI
------
diff --git a/source/solutions-library/manufacturing-asset-fleet-management.txt b/source/solutions-library/manufacturing-asset-fleet-management.txt
index 17ea3f34..b2ade46f 100644
--- a/source/solutions-library/manufacturing-asset-fleet-management.txt
+++ b/source/solutions-library/manufacturing-asset-fleet-management.txt
@@ -96,6 +96,8 @@ OpenAI LLM.
:alt: Basic Components of an AI Agent
Figure 1: Basic components of an AI agent
+
+.. video:: https://www.youtube.com/watch?v=_CAOb7BR-Rg
Reference Architecture
----------------------
@@ -371,7 +373,7 @@ Feel free to adjust the prompt in main.py or update the telemetry data in the te
Running the solution
~~~~~~~~~~~~~~~~~~~~
-**Starting a new diagnosis**
+**Starting a New Diagnosis**
- Open the frontend and choose “New Diagnosis”.
@@ -397,7 +399,7 @@ Running the solution
- Click the “Run Agent” button and wait for a minute or two as the agent
finishes its run.
-**Viewing workflow**
+**Viewing Workflow**
- The workflow, chain-of-thought output, and the final recommendation
is shown in the left column.
@@ -405,7 +407,7 @@ Running the solution
- The workflow is generated in real time, giving transparency into the
agent's decision-making process.
-**Reviewing MongoDB documents**
+**Reviewing MongoDB Documents**
- In the right column, the documents shown are the records inserted during the current agent run:
@@ -423,7 +425,7 @@ Running the solution
- **checkpoints:** (From the checkpointing database) Shows the last saved state for potential recovery.
-**Resume functionality**
+**Resume Functionality**
- Optionally, we can demonstrate the "Resume Diagnosis" feature by
entering a thread ID and showing how the system retrieves the
diff --git a/source/solutions-library/retail-asset-rfid-retail.txt b/source/solutions-library/retail-asset-rfid-retail.txt
new file mode 100644
index 00000000..03eb12d3
--- /dev/null
+++ b/source/solutions-library/retail-asset-rfid-retail.txt
@@ -0,0 +1,349 @@
+.. _arch-center-is-rfid-retail:
+
+================================
+RFID: Real-Time Product Tracking
+================================
+
+.. facet::
+ :name: genre
+ :values: tutorial
+
+.. meta::
+ :keywords: document model, retail, tracking, analytics, catalog
+ :description: Learn how to build a real-time inventory management system with RFID and MongoDB Atlas.
+
+.. contents:: On this page
+ :local:
+ :backlinks: none
+ :depth: 1
+ :class: singlecol
+
+Enhance retail inventory management with Radio Frequency Identification
+(RFID) Technology and MongoDB Atlas for real-time tracking, improved
+accuracy, and data-driven insights across your supply chain.
+
+**Use cases:** `Catalog `__,
+`Personalization `__
+
+**Industries:** `Retail `__
+
+**Products:** `MongoDB Atlas `__
+
+Solution Overview
+-----------------
+
+Retailers must ensure accurate and consistent inventory information
+across multiple channels while handling vast amounts of data. However,
+traditional methods struggle to keep pace with the demands of today's
+dynamic market.
+
+In this scenario, RFID Technology offers a transformative solution. By
+automatically tracking tagged items using electromagnetic fields,
+retailers gain unprecedented real-time visibility into inventory levels.
+This implementation optimize stock management, reduce labor
+costs, and elevate customer satisfaction.
+
+Harnessing RFID's potential requires a robust data layer. MongoDB Atlas
+provides the solution for capturing, processing, and analyzing these
+massive datasets.
+
+RFID Technology Benefits
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+By integrating RFID Technology with a powerful database solution,
+retailers can efficiently address product information management
+challenges and unlock key advantages:
+
+- **Inventory accuracy:** Eliminate stock discrepancies and reduce
+ out-of-stocks, ensuring products are where customers expect them to be.
+
+- **Operational efficiency:** Streamline processes like receiving,
+ picking, and packing, leading to faster turnaround times and cost
+ savings.
+
+- **Enhanced customer experience:** Fulfill orders accurately and
+ quickly, boosting customer satisfaction and loyalty.
+
+- **Data-driven insights:** Leverage detailed product and sales data to make
+ informed business decisions and optimize product assortment.
+
+.. video:: https://www.youtube.com/watch?v=xK2RHBcpZXc
+
+Reference Architectures
+-----------------------
+
+Businesses can track items from the manufacturing floor to the end
+consumer by attaching RFID tags to products and using a network of
+readers. Below, we explain the general architecture of a RFID system
+and provide a specific example with Zebra Technologies.
+
+Supply Chain Tracking with RFID
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This architecture shows a comprehensive system with RFID Technology to
+monitor product movement through the supply chain. MongoDB Atlas serves
+as the underlying data layer to manage and analyze RFID data.
+
+Key Components and Functions
+````````````````````````````
+
+- **RFID data collection:** Information is captured from RFID tags
+ attached to products using RFID readers.
+
+- **Data management:** MongoDB Atlas stores and processes collected RFID
+ data.
+
+- **Data analysis:** The system utilizes MongoDB Atlas to extract
+ valuable insights from the data through data cleaning, transformation,
+ and analysis.
+
+- **Workflow optimization:** The architecture visualizes the data flow
+ from initial collection to the generation of actionable insights.
+
+.. figure:: /includes/images/industry-solutions/rfid-product-architecture.svg
+ :figwidth: 1200px
+ :alt: End-to-end supply chain RFID tracking architecture
+
+ Figure 1. End-to-end supply chain RFID tracking architecture
+
+RFID Product Tracking Implementation
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Using a RFID product tracking architecture, we show an example that
+integrates the Zebra Technologies 123RFID app with MongoDB Atlas through
+an API gateway.
+
+**Key Components and Functionalities**
+
+- **RFID data capture:** The Zebra Technologies 123RFID app collects product
+ information via RFID tags.
+
+- **Data integration:** An API gateway seamlessly transfers RFID data
+ from the app to MongoDB Atlas.
+
+- **Data storage and analysis:** MongoDB Atlas serves as the central
+ repository for RFID data, enabling comprehensive data analysis.
+
+.. figure:: /includes/images/industry-solutions/rag-chatbot-architecture.svg
+ :figwidth: 1200px
+ :alt: Example of a RFID product architecture with Atlas and Zebra Technologies
+
+ Figure 2. Example of a RFID product tracking architecture based on the integration of Zebra Technologies with MongoDB Atlas
+
+Building the Solution
+---------------------
+
+This guide explains how a retail RFID product tracking application
+integrates with MongoDB Atlas and demonstrates how to use it for
+efficient inventory checks.
+
+.. procedure::
+ :style: normal
+
+ .. step:: Set Up MongoDB Atlas
+
+ **Cluster Setup**
+
+ - Select a cloud provider.
+
+ - Choose a region.
+
+ - Configure cluster specifications (e.g., instance size, storage).
+
+ **Network Security**
+
+ - Configure network access.
+
+ - Identify IP access list for edge devices and application
+ servers.
+
+ - User authentication.
+
+ - Create a database user with read and write permissions for the
+ inventory database.
+
+ **Connection**
+
+ - Obtain connection string from MongoDB Atlas.
+
+ - Use connection string to connect your application to the
+ cluster.
+
+ .. step:: Configure your project in Xcode
+
+ **Project Setup**
+
+ - Open the 123RFID (or the name you’ve given it) project in `Xcode
+ `__.
+
+ - Configure project settings (deployment target).
+
+ - Add necessary frameworks and libraries from Zebra SDK.
+
+ - Configure build settings (library search paths, framework search
+ paths).
+
+ **Device Pairing**
+
+ - Enable Bluetooth on iOS device.
+
+ - Pair RFID reader using 123RFID app.
+
+ **Running the Application**
+
+ - Connect iOS device to Mac.
+
+ - Select device as target in Xcode.
+
+ - Run the application.
+
+ .. step:: Match Inventory Tags
+
+ The *getMatchingTagList* method in Objective-C compares RFID tags
+ from the current physical inventory with a predefined list of tags
+ and updates the user interface accordingly. This procedure works
+ as follows:
+
+ - Retrieves current inventory and predefined tag list.
+
+ - Compares inventory tags with the tag list to find matches.
+
+ - Removes matched tags from the missing tags list.
+
+ - Updates UI with counts of unique and total tags.
+
+ - Stops inventory operation and confirms a complete match if all
+ tags are accounted.
+
+ .. step:: Send Match Confirmation
+
+ The *sendUrlRequestToFlag* method sends a POST request to a
+ specified URL to indicate the result of the inventory check. This
+ process works as follows:
+
+ - Initializes POST request to the target URL.
+
+ - Sets JSON content type header.
+
+ - Prepares JSON payload with inventory check results.
+
+ - Sends POST request and logs the results.
+
+ - Displays a warning message based on the inventory check outcome.
+
+ .. step:: Display Your Inventory Checks in Real Time
+
+ We leverage `MongoDB Change Streams
+ `__ for
+ instant notifications and visualize the data using `MongoDB Atlas
+ Charts
+ `__. The
+ code sets up a change stream to monitor new inventory checks in
+ the inventoryCheck collection.
+
+ **Endpoint Setup**
+
+ - Use MongoDB Change Streams to monitor changes in the
+ inventoryCheck collection.
+
+ .. code-block:: javascript
+ :copyable: true
+
+ const startWatchInventoryCheck = async (dashboard, addAlert, utils) => {
+ console.log("Start watching stream");
+
+ const runs = await getMongoCollection(utils.dbInfo.dbName, "inventoryCheck");
+ const filter = {
+ filter: {
+ operationType: "insert"
+ }
+ };
+
+ const stream = runs.watch(filter);
+
+ const closeStreamInventoryCheck = () => {
+ console.log("Closing stream");
+ stream.return();
+ };
+
+ try {
+ for await (const change of stream) {
+ console.log(change.fullDocument);
+ addAlert(change.fullDocument.checkResult);
+ dashboard.refresh();
+ }
+ } catch (error) {
+ console.error("Error watching stream:", error);
+ }
+ };
+
+ **Embed the dashboard**
+
+ - Use MongoDB Charts embedding SDK to integrate the dashboard into
+ your web application.
+
+ - Import the necessary libraries and context.
+
+ - Create an instance of ChartsEmbedSDK with your base URL.
+
+ - Define and render the dashboard properties into a designated
+ div.
+ - Start the change stream and handle real-time updates with
+ alerts.
+
+ **Implement Real-Time Alerts**
+
+ - Display success or error alerts based on the inventory check
+ results using *pushToast*.
+
+ **Ensure Integration**
+
+ - Verify that real-time notifications and dashboard updates work
+ seamlessly.
+
+ - Maintain accurate inventory data and respond quickly to
+ discrepancies.
+
+Follow this guide to effectively integrate the Zebra 123RFID app with
+MongoDB Atlas, enabling real-time inventory management and data
+accuracy.
+
+Key Learnings
+-------------
+
+By combining RFID Technology and MongoDB Atlas, retailers can enhance
+their inventory management capabilities. This integration provides several
+key advantages:
+
+- **Real-time inventory management:** Leverage RFID Technology and MongoDB
+ Atlas to achieve accurate and up-to-date inventory data.
+
+- **Improved efficiency:** Streamline inventory processes, reduce stockouts,
+ and optimize operations through data-driven insights.
+
+- **Data-driven decision making:** Use MongoDB Atlas Charts for real-time
+ visualizations, enabling informed business decisions.
+
+Technologies and Products Used
+------------------------------
+
+MongoDB Developer Data Platform
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+- `MongoDB Atlas `__
+
+Additional Technologies
+~~~~~~~~~~~~~~~~~~~~~~~
+
+- `Zebra Technologies 123RFID app `__
+- `Zebra RFID readers/scanners `__
+
+Authors
+-------
+
+- Francesco Baldissera, MongoDB
+- Pedro Bereilh, MongoDB
+- Rami Pinto, MongoDB
+- Sebastian Rojas Arbulu, MongoDB
+- Mehar Grewal, MongoDB
+- Prashant Juttukonda, MongoDB
\ No newline at end of file
diff --git a/source/solutions-library/retail-catalog.txt b/source/solutions-library/retail-catalog.txt
index 59117025..bae4d25a 100644
--- a/source/solutions-library/retail-catalog.txt
+++ b/source/solutions-library/retail-catalog.txt
@@ -7,4 +7,5 @@ Retail Catalog
As-You-Type Suggestions
Building Inventory Management System
- Building Omnichannel Ordering Solution
\ No newline at end of file
+ Building Omnichannel Ordering Solution
+ Real-Time Product Tracking
\ No newline at end of file