SHAPINg the future with
HYPERAUTOMATION
Process intelligence + Automation
SHAPINg the future with
HYPERAUTOMATION
Process intelligence + Automation
IMPROVE PROCESS EXCELLENCE AND ACHIEVE SUSTAINABLE ADVANTAGES
Embarking on a hyperautomation journey involves a strategic, phased approach that ensures a smooth transition and maximization of benefits.
We understand that embarking on a hyperautomation journey is a pivotal step for organizations looking to enhance their operational efficiency and drive innovation. To successfully reach the summit of hyperautomation, our 3-step model is the perfect travel guide.
SHAPINg the future with
HYPERAUTOMATION
Process intelligence + Automation
IMPROVE PROCESS EXCELLENCE AND ACHIEVE SUSTAINABLE ADVANTAGES
Embarking on a hyperautomation journey involves a strategic, phased approach that ensures a smooth transition and maximization of benefits.
We understand that embarking on a hyperautomation journey is a pivotal step for organizations looking to enhance their operational efficiency and drive innovation. To successfully reach the summit of hyperautomation, our 3-step model is the perfect travel guide.
STEP 1: DISCOVERY + ANALYSIS
.. provides the foundation for a successful automation. It is crucial for identifying processes and use cases suitable for automation with focus on business value and a secure and scalable architecture.
Process Mining can optionally be used for a holistic view on your processes.
STEP 1: DISCOVERY + ANALYSIS
.. provides the foundation for a successful automation. It is crucial for identifying processes and use cases suitable for automation with focus on business value and a secure and scalable architecture.
Process Mining can optionally be used for a holistic view on your processes.
STEP 2: AUTOMATION
.. is all about applying the right tools and architecture in an incremental design-build-deploy cycle to create a tailored automation solution that fit your unique requirements with measurable business impact.
RPA (Robotic Process Automation): Ideal for automating repetitive, rule-based tasks such as data entry, system updates, and file transfers. RPA is best used where structured data and stable processes are present, helping reduce manual errors and operational costs.
Agents (Intelligent Agentic Automation): AI agents, also kown as intelligent agents, are software or hardware entities that autonomously perform tasks, process data, make trustworthy decisions and interact with their environment or other agents. These agents are based on advanced algorithms and machine learning that enable them to adapt to changing conditions and constantly learn.
IDP (Intelligent Document Processing): Enables automation of document-centric tasks by extracting, classifying, and validating unstructured data from sources like PDFs, invoices, and forms. IDP can be applied in all industries and processes where large volumes of documents are processed.
API (Reusable Components): Facilitates seamless integration across systems, applications, and services. APIs are critical when e.g. multiple platforms or agents need to exchange data securly and in real-time, enabling end-to-end automation and enhanced digital experiences.
Each of these tools can be deployed individually or in combination, depending on the complexity and nature of your processes. The result is a streamlined, intelligent automation solution that enhances productivity, reduces costs, and improves overall operational agility.
STEP 2: AUTOMATION
.. is all about applying the right tools and architecture in an incremental design-build-deploy cycle to create a tailored automation solution that fit your unique requirements with measurable business impact.
RPA (Robotic Process Automation): Ideal for automating repetitive, rule-based tasks such as data entry, system updates, and file transfers. RPA is best used where structured data and stable processes are present, helping reduce manual errors and operational costs.
Agents (Intelligent Agentic Automation): AI agents, also kown as intelligent agents, are software or hardware entities that autonomously perform tasks, process data, make trustworthy decisions and interact with their environment or other agents. These agents are based on advanced algorithms and machine learning that enable them to adapt to changing conditions and constantly learn.
IDP (Intelligent Document Processing): Enables automation of document-centric tasks by extracting, classifying, and validating unstructured data from sources like PDFs, invoices, and forms. IDP can be applied in all industries and processes where large volumes of documents are processed.
API (Reusable Components): Facilitates seamless integration across systems, applications, and services. APIs are critical when e.g. multiple platforms or agents need to exchange data securly and in real-time, enabling end-to-end automation and enhanced digital experiences.
Each of these tools can be deployed individually or in combination, depending on the complexity and nature of your processes. The result is a streamlined, intelligent automation solution that enhances productivity, reduces costs, and improves overall operational agility.
STEP 3: SCALE + SUSTAIN
To roll out intelligent automation sustainably and securely in the company, it is important to scale effectively via value-creating use cases and to establish an architecture and governance that takes into account the “pay as you go” license models on the one hand and keeps pace with the rapidly changing environment on the other.
STEP 3: SCALE + SUSTAIN
To roll out intelligent automation sustainably and securely in the company, it is important to scale effectively via value-creating use cases and to establish an architecture and governance that takes into account the “pay as you go” license models on the one hand and keeps pace with the rapidly changing environment on the other.
USE CASES
Use Case 1
Step 1
Step 2
Step 3
Technologies & Tools Used
Key Functional Highlights
Use Case 1
This use case outlines an automated workflow with Salesforce and MuleSoft, tailored for service personnel handling purchase orders (POs) from B2B customers. These POs, typically received as scanned PDF documents, are deposited into a shared FTP folder. The service agent then initiates a request through an Order Management Agent to upload, process the documents and create the corresponding orders in Salesforce.
The end-to-end automation seamlessly handles the following steps:
• Upload of scanned POs
• Document classification
• Data extraction and validation
• Creation of the final order in Salesforce
This streamlined end-to-end automation significantly reduces manual effort, ensures greater accuracy, and accelerates order fulfilment.
The end-to-end automation seamlessly handles the following steps:
• Upload of scanned POs
• Document classification
• Data extraction and validation
• Creation of the final order in Salesforce
This streamlined end-to-end automation significantly reduces manual effort, ensures greater accuracy, and accelerates order fulfilment.
Step 1
The process begins when a service agent submits an order upload request through an Order Management Agent built with Salesforce Agentforce for seamless interaction. Once the request is received, the Agent triggers a Salesforce Flow to initiate the order intake process.
Step 1: Uploading PDFs from FTP to Salesforce
The first step in the flow invokes MuleSoft API #1, known as the Uploader. This API connects to a shared FTP folder, where scanned PDF purchase orders from B2B customers are stored. The API converts each file into Base64 format and uses the Salesforce REST API to upload the documents into Salesforce. Upon successful upload, it returns a list of Upload IDs (Content Version) back to the calling flow.
Step 1: Uploading PDFs from FTP to Salesforce
The first step in the flow invokes MuleSoft API #1, known as the Uploader. This API connects to a shared FTP folder, where scanned PDF purchase orders from B2B customers are stored. The API converts each file into Base64 format and uses the Salesforce REST API to upload the documents into Salesforce. Upon successful upload, it returns a list of Upload IDs (Content Version) back to the calling flow.
Step 2
Step 2: Document Classification and Data Extraction
The Salesforce Flow then iterates through each uploaded document using the list of the returned IDs. For every document, it generates a secure download link and sends it to MuleSoft API #2, known as the Data Extractor. This API retrieves the file from Salesforce and forwards it to an MuleSoft Intelligent Document Processing (IDP) system for data extraction.
The IDP system performs two essential functions:
1. Classification
It identifies the document’s layout and source. This step is crucial, as B2B customers often use different templates and formats for their purchase orders.
2. Data Extraction
The IDP extracts all key information from the scanned image, like Purchase order type, Order date, Billing and shipping addresses, Line items details, Total order value etc.
The extracted information is then returned to the Salesforce Flow in a structured JSON format, ready for further processing and validation.
The Salesforce Flow then iterates through each uploaded document using the list of the returned IDs. For every document, it generates a secure download link and sends it to MuleSoft API #2, known as the Data Extractor. This API retrieves the file from Salesforce and forwards it to an MuleSoft Intelligent Document Processing (IDP) system for data extraction.
The IDP system performs two essential functions:
1. Classification
It identifies the document’s layout and source. This step is crucial, as B2B customers often use different templates and formats for their purchase orders.
2. Data Extraction
The IDP extracts all key information from the scanned image, like Purchase order type, Order date, Billing and shipping addresses, Line items details, Total order value etc.
The extracted information is then returned to the Salesforce Flow in a structured JSON format, ready for further processing and validation.
Step 3
Step 3: Creating the Order in Salesforce
Once the structured data is received, the Salesforce Flow parses the JSON to extract both the order header and line-item details. It begins by creating the Order record in Salesforce, followed by a loop that creates individual Line Items for each product listed in the purchase order.
To maintain full traceability, the original scanned PDF is also linked to the order record as a supporting document. Upon successful order creation, the Flow returns the Order ID and Order Number back to Agent and then subsequently to the service person, confirming that the process is complete.
Optional Post-Processing via AgentForce
Following order creation, the service agent can continue interacting with the system through the Agent to perform additional actions such as:
• Checking the current order status
• Reviewing billing or shipping details
• Accessing related documents
All of these tasks can be performed within the same conversational interface—eliminating the need to navigate between different systems and enhancing overall productivity.
Once the structured data is received, the Salesforce Flow parses the JSON to extract both the order header and line-item details. It begins by creating the Order record in Salesforce, followed by a loop that creates individual Line Items for each product listed in the purchase order.
To maintain full traceability, the original scanned PDF is also linked to the order record as a supporting document. Upon successful order creation, the Flow returns the Order ID and Order Number back to Agent and then subsequently to the service person, confirming that the process is complete.
Optional Post-Processing via AgentForce
Following order creation, the service agent can continue interacting with the system through the Agent to perform additional actions such as:
• Checking the current order status
• Reviewing billing or shipping details
• Accessing related documents
All of these tasks can be performed within the same conversational interface—eliminating the need to navigate between different systems and enhancing overall productivity.
Technologies & Tools Used
| Component | Technology/Tool | Purpose |
|---|---|---|
| Order System | Salesforce | CRM system to store and manage orders |
| Automation (Salesforce) | Agentforce | Front-end used by service agents to manage order uploads and review created orders |
| Automation (Salesforce) | Flow (Auto-launched) | Orchestrates the end-to-end process |
| Automation (MuleSoft) | MuleSoft Anypoint platform | Interfaces with FTP, IDP, and Salesforce APIs |
| Automation (MuleSoft) | MuleSoft Intelligent Document Processing | Classifies and extracts data from Order documents |
| Order External upload point | FTP Server | Source of Purchase orders |
Key Functional Highlights
Key Highlights
• Scanned Image to Structured Data
Converts a wide range of non-machine-readable PDFs of drastically varying formats into structured data using AI-powered document understanding—no reliance on fixed templates.
• Intelligent and Scalable Data Extraction
Used MuleSoft IDP, to automatically classify and adapt to different customer PO formats, eliminating the need for one-off configurations or too specific code. This ensures a scalable architecture that can be easily extended to include more customer specific documents.
• Fully Automated Workflow
Delivers end-to-end automation from scanned document to Salesforce order creation, with zero manual intervention.
• Designed for Scalability
Easily handles increasing document volume and supports onboarding of new customers with minimal effort, thanks to flexible, API-driven architecture.
• Built for Maintainability Modular design using Salesforce Flows and MuleSoft APIs enables easy updates, version control, and low-code enhancements without disrupting the end-to-end process.
Business Impact
This use case demonstrates the powerful synergy between Salesforce, MuleSoft, and AI-based Intelligent Document Processing (IDP) to deliver a resilient, scalable, and agent-friendly automation of B2B order intake.
Tangible Benefits:
For the Business:
o Reduced manual workload and errors
o Faster order processing
o High adaptability to customer diversity
For the Frontline Team:
o Seamless experience with zero technical friction
o Quick access to order details and actions via chat
o More time to focus on customer service, not data entry
This is intelligent automation not just for efficiency—but for empowering people.
• Scanned Image to Structured Data
Converts a wide range of non-machine-readable PDFs of drastically varying formats into structured data using AI-powered document understanding—no reliance on fixed templates.
• Intelligent and Scalable Data Extraction
Used MuleSoft IDP, to automatically classify and adapt to different customer PO formats, eliminating the need for one-off configurations or too specific code. This ensures a scalable architecture that can be easily extended to include more customer specific documents.
• Fully Automated Workflow
Delivers end-to-end automation from scanned document to Salesforce order creation, with zero manual intervention.
• Designed for Scalability
Easily handles increasing document volume and supports onboarding of new customers with minimal effort, thanks to flexible, API-driven architecture.
• Built for Maintainability Modular design using Salesforce Flows and MuleSoft APIs enables easy updates, version control, and low-code enhancements without disrupting the end-to-end process.
Business Impact
This use case demonstrates the powerful synergy between Salesforce, MuleSoft, and AI-based Intelligent Document Processing (IDP) to deliver a resilient, scalable, and agent-friendly automation of B2B order intake.
Tangible Benefits:
For the Business:
o Reduced manual workload and errors
o Faster order processing
o High adaptability to customer diversity
For the Frontline Team:
o Seamless experience with zero technical friction
o Quick access to order details and actions via chat
o More time to focus on customer service, not data entry
This is intelligent automation not just for efficiency—but for empowering people.
Use Case 2
Challenge
Solution
Benefits
Use Case 2
This use case showcases how we transformed the manual order processing of a B2B provider specializing in cable management and EMC shielding solutions into a scalable, fully automated system.
By integrating intelligent document processing (IDP), robotic process automation (RPA), and MuleSoft for orchestration, the company significantly reduced manual workload, improved data accuracy, and enabled efficient, around-the-clock processing of unstructured order documents.
By integrating intelligent document processing (IDP), robotic process automation (RPA), and MuleSoft for orchestration, the company significantly reduced manual workload, improved data accuracy, and enabled efficient, around-the-clock processing of unstructured order documents.
Challenge
The company has so far been processing customer orders manually:
• Customers send informal orders via email in unstructured PDF documents
• These orders must be manually typed by employees and entered into an internal ERP system (ICM)
• The process is time-consuming, error-prone, and scales poorly
• Processing capacity is limited by manual steps and limited resources
• Customers send informal orders via email in unstructured PDF documents
• These orders must be manually typed by employees and entered into an internal ERP system (ICM)
• The process is time-consuming, error-prone, and scales poorly
• Processing capacity is limited by manual steps and limited resources
Solution
An automated system for processing incoming order documents:
MuleSoft Anypoint API:
Orders received as email attachments are retrieved and provided via an API
Intelligent Document Processing (IDP):
Incoming orders are automatically read and structured
Confidence-Based Review Process:
If uncertainty is detected (e.g., <80% accuracy), a "manual review" step is triggered
Batch-Based Processing:
Email reading, manual post-processing, and execution in the CRM by the robot are fully decoupled and executed independently (in parallel)
MuleSoft Object Store:
Seamless integration of the individual steps—order ingestion, manual review, and RPA execution—is handled via the MuleSoft Object Store
Robotic Process Automation (RPA):
A virtual robot enters the data provided by the IDP into the ERP system
Logging and Traceability:
Process data is logged as extensively as possible—within the RPA system and to a limited extent in MuleSoft flows
MuleSoft Anypoint API:
Orders received as email attachments are retrieved and provided via an API
Intelligent Document Processing (IDP):
Incoming orders are automatically read and structured
Confidence-Based Review Process:
If uncertainty is detected (e.g., <80% accuracy), a "manual review" step is triggered
Batch-Based Processing:
Email reading, manual post-processing, and execution in the CRM by the robot are fully decoupled and executed independently (in parallel)
MuleSoft Object Store:
Seamless integration of the individual steps—order ingestion, manual review, and RPA execution—is handled via the MuleSoft Object Store
Robotic Process Automation (RPA):
A virtual robot enters the data provided by the IDP into the ERP system
Logging and Traceability:
Process data is logged as extensively as possible—within the RPA system and to a limited extent in MuleSoft flows
Benefits
Time Savings: Significant reduction in manual data entry
Error Reduction: Automated extraction and validation improve data quality
Scalability: High performance even with large order volumes
Increased Efficiency: The robot can autonomously process orders outside of business hours
Cost Reduction: Minimization of manual resources without expensive database infrastructure
Flexibility: Asynchronous processing without system blocking enables continuous operations
Error Reduction: Automated extraction and validation improve data quality
Scalability: High performance even with large order volumes
Increased Efficiency: The robot can autonomously process orders outside of business hours
Cost Reduction: Minimization of manual resources without expensive database infrastructure
Flexibility: Asynchronous processing without system blocking enables continuous operations
Use Case 3
IDP
Benefits
Use Case 3
This Intelligent Document Processing (IDP) use case includes thousands of PDF delivery notes that are received via email annually and must be processed to update inventory in the ERP system and generate invoices for customers. While the delivery notes are consistent for each supplier, they vary significantly between different suppliers.
Therefore the process previously required significant manual effort and was prone to errors.
Therefore the process previously required significant manual effort and was prone to errors.
IDP
Intelligent Document Processing (IDP) played a central role in automating the processing of thousands of PDF delivery notes that arrived via email from various suppliers. Here’s how:
1. Document Ingestion
The system automatically monitors a dedicated mailbox and retrieves incoming PDF delivery notes.
2. Document Classification
Using machine learning, the IDP solution identifies the document type (delivery note) and recognizes the supplier — even if layout, formatting, or structure varies significantly.
3. Intelligent Data Extraction
Key data fields are extracted using a combination of OCR and AI:
- Delivery date
- Material numbers and quantities
- Packaging and weight
- Sender and recipient addresses
- Total cost and customs fees
The system is trained to handle variations in layout, language, and field positioning between suppliers.
4. Data Validation & Enrichment
Extracted data is automatically validated against business rules (e.g., cross-checking material numbers with the ERP).
Where needed, contextual enrichment (e.g., assigning internal item codes) is performed.
5. Integration with ERP System
Clean, validated data is pushed directly into the ERP system:
- Inventory levels are updated
- Invoice records are prepared
- Delivery confirmations are triggered if needed
Benefits
Key Benefits of the IDP Solution
Scalability: Capable of processing over 12,000 documents annually without the need for additional human resources.
Flexibility: Adapts to a wide range of delivery note formats from various suppliers, regardless of layout or structure.
Accuracy: Dramatically reduces manual data entry errors by leveraging AI-powered data extraction.
Efficiency: Saves more than 2,100 hours of manual work per year, accelerating inventory updates and invoice creation.
Compliance: Ensures that critical information such as customs and regulatory data is consistently and accurately captured.
Operational Impact: 12,000+ documents processed annually, 2,100+ labor hours saved, 1,200+ tons of cast iron tracked through automated workflows.
Scalability: Capable of processing over 12,000 documents annually without the need for additional human resources.
Flexibility: Adapts to a wide range of delivery note formats from various suppliers, regardless of layout or structure.
Accuracy: Dramatically reduces manual data entry errors by leveraging AI-powered data extraction.
Efficiency: Saves more than 2,100 hours of manual work per year, accelerating inventory updates and invoice creation.
Compliance: Ensures that critical information such as customs and regulatory data is consistently and accurately captured.
Operational Impact: 12,000+ documents processed annually, 2,100+ labor hours saved, 1,200+ tons of cast iron tracked through automated workflows.
Use Case 4
The Challenge
Solution
Benefits
Use Case 4
This use case highlights a successful automation project we delivered for a leading company in the metering industry. The client was struggling with the manual processing of thousands of documents each month, resulting in high operational costs and delayed data entry.
We implemented a scalable solution using MuleSoft’s Anypoint Platform, Intelligent Document Processing (IDP), and integrated AI models to extract and process critical data automatically. The result: streamlined operations, over €60,000 in annual cost savings, and a new revenue-generating product for our client in the area of document automation.
We implemented a scalable solution using MuleSoft’s Anypoint Platform, Intelligent Document Processing (IDP), and integrated AI models to extract and process critical data automatically. The result: streamlined operations, over €60,000 in annual cost savings, and a new revenue-generating product for our client in the area of document automation.
The Challenge
A leading metering company was facing significant inefficiencies in processing thousands of documents received via email each month. Key information such as meter readings, serial numbers, addresses, and invoice values had to be manually entered into the ERP system—a time-consuming process costing the company over €120,000 annually.
This manual workflow also introduced:
• Frequent delays in data entry
• Increased risk of late payments and related dunning fees
• Limited scalability in handling growing document volumes
This manual workflow also introduced:
• Frequent delays in data entry
• Increased risk of late payments and related dunning fees
• Limited scalability in handling growing document volumes
Solution
To eliminate manual processing, we implemented an automated document processing solution powered by:
• MuleSoft IDP (Intelligent Document Processing)
• External AI model integration via Anypoint for smart data extraction and classification
The solution enabled end-to-end automation—emails are now ingested, documents are analyzed in real time, and key data points are automatically populated into the ERP system.
The automated platform has been so effective that the company now offers this solution as a product to its own customers.
• MuleSoft IDP (Intelligent Document Processing)
• External AI model integration via Anypoint for smart data extraction and classification
The solution enabled end-to-end automation—emails are now ingested, documents are analyzed in real time, and key data points are automatically populated into the ERP system.
The automated platform has been so effective that the company now offers this solution as a product to its own customers.
Benefits
• €60,000 in annual cost savings through automation
• €750,000 in additional revenue by offering the solution as a product
• 500,000+ documents processed annually, with capacity to scale further
• Improved processing speed and accuracy
• Reduced risk of late fees due to delayed entries
• €750,000 in additional revenue by offering the solution as a product
• 500,000+ documents processed annually, with capacity to scale further
• Improved processing speed and accuracy
• Reduced risk of late fees due to delayed entries
USE CASES
Use Case 1
Step 1
Step 2
Step 3
Technologies & Tools Used
Key Functional Highlights
Use Case 1
This use case outlines an automated workflow with Salesforce and MuleSoft, tailored for service personnel handling purchase orders (POs) from B2B customers. These POs, typically received as scanned PDF documents, are deposited into a shared FTP folder. The service agent then initiates a request through an Order Management Agent to upload, process the documents and create the corresponding orders in Salesforce.
The end-to-end automation seamlessly handles the following steps:
• Upload of scanned POs
• Document classification
• Data extraction and validation
• Creation of the final order in Salesforce
This streamlined end-to-end automation significantly reduces manual effort, ensures greater accuracy, and accelerates order fulfilment.
The end-to-end automation seamlessly handles the following steps:
• Upload of scanned POs
• Document classification
• Data extraction and validation
• Creation of the final order in Salesforce
This streamlined end-to-end automation significantly reduces manual effort, ensures greater accuracy, and accelerates order fulfilment.
Step 1
The process begins when a service agent submits an order upload request through an Order Management Agent built with Salesforce Agentforce for seamless interaction. Once the request is received, the Agent triggers a Salesforce Flow to initiate the order intake process.
Step 1: Uploading PDFs from FTP to Salesforce
The first step in the flow invokes MuleSoft API #1, known as the Uploader. This API connects to a shared FTP folder, where scanned PDF purchase orders from B2B customers are stored. The API converts each file into Base64 format and uses the Salesforce REST API to upload the documents into Salesforce. Upon successful upload, it returns a list of Upload IDs (Content Version) back to the calling flow.
Step 1: Uploading PDFs from FTP to Salesforce
The first step in the flow invokes MuleSoft API #1, known as the Uploader. This API connects to a shared FTP folder, where scanned PDF purchase orders from B2B customers are stored. The API converts each file into Base64 format and uses the Salesforce REST API to upload the documents into Salesforce. Upon successful upload, it returns a list of Upload IDs (Content Version) back to the calling flow.
Step 2
Step 2: Document Classification and Data Extraction
The Salesforce Flow then iterates through each uploaded document using the list of the returned IDs. For every document, it generates a secure download link and sends it to MuleSoft API #2, known as the Data Extractor. This API retrieves the file from Salesforce and forwards it to an MuleSoft Intelligent Document Processing (IDP) system for data extraction.
The IDP system performs two essential functions:
1. Classification
It identifies the document’s layout and source. This step is crucial, as B2B customers often use different templates and formats for their purchase orders.
2. Data Extraction
The IDP extracts all key information from the scanned image, like Purchase order type, Order date, Billing and shipping addresses, Line items details, Total order value etc.
The extracted information is then returned to the Salesforce Flow in a structured JSON format, ready for further processing and validation.
The Salesforce Flow then iterates through each uploaded document using the list of the returned IDs. For every document, it generates a secure download link and sends it to MuleSoft API #2, known as the Data Extractor. This API retrieves the file from Salesforce and forwards it to an MuleSoft Intelligent Document Processing (IDP) system for data extraction.
The IDP system performs two essential functions:
1. Classification
It identifies the document’s layout and source. This step is crucial, as B2B customers often use different templates and formats for their purchase orders.
2. Data Extraction
The IDP extracts all key information from the scanned image, like Purchase order type, Order date, Billing and shipping addresses, Line items details, Total order value etc.
The extracted information is then returned to the Salesforce Flow in a structured JSON format, ready for further processing and validation.
Step 3
Step 3: Creating the Order in Salesforce
Once the structured data is received, the Salesforce Flow parses the JSON to extract both the order header and line-item details. It begins by creating the Order record in Salesforce, followed by a loop that creates individual Line Items for each product listed in the purchase order.
To maintain full traceability, the original scanned PDF is also linked to the order record as a supporting document. Upon successful order creation, the Flow returns the Order ID and Order Number back to Agent and then subsequently to the service person, confirming that the process is complete.
Optional Post-Processing via AgentForce
Following order creation, the service agent can continue interacting with the system through the Agent to perform additional actions such as:
• Checking the current order status
• Reviewing billing or shipping details
• Accessing related documents
All of these tasks can be performed within the same conversational interface—eliminating the need to navigate between different systems and enhancing overall productivity.
Once the structured data is received, the Salesforce Flow parses the JSON to extract both the order header and line-item details. It begins by creating the Order record in Salesforce, followed by a loop that creates individual Line Items for each product listed in the purchase order.
To maintain full traceability, the original scanned PDF is also linked to the order record as a supporting document. Upon successful order creation, the Flow returns the Order ID and Order Number back to Agent and then subsequently to the service person, confirming that the process is complete.
Optional Post-Processing via AgentForce
Following order creation, the service agent can continue interacting with the system through the Agent to perform additional actions such as:
• Checking the current order status
• Reviewing billing or shipping details
• Accessing related documents
All of these tasks can be performed within the same conversational interface—eliminating the need to navigate between different systems and enhancing overall productivity.
Technologies & Tools Used
| Component | Technology/Tool | Purpose |
|---|---|---|
| Order System | Salesforce | CRM system to store and manage orders |
| Automation (Salesforce) | Agentforce | Front-end used by service agents to manage order uploads and review created orders |
| Automation (Salesforce) | Flow (Auto-launched) | Orchestrates the end-to-end process |
| Automation (MuleSoft) | MuleSoft Anypoint platform | Interfaces with FTP, IDP, and Salesforce APIs |
| Automation (MuleSoft) | MuleSoft Intelligent Document Processing | Classifies and extracts data from Order documents |
| Order External upload point | FTP Server | Source of Purchase orders |
Key Functional Highlights
Key Highlights
• Scanned Image to Structured Data
Converts a wide range of non-machine-readable PDFs of drastically varying formats into structured data using AI-powered document understanding—no reliance on fixed templates.
• Intelligent and Scalable Data Extraction
Used MuleSoft IDP, to automatically classify and adapt to different customer PO formats, eliminating the need for one-off configurations or too specific code. This ensures a scalable architecture that can be easily extended to include more customer specific documents.
• Fully Automated Workflow
Delivers end-to-end automation from scanned document to Salesforce order creation, with zero manual intervention.
• Designed for Scalability
Easily handles increasing document volume and supports onboarding of new customers with minimal effort, thanks to flexible, API-driven architecture.
• Built for Maintainability Modular design using Salesforce Flows and MuleSoft APIs enables easy updates, version control, and low-code enhancements without disrupting the end-to-end process.
Business Impact
This use case demonstrates the powerful synergy between Salesforce, MuleSoft, and AI-based Intelligent Document Processing (IDP) to deliver a resilient, scalable, and agent-friendly automation of B2B order intake.
Tangible Benefits:
For the Business:
o Reduced manual workload and errors
o Faster order processing
o High adaptability to customer diversity
For the Frontline Team:
o Seamless experience with zero technical friction
o Quick access to order details and actions via chat
o More time to focus on customer service, not data entry
This is intelligent automation not just for efficiency—but for empowering people.
• Scanned Image to Structured Data
Converts a wide range of non-machine-readable PDFs of drastically varying formats into structured data using AI-powered document understanding—no reliance on fixed templates.
• Intelligent and Scalable Data Extraction
Used MuleSoft IDP, to automatically classify and adapt to different customer PO formats, eliminating the need for one-off configurations or too specific code. This ensures a scalable architecture that can be easily extended to include more customer specific documents.
• Fully Automated Workflow
Delivers end-to-end automation from scanned document to Salesforce order creation, with zero manual intervention.
• Designed for Scalability
Easily handles increasing document volume and supports onboarding of new customers with minimal effort, thanks to flexible, API-driven architecture.
• Built for Maintainability Modular design using Salesforce Flows and MuleSoft APIs enables easy updates, version control, and low-code enhancements without disrupting the end-to-end process.
Business Impact
This use case demonstrates the powerful synergy between Salesforce, MuleSoft, and AI-based Intelligent Document Processing (IDP) to deliver a resilient, scalable, and agent-friendly automation of B2B order intake.
Tangible Benefits:
For the Business:
o Reduced manual workload and errors
o Faster order processing
o High adaptability to customer diversity
For the Frontline Team:
o Seamless experience with zero technical friction
o Quick access to order details and actions via chat
o More time to focus on customer service, not data entry
This is intelligent automation not just for efficiency—but for empowering people.
Use Case 2
Challenge
Solution
Benefits
Use Case 2
This use case showcases how we transformed the manual order processing of a B2B provider specializing in cable management and EMC shielding solutions into a scalable, fully automated system.
By integrating intelligent document processing (IDP), robotic process automation (RPA), and MuleSoft for orchestration, the company significantly reduced manual workload, improved data accuracy, and enabled efficient, around-the-clock processing of unstructured order documents.
By integrating intelligent document processing (IDP), robotic process automation (RPA), and MuleSoft for orchestration, the company significantly reduced manual workload, improved data accuracy, and enabled efficient, around-the-clock processing of unstructured order documents.
Challenge
The company has so far been processing customer orders manually:
• Customers send informal orders via email in unstructured PDF documents
• These orders must be manually typed by employees and entered into an internal ERP system (ICM)
• The process is time-consuming, error-prone, and scales poorly
• Processing capacity is limited by manual steps and limited resources
• Customers send informal orders via email in unstructured PDF documents
• These orders must be manually typed by employees and entered into an internal ERP system (ICM)
• The process is time-consuming, error-prone, and scales poorly
• Processing capacity is limited by manual steps and limited resources
Solution
An automated system for processing incoming order documents:
MuleSoft Anypoint API:
Orders received as email attachments are retrieved and provided via an API
Intelligent Document Processing (IDP):
Incoming orders are automatically read and structured
Confidence-Based Review Process:
If uncertainty is detected (e.g., <80% accuracy), a "manual review" step is triggered
Batch-Based Processing:
Email reading, manual post-processing, and execution in the CRM by the robot are fully decoupled and executed independently (in parallel)
MuleSoft Object Store:
Seamless integration of the individual steps—order ingestion, manual review, and RPA execution—is handled via the MuleSoft Object Store
Robotic Process Automation (RPA):
A virtual robot enters the data provided by the IDP into the ERP system
Logging and Traceability:
Process data is logged as extensively as possible—within the RPA system and to a limited extent in MuleSoft flows
MuleSoft Anypoint API:
Orders received as email attachments are retrieved and provided via an API
Intelligent Document Processing (IDP):
Incoming orders are automatically read and structured
Confidence-Based Review Process:
If uncertainty is detected (e.g., <80% accuracy), a "manual review" step is triggered
Batch-Based Processing:
Email reading, manual post-processing, and execution in the CRM by the robot are fully decoupled and executed independently (in parallel)
MuleSoft Object Store:
Seamless integration of the individual steps—order ingestion, manual review, and RPA execution—is handled via the MuleSoft Object Store
Robotic Process Automation (RPA):
A virtual robot enters the data provided by the IDP into the ERP system
Logging and Traceability:
Process data is logged as extensively as possible—within the RPA system and to a limited extent in MuleSoft flows
Benefits
Time Savings: Significant reduction in manual data entry
Error Reduction: Automated extraction and validation improve data quality
Scalability: High performance even with large order volumes
Increased Efficiency: The robot can autonomously process orders outside of business hours
Cost Reduction: Minimization of manual resources without expensive database infrastructure
Flexibility: Asynchronous processing without system blocking enables continuous operations
Error Reduction: Automated extraction and validation improve data quality
Scalability: High performance even with large order volumes
Increased Efficiency: The robot can autonomously process orders outside of business hours
Cost Reduction: Minimization of manual resources without expensive database infrastructure
Flexibility: Asynchronous processing without system blocking enables continuous operations
Use Case 3
IDP
Benefits
Use Case 3
This Intelligent Document Processing (IDP) use case includes thousands of PDF delivery notes that are received via email annually and must be processed to update inventory in the ERP system and generate invoices for customers. While the delivery notes are consistent for each supplier, they vary significantly between different suppliers.
Therefore the process previously required significant manual effort and was prone to errors.
Therefore the process previously required significant manual effort and was prone to errors.
IDP
Intelligent Document Processing (IDP) played a central role in automating the processing of thousands of PDF delivery notes that arrived via email from various suppliers. Here’s how:
1. Document Ingestion
The system automatically monitors a dedicated mailbox and retrieves incoming PDF delivery notes.
2. Document Classification
Using machine learning, the IDP solution identifies the document type (delivery note) and recognizes the supplier — even if layout, formatting, or structure varies significantly.
3. Intelligent Data Extraction
Key data fields are extracted using a combination of OCR and AI:
- Delivery date
- Material numbers and quantities
- Packaging and weight
- Sender and recipient addresses
- Total cost and customs fees
The system is trained to handle variations in layout, language, and field positioning between suppliers.
4. Data Validation & Enrichment
Extracted data is automatically validated against business rules (e.g., cross-checking material numbers with the ERP).
Where needed, contextual enrichment (e.g., assigning internal item codes) is performed.
5. Integration with ERP System
Clean, validated data is pushed directly into the ERP system:
- Inventory levels are updated
- Invoice records are prepared
- Delivery confirmations are triggered if needed
Benefits
Key Benefits of the IDP Solution
Scalability: Capable of processing over 12,000 documents annually without the need for additional human resources.
Flexibility: Adapts to a wide range of delivery note formats from various suppliers, regardless of layout or structure.
Accuracy: Dramatically reduces manual data entry errors by leveraging AI-powered data extraction.
Efficiency: Saves more than 2,100 hours of manual work per year, accelerating inventory updates and invoice creation.
Compliance: Ensures that critical information such as customs and regulatory data is consistently and accurately captured.
Operational Impact: 12,000+ documents processed annually, 2,100+ labor hours saved, 1,200+ tons of cast iron tracked through automated workflows.
Scalability: Capable of processing over 12,000 documents annually without the need for additional human resources.
Flexibility: Adapts to a wide range of delivery note formats from various suppliers, regardless of layout or structure.
Accuracy: Dramatically reduces manual data entry errors by leveraging AI-powered data extraction.
Efficiency: Saves more than 2,100 hours of manual work per year, accelerating inventory updates and invoice creation.
Compliance: Ensures that critical information such as customs and regulatory data is consistently and accurately captured.
Operational Impact: 12,000+ documents processed annually, 2,100+ labor hours saved, 1,200+ tons of cast iron tracked through automated workflows.
Use Case 4
The Challenge
Solution
Benefits
Use Case 4
This use case highlights a successful automation project we delivered for a leading company in the metering industry. The client was struggling with the manual processing of thousands of documents each month, resulting in high operational costs and delayed data entry.
We implemented a scalable solution using MuleSoft’s Anypoint Platform, Intelligent Document Processing (IDP), and integrated AI models to extract and process critical data automatically. The result: streamlined operations, over €60,000 in annual cost savings, and a new revenue-generating product for our client in the area of document automation.
We implemented a scalable solution using MuleSoft’s Anypoint Platform, Intelligent Document Processing (IDP), and integrated AI models to extract and process critical data automatically. The result: streamlined operations, over €60,000 in annual cost savings, and a new revenue-generating product for our client in the area of document automation.
The Challenge
A leading metering company was facing significant inefficiencies in processing thousands of documents received via email each month. Key information such as meter readings, serial numbers, addresses, and invoice values had to be manually entered into the ERP system—a time-consuming process costing the company over €120,000 annually.
This manual workflow also introduced:
• Frequent delays in data entry
• Increased risk of late payments and related dunning fees
• Limited scalability in handling growing document volumes
This manual workflow also introduced:
• Frequent delays in data entry
• Increased risk of late payments and related dunning fees
• Limited scalability in handling growing document volumes
Solution
To eliminate manual processing, we implemented an automated document processing solution powered by:
• MuleSoft IDP (Intelligent Document Processing)
• External AI model integration via Anypoint for smart data extraction and classification
The solution enabled end-to-end automation—emails are now ingested, documents are analyzed in real time, and key data points are automatically populated into the ERP system.
The automated platform has been so effective that the company now offers this solution as a product to its own customers.
• MuleSoft IDP (Intelligent Document Processing)
• External AI model integration via Anypoint for smart data extraction and classification
The solution enabled end-to-end automation—emails are now ingested, documents are analyzed in real time, and key data points are automatically populated into the ERP system.
The automated platform has been so effective that the company now offers this solution as a product to its own customers.
Benefits
• €60,000 in annual cost savings through automation
• €750,000 in additional revenue by offering the solution as a product
• 500,000+ documents processed annually, with capacity to scale further
• Improved processing speed and accuracy
• Reduced risk of late fees due to delayed entries
• €750,000 in additional revenue by offering the solution as a product
• 500,000+ documents processed annually, with capacity to scale further
• Improved processing speed and accuracy
• Reduced risk of late fees due to delayed entries
"For us, transforming your business is not just a project, but a joint journey based on reliable partnership!"
Tobias Stein
Director
Process Intelligence + automation
tobias.stein [at] lpdg.io
"For us, transforming your business is not just a project, but a joint journey based on reliable partnership!"
Tobias Stein
Director
Process Intelligence + automation
tobias.stein [at] lpdg.io