Guide to Purchase Order OCR — Extract data from Purchase Order

What is Purchase Order Processing?

Definition of Purchase Orders

A purchase order (PO) is a formal document generated by a buyer and sent to a supplier to initiate a purchase transaction. It contains critical details that outline the specifics of the transaction, including:

• A detailed list of the goods or services requested.
• The quantities needed.
• The agreed-upon prices for each item or service.
• Delivery schedules, including timelines and locations.
• Payment terms, such as methods and deadlines for payment.

Once the supplier accepts the purchase order, it becomes a legally binding agreement, ensuring both parties are accountable for their obligations. The buyer is assured of receiving the specified goods or services, while the supplier is guaranteed payment under the agreed terms. This mutual agreement forms the cornerstone of efficient and reliable procurement processes in modern businesses.

TL;DR

This article examines the challenges of processing purchase orders and demonstrates how using Large Language Models (LLMs) can enable new ways of handling purchase order data extraction.

If you wish to skip directly to the solution section, where you can see how Unstract uses AI to extract data from various types of purchase orders, click here.

Purpose of Purchase Orders

Purchase orders serve a variety of purposes that make them indispensable in business transactions. Below are some of their key roles:

1. Clarity and Communication
   Purchase orders provide a clear and comprehensive outline of the buyer’s needs, reducing the risk of misunderstandings or discrepancies between buyers and suppliers. By explicitly detailing product specifications, quantities, and timelines, they act as a reference point for both parties throughout the transaction.
2. Budget Management
   For businesses, managing expenditures effectively is critical for financial health. POs help organizations plan and monitor their budgets by clearly outlining expected costs. They allow procurement teams to assess spending commitments against available budgets, ensuring no overspending occurs.
3. Legal Protection
   As legally binding documents, POs offer both buyers and suppliers a layer of legal protection. If disputes arise—such as discrepancies in the quality of goods delivered or delays in delivery—the purchase order serves as concrete evidence of the agreed terms.
4. Record-Keeping
   Purchase orders create a documented trail of all transactions, which is invaluable for record-keeping. These records are critical during audits, tax filing, and financial reporting, as they provide an accurate history of all purchases made by the business.
5. Efficiency and Workflow Optimization
   By formalizing the procurement process, purchase orders streamline workflows. They provide structure to the purchasing process, making it easier for teams to track orders, approve budgets, and reconcile invoices with minimal delays or errors.

Practical Example of Purchase Orders in Action

Consider a retail chain needing to restock its inventory for an upcoming sale. To ensure timely delivery and clarity, the procurement team issues a purchase order to the supplier, specifying the following:

• Items required: A list of products such as clothing, footwear, or accessories.
• Quantities: The exact number of units for each item.
• Prices: The agreed-upon rates per unit.
• Delivery deadlines: Timelines to ensure the stock arrives before the sale begins.
• Payment terms: Details on when and how the supplier will be paid, such as net 30 days after delivery.

This purchase order ensures that the supplier understands the retailer’s requirements and delivers accordingly. For the retailer, it provides a document trail that helps in budget planning, invoice matching, and resolving potential disputes.

Why is Purchase Order Processing a Critical Business Process?

1. Importance of Purchase Orders in Supply Chain and Procurement Workflows
In supply chain and procurement workflows, purchase orders play a pivotal role in ensuring the smooth flow of goods and services. They act as the backbone of these workflows by:

• Defining what is needed, when, and at what cost.
• Acting as a point of reference for both buyers and suppliers to avoid miscommunication.
• Supporting the alignment of procurement activities with organizational goals.

Key reasons why purchase order processing is critical include:

• Improved Financial Control:
  Purchase orders establish spending limits and help prevent unauthorized purchases. This is particularly important for large organizations where multiple departments may have independent procurement needs.

Example: A manufacturing company using POs ensures that raw material purchases stay within budget and align with production schedules.

• Better Supplier Relationships:
  Clear and accurate POs build trust with suppliers, as they provide explicit details about expectations, reducing conflicts and delays.
  Example: A supplier receiving detailed POs with accurate quantities and delivery timelines is more likely to fulfill orders promptly.
• Enhanced Auditability and Compliance:
  POs create a documented trail of all transactions, which is essential for audits and regulatory compliance.
  Example: During a financial audit, POs provide evidence of purchases, ensuring transparency.
• Efficient Inventory Management:
  By clearly defining what is being purchased and when it will be delivered, POs help businesses avoid overstocking or stockouts.

2. Benefits of Automating Purchase Order Data Extraction
Traditional, manual PO processing methods often involve extensive time and effort, with room for errors and inefficiencies. Automating purchase order data extraction provides significant benefits:

• Time Efficiency: Automation processes POs within seconds, freeing employees to focus on strategic tasks.
• Reduced Errors: Automated systems extract data accurately, minimizing issues caused by manual entry.
• Scalability: Automated solutions handle high volumes of POs, ensuring smooth operations during peak periods.
• Data Integration: Extracted data can be seamlessly integrated into accounting, ERP, and supply chain systems for real-time updates.

For instance, an e-commerce company using automated PO processing can manage thousands of orders daily, ensuring accurate data flow between procurement and inventory systems.

Challenges in Purchase Order Processing (Automation)

Despite the clear advantages, automating purchase order processing comes with specific challenges:

1. Variability in Formats and Layouts Across Vendors
Vendors often have unique purchase order formats, which can include:

• Different table structures for line items.
• Variations in the placement of critical details like delivery dates or payment terms.
• Custom numbering systems for purchase orders.

This variability makes standardization difficult, requiring automation tools to be adaptable.
Example: A retail chain sourcing products from multiple suppliers might receive POs in a mix of digital, handwritten, or scanned formats, each requiring a tailored approach.

2. Complexity in Extracting Data from Scanned or Poorly Formatted Documents
Many organizations still rely on scanned or printed purchase orders. These documents may have:

• Low-quality scans: Blurry or faded text, skewed images, or poor alignment.
• Handwritten Annotations: Difficult to process with standard OCR tools.
• Mixed Content: A combination of text, tables, and checkboxes.

Extracting accurate data from such documents requires advanced pre-processing techniques, including:

• Noise Removal: To clean up faded or blurred text.
• Skew Correction: To align tilted text properly.
• Intelligent Character Recognition (ICR): To interpret handwritten notes.

Example: An automotive company dealing with handwritten POs from smaller suppliers may face delays in processing due to the difficulty of interpreting handwriting.

3. Integration Challenges
Integrating automated PO processing tools with existing systems like ERPs, CRMs, or accounting software can be complex. Compatibility issues may arise, causing data silos or duplicate entries.

Example: A logistics company adopting PO automation must ensure seamless integration with its inventory management and billing systems to avoid disruptions in operations.

4. Compliance with Evolving Regulations
Procurement is a highly regulated domain, and laws vary across regions. Ensuring compliance with these ever-changing regulations can be challenging.

Example: An international company must extract and validate data against the tax codes and environmental policies of different countries, requiring robust automation tools that adapt to these variations.

Purchase order processing is the cornerstone of efficient procurement and supply chain management. While traditional methods rely heavily on manual effort, the adoption of automation tools for purchase order data extraction addresses key challenges like format variability, poor document quality, and regulatory compliance.

By leveraging advanced technologies such as OCR, AI, and machine learning, businesses can:

• Streamline workflows.
• Enhance accuracy.
• Reduce processing times.
• Build stronger supplier relationships.

In a fast-paced, data-driven world, automating purchase order processing is no longer a luxury but a necessity. Whether you’re managing hundreds or thousands of POs, automation ensures your operations remain efficient, scalable, and future-ready. Businesses that adopt these tools today will be well-positioned to tackle tomorrow’s procurement challenges with ease.

The Role of AI and LLMs in Transforming Unstructured Data into Actionable Insights

In today’s data-driven world, the sheer volume of unstructured data generated by businesses poses significant challenges. Documents like purchase orders, invoices, tax filings, and contracts often come in various formats—scanned PDFs, handwritten notes, or unstructured digital files—making manual data extraction time-consuming and error-prone. This is where Artificial Intelligence (AI) and Large Language Models (LLMs) revolutionize the way businesses process unstructured data.

Overview of AI and LLM Capabilities

AI and LLMs are transforming the landscape of document processing by leveraging advanced algorithms to extract, interpret, and organize data with remarkable accuracy. Key capabilities include:

1. Contextual Understanding
   Unlike traditional systems that rely on rigid templates, AI-powered models understand the semantic context of documents. This allows them to identify relationships between fields, comprehend hierarchical structures, and extract meaningful data regardless of layout variations.
2. Pattern Recognition
   AI models excel at recognizing patterns in text, enabling them to identify critical details such as dates, names, or item descriptions even in complex or inconsistent document layouts.
3. Adaptability to Document Variability
   AI solutions are designed to handle diverse document formats, including scanned images, PDFs, and digital forms. They adapt to irregular layouts, poor-quality scans, or multilingual content without requiring template updates.
4. Automation and Scalability
   With the ability to process large volumes of documents in parallel, AI-powered systems drastically reduce the time and effort needed for manual data entry. They also scale effortlessly to meet enterprise-level demands.
5. Intelligent Pre-Processing
   AI enhances the quality of input data through techniques like noise reduction, de-skewing, and contrast adjustment. This ensures that even low-quality scanned documents are accurately processed.

AI/LLMs in Processing Purchase Orders

Purchase orders, though standardized within organizations, often vary significantly between vendors and suppliers. Manual processing of these documents can be inefficient and error-prone, especially when dealing with high volumes. AI and LLMs streamline this process by extracting critical details from purchase orders with speed and precision.

Key Applications of AI in Purchase Order Processing

1. Extraction of Key Details
   AI-powered systems can automatically identify and extract essential data points from purchase orders, including:
   • Vendor Name: Recognizes and extracts supplier details such as names, addresses, and contact information, even if they are scattered across the document.
   • Item Descriptions: AI models interpret line items, capturing product names, quantities, and unit prices regardless of formatting.
   • Total Amounts: Calculates totals, taxes, and discounts by understanding the document’s structure and context.
   • Payment Terms: Extracts information about due dates, payment methods, and terms of service.
2. Handling Variability in Layouts
   Purchase orders from different suppliers often have unique formats, making it difficult for template-based systems to process them efficiently. AI-driven models adapt dynamically to these variations, ensuring consistent data extraction without the need for constant reconfiguration.
3. Error Detection and Validation
   AI systems validate extracted data by cross-referencing it with predefined business rules or databases. For instance, they can flag discrepancies in pricing or quantities, ensuring that the data is accurate before further processing.
4. Integration with Workflows
   By integrating with existing procurement and ERP systems, AI-powered solutions enable seamless data flow. Extracted information is directly transferred into structured formats like JSON or CSV, ready for analysis or action.

Real-World Application Example

Imagine a multinational retail chain receiving purchase orders from hundreds of suppliers in varying formats. A manual approach would involve significant time and resources to extract vendor details, item descriptions, and payment terms for each document. By implementing an AI-based solution:

• The system scans and processes each purchase order, extracting critical details with over 95% accuracy.
• Data inconsistencies, such as mismatched totals, are flagged for review.
• Structured outputs, such as JSON, are generated and automatically uploaded to the company’s ERP system for further processing.

Benefits of AI/LLMs in Purchase Order Data Extraction

1. Efficiency: AI automates repetitive tasks, reducing processing times from hours to minutes.
2. Scalability: Handles thousands of documents simultaneously without compromising accuracy.
3. Cost Savings: Eliminates the need for extensive manual data entry, reducing labor costs.
4. Improved Accuracy: Minimizes human errors and ensures data consistency.
5. Enhanced Decision-Making: By providing structured, real-time data, AI enables businesses to make faster, data-driven decisions.

The integration of AI and LLMs into purchase order processing marks a significant leap forward for businesses, turning a traditionally tedious task into a streamlined, error-free operation. By leveraging these technologies, organizations can optimize their procurement workflows, improve supplier relationships, and achieve greater operational efficiency.

Brief Introduction to Unstract and How it Leverages AI in Structuring Unstructured Data

In a business environment where efficiency and accuracy are paramount, Unstract emerges as a game-changing platform that simplifies the transformation of unstructured data into actionable insights.

Designed as a no-code, AI-powered tool, Unstract specializes in processing and structuring data from complex documents like purchase orders, invoices, and tax forms. By leveraging advanced technologies such as Artificial Intelligence (AI) and Large Language Models (LLMs), Unstract offers unparalleled capabilities for automating the extraction and structuring of data from unstructured documents.

Overview of Unstract’s Capabilities for Purchase Order Processing

1. Comprehensive Document Handling

Unstract excels at handling diverse document types, including scanned PDFs, fillable forms, and handwritten documents. Its versatility ensures businesses can process various document formats without requiring multiple tools or manual intervention.

• Adaptability to Formats: Whether dealing with structured purchase orders or scanned handwritten invoices, Unstract adapts dynamically to different layouts and styles, delivering consistent and reliable results.
• Support for Complex Layouts: It recognizes tables, nested fields, multi-column formats, and overlapping elements, ensuring no data is overlooked. For example, Unstract can extract itemized lists from a purchase order while maintaining the table structure for downstream processing.

Batch Processing: Unstract’s scalable infrastructure allows simultaneous processing of multiple documents, making it ideal for organizations handling high volumes of purchase orders. This capability significantly reduces processing times while maintaining accuracy.

2. AI-Powered Data Structuring

Unstract leverages AI and LLMs to transform raw, unstructured data into well-organized formats like JSON, CSV, or Excel, making it ready for integration with business systems.

• Context-Aware Analysis: Unlike traditional tools that rely on rigid templates, Unstract uses AI to understand the context of a document. It identifies relationships between fields, such as linking a supplier’s name to corresponding payment terms or item descriptions. This ensures that extracted data retains its meaning and relevance
• Adaptability: The platform continuously learns from new documents, improving its accuracy and efficiency over time. This means Unstract becomes more effective with every use, adapting to the unique requirements of different businesses and document formats.

3. Seamless Integration with Procurement Workflows

One of Unstract’s standout features is its ability to integrate seamlessly into existing procurement workflows, ensuring that data extraction aligns with broader business processes.

• Real-Time API Integration: Unstract’s API allows businesses to feed structured data directly into ERP, CRM, and financial systems. For example, extracted purchase order details can be instantly uploaded to a company’s accounting software for faster invoice matching and payment processing.
• Customizable Outputs: The platform supports tailored outputs based on specific business needs. Whether you require a detailed breakdown of itemized costs or a summarized report of vendor transactions, Unstract can deliver the exact data format required.
• Workflow Automation: By automating the extraction and structuring of purchase order data, Unstract eliminates manual steps, reducing bottlenecks in procurement workflows and enabling faster decision-making.

Unstract is an open-source no-code LLM platform to launch APIs and ETL pipelines to structure unstructured documents. Get started with this quick guide.

How Unstract Automates Purchase Order Processing

1. Intelligent Purchase Order OCR with LLMWhisperer

Unstract integrates with LLMWhisperer, a tool specifically designed to optimize document data for LLMs. This integration enhances the platform’s ability to pre-process purchase orders, ensuring that the data extracted is clean, accurate, and structured.

• Noise Reduction: LLMWhisperer removes artifacts like smudges, stains, and skewed text, improving the quality of scanned purchase orders.
• Layout Preservation: It retains the structure of purchase orders, ensuring that tables, line items, and total amounts are extracted in their original context.
• Dynamic Mode Switching: Depending on the document type, LLMWhisperer automatically adjusts between OCR and text extraction modes, optimizing the results.

2. Advanced Data Extraction

Unstract uses AI to identify and extract critical details from purchase orders, such as:

• Vendor and buyer information.
• Itemized product lists, including quantities and unit prices.
• Payment terms and due dates.
• Total amounts, taxes, and discounts.
  By leveraging machine learning, the platform accurately processes even poorly formatted or handwritten documents.

3. Validation and Error Detection

Unstract incorporates rule-based validation checks to ensure that extracted data matches business requirements. For example, it can cross-verify extracted totals with line items or check payment terms against predefined thresholds, reducing the risk of errors.

4. Deployment as APIs

Unstract allows businesses to deploy their data extraction workflows as APIs, enabling seamless integration with procurement systems. This feature ensures that extracted purchase order data flows directly into ERP or accounting software without manual intervention, accelerating payment processing and financial reporting.

The Role of Unstract in Business Efficiency

1. Improved Accuracy and Consistency

Unstract minimizes human errors by automating data extraction and validation. This consistency ensures that purchase order data is always accurate, reducing delays caused by manual discrepancies.

2. Scalability for High-Volume Operations

The platform’s ability to process thousands of purchase orders simultaneously makes it an ideal solution for large enterprises. Its scalability ensures that businesses can maintain operational efficiency even during peak periods.

3. Cost and Time Savings

By automating manual tasks, Unstract reduces labor costs and frees up employee time for strategic activities. For instance, procurement teams can focus on supplier negotiations instead of spending hours processing purchase orders.

4. Enhanced Supplier Relationships

With faster and more accurate purchase order processing, businesses can ensure timely payments and efficient communication with suppliers. This fosters stronger relationships and long-term collaboration.

Unstract is redefining purchase order processing by combining advanced AI, seamless workflow integration, and intelligent automation. Its ability to handle diverse document types, extract critical data points, and deliver structured outputs positions it as an indispensable tool for modern businesses.

By leveraging Unstract, organizations can streamline procurement workflows, reduce errors, and unlock new levels of operational efficiency, ensuring they stay ahead in today’s competitive marketplace.

Introduction to LLMWhisperer — The Purchase Order OCR

In the digital transformation era, processing unstructured documents has become a cornerstone of efficient business workflows. LLMWhisperer is a groundbreaking technology that prepares complex documents—like invoices, purchase orders, and forms—for seamless consumption by Large Language Models (LLMs). LLMWhisperer bridges the gap between unstructured data and machine-readable formats, enabling businesses to unlock insights from challenging document layouts with unparalleled precision.

Key Features of LLMWhisperer:

1. Layout Preservation: Maintains the structure of multi-column layouts, forms, and tables, ensuring downstream LLMs can extract insights with context and accuracy.
2. Advanced Checkbox and Radio Button Recognition: Handles form-specific elements like checkboxes and radio buttons, providing clear, actionable data.
3. Auto Mode Switching: Automatically toggles between OCR and text extraction modes, ensuring optimal results across document types.
4. Token Compaction: Minimizes unnecessary data, reducing processing costs while maintaining essential content for analysis.
5. Pre-Processing Capabilities: Enhances document quality using advanced filters and adjustments for noisy or scanned inputs.

To see LLMWhisperer in action, users can explore the LLMWhisperer Playground. This free tool processes up to 100 pages daily, allowing you to test its capabilities with real documents effortlessly.

Live coding session on data extraction from a scanned PDF form with LLMWhisperer

You can also watch this live coding webinar where we explore all the challenges involved in scanned PDF parsing. We’ll also compare the capabilities of different PDF parsing tools to help you understand their strengths and limitations.

Example: Purchase Order OCR Processing in LLMWhisperer Playground

Test Document: A purchase order with complex tabular data:

Using the LLMWhisperer Playground:
Upload the purchase order to the LLMWhisperer Playground, and the platform works its magic.

Layout Preservation:
The tool retains the table structure, ensuring clarity and providing a one-to-one document representation for auditing or analysis. The extracted data can be seamlessly integrated into your LLM data extraction workflow.

Why LLMWhisperer OCR Excels:

1. Retention of Tabular Data: The extracted information mirrors the original layout, ensuring critical relationships between quantities, prices, and totals are preserved.
2. Scalability: Whether processing a single PO or hundreds, the platform handles bulk uploads with the same precision.
3. Interactive and Intuitive: The Playground provides an easy-to-use interface for testing and validating document processing capabilities in real-time.

Try LLMWhisperer Playground Today

Experience the full potential of LLMWhisperer by visiting the Playground. Upload your invoices, purchase orders, or other documents and see how efficiently layouts, tables, and critical data points are preserved and extracted. Unlock the future of document automation with LLMWhisperer!

Steps in Unstract to Extract Data from Purchase Orders

Unstract simplifies the process of extracting data from purchase orders (POs) by combining its intuitive platform with advanced technologies like OpenAI, embeddings, vector databases, and LLMWhisperer. Here’s a detailed guide to setting up and configuring Unstract for seamless purchase order data extraction.

Step 1: Setting Up Unstract

To begin extracting data from purchase orders, follow these steps:

1.1 Sign Up for Unstract

• Visit the Unstract platform and create an account. The registration process is straightforward, providing access to essential tools, including Prompt Studio and LLMWhisperer.

1.2 Configure OpenAI for LLM Integration

• Configure the LLM by navigating to Settings → LLMs.
• Click New LLM Profile, choose the LLM provider, and enter the required details prompted by the interface.
• Finalize your LLM profile for seamless integration with Unstract.

1.3 Set Up Embeddings

Embeddings are essential for mapping and analyzing text within documents, providing a foundation for intelligent data retrieval.

• Navigate to Settings → Embedding Profiles.
• Click New Embedding Profile, select the embeddings provider, and configure the profile by following the prompts.

1.4 Connect a Vector Database

A vector database stores and retrieves embeddings, ensuring that extracted data is well-organized and easily accessible for future queries.

• Go to Settings → Vector DBs.
• Click New Vector DB Profile, select your database type (e.g., PostgreSQL or Pinecone), and configure the necessary details to set up the connection.

1.5 Link a Text Extractor

Unstract’s text extractor ensures raw data from purchase orders is processed accurately.

• Navigate to Settings → Text Extractor.
• Click New Text Extractor, select LLMWhisperer, and enter the API Key to activate it for your account.

Step 2: Extracting Data from Purchase Orders in Prompt Studio

2.1 Create a Prompt Studio Project

• Navigate to Prompt Studio and create a new project for purchase order extraction.
• Name the project (e.g., “Purchase Order Parser”) and describe its purpose.

2.2 Upload Purchase Orders

• Use the Manage Documents section to upload sample purchase orders for testing.
• Include both digital and scanned POs to ensure comprehensive extraction capabilities.

2.3 Select JSON as the Output Format

• In the project settings, set the output format to JSON to ensure structured data extraction.

2.4 Craft Prompts for Key Fields

Define prompts to extract critical fields from the purchase orders. Example configurations:

Field 1 Name: vendor_info
Prompt: “Extract the vendor’s name, address, and contact information from the purchase order.”
Example Output:

Field 2 Name: customer_info
Prompt: “Extract the customer’s name, address, and contact information from the purchase order.”
Example Output:

Field 3 Name: purchase_details
Prompt: “Extract the purchase details, including units, descriptions, unit prices, and amounts, in a tabular format.”
Example Output:

2.5 Run and Validate the Prompts

• Execute the prompts in the Prompt Studio interface.
• Verify the accuracy of the extracted data and ensure the output adheres to the JSON format.
• Observe the magic of structured responses, where all fields—vendor info, customer info, and purchase details—are neatly formatted in JSON.

2.6 Choose an Alternative Format (If required)

• If you need the output in a format other than JSON, such as CSV or XML, select the desired format in the settings.

Export and Deploy the Tool as an API

Export as Tool

• Once the prompts have been validated, click on Export as Tool to convert the project into a reusable tool.
• Assign a name like “Purchase Order Parser Workflow.”

Create a Workflow

• Navigate to Build → Workflows and click New Workflow.
• Drag and drop the exported tool into the workflow area.
• Define:
  • Input: API
  • Output: API

Deploy as an API

• Navigate to Manage → API Deployments and click + API Deployment.
• Provide a name like “Purchase Order Parsing API.”
• Retrieve the API URL and generate an API key for integration.

By following these steps, you can efficiently extract structured data from purchase orders and deploy it as an API for seamless integration with your business workflows.

Step 3: Testing the API via Postman

Once the API is deployed, you can test its functionality using Postman to validate the data extraction workflow for purchase orders.

Configure the POST Request

1. Create a New Request
   • Open Postman and click New Request.
   • Set the request method to POST.
   • In the request field, paste the deployment URL provided by Unstract during the API deployment process.
2. Add Authorization Header
   • Navigate to the Headers tab.
   • Add the following header:
     • Key: Authorization
     • Value: unstract-key YOUR_API_KEY
       (Replace YOUR_API_KEY with the API key generated in the Unstract dashboard.)
3. Set the Body Format
   • Go to the Body tab.
   • Select the form-data option.
   • Add the following key-value pair:
     • Key: files
     • Type: File
     • Value: Upload the scanned purchase order document.

Send the Request

1. Click the Send button to initiate the API call.
2. The API processes the uploaded document and extracts data using the configured prompts.

View JSON Output

• After the request is processed, the API will return the extracted data in structured JSON format.
  Example Output:

{
    "status": "COMPLETED",
    "message": [
        {
            "file": "Purchase-Order-Unstract-test.pdf",
            "status": "Success",
            "result": {
                "output": {
                    "customer_info": {
                        "address": "9090, West river avenue",
                        "city": "Los Angeles",
                        "name": "John Armstrong",
                        "state": "CA",
                        "zip": "92802"
                    },
                    "dates": {
                        "Order Date": "09/04/24",
                        "Start Date": "03/23/2024"
                    },
                    "delivery_details": {
                        "address": {
                            "city": "Los Angeles",
                            "state": "CA",
                            "street": "9090, West river avenue",
                            "zip": "92802"
                        },
                        "company": "Hive view Inc",
                        "name": "Simon Jones"
                    },
                    "po_number": 784993,
                    "purchase_details": [
                        {
                            "Amount ($)": 525.0,
                            "Description": "Stainless Steel 304 Hex Head Screw (M8X35)",
                            "Unit Price ($)": 3.5,
                            "Units": 150
                        },
                        {
                            "Amount ($)": 750.0,
                            "Description": "Stainless Steel 304 Hex Head Screw (M5X30)",
                            "Unit Price ($)": 3.75,
                            "Units": 200
                        },
                        {
                            "Amount ($)": 400.0,
                            "Description": "Mccoy 50 x 8 wooden screw - Black Finish",
                            "Unit Price ($)": 4.0,
                            "Units": 100
                        },
                        {
                            "Amount ($)": 525.0,
                            "Description": "MS Steel 3/4 Inch Screw",
                            "Unit Price ($)": 3.5,
                            "Units": 150
                        },
                        {
                            "Amount ($)": 750.0,
                            "Description": "Pan Slotted Self Tapping Screw",
                            "Unit Price ($)": 3.75,
                            "Units": 200
                        },
                        {
                            "Amount ($)": 400.0,
                            "Description": "SS Round Head Nails",
                            "Unit Price ($)": 4.0,
                            "Units": 100
                        }
                    ],
                    "tax": 402.0,
                    "total_amount": {
                        "value": "3,752.00"
                    },
                    "vendor_info": {
                        "address": "222, River view st.",
                        "city": "Sacremento",
                        "company": "River Park Inc",
                        "email": "info@reverparinc.com",
                        "phone": "(903) 903-8895",
                        "state": "CA",
                        "zip": "90203"
                    }
                }
            },
            "metadata": {
                "source_name": "Purchase-Order-Unstract-test.pdf",
                "source_hash": "b690079a73976ea76d79ef9d32f00f0ab67fdf875777013e122f92a67fa1bce8",
                "organization_id": "org_KByxbnDNQojfPwey",
                "workflow_id": "1ec03e16-aca7-4fc7-9e65-c38e6e866620",
                "execution_id": "018c4be1-1bb5-4ff3-9be8-927aa2ad5119",
                "total_elapsed_time": 60.323492,
                "tool_metadata": [
                    {
                        "tool_name": "structure_tool",
                        "elapsed_time": 60.323484,
                        "output_type": "JSON"
                    }
                ]
            }
        }
    ]
}

Demo of Unstract for processing unstrucutred documents

In this webinar, we’ll dive deep into all the features of Unstract and guide you through setting up an ETL pipeline tailored for unstructured data extraction.

Key Advantages of Using Unstract for Purchase Order Processing

1. Automated Data Extraction
   Unstract automates the extraction of data from purchase orders, whether scanned, handwritten, or digitally created. This reduces the need for manual intervention, saving significant time and ensuring accurate extraction of vendor details, itemized lists, and payment terms.
2. Preservation of Layout and Context
   With the help of LLMWhisperer’s layout-preserving technology, Unstract retains the original format of purchase orders, including tables, multi-column layouts, and checkbox selections. This ensures that extracted data is contextually accurate and ready for downstream processing.
3. Integration with Existing Systems
   Unstract integrates seamlessly with accounting software, ERPs, and CRMs, enabling extracted data to flow directly into operational systems. This streamlines workflows across procurement, finance, and analytics departments.
4. Customizable and Scalable Workflows
   Unstract’s no-code environment allows users to configure workflows and prompts tailored to their unique business needs. The platform can scale effortlessly to handle thousands of purchase orders, ensuring peak efficiency during high-volume periods.
5. Improved Compliance and Audit Readiness
   By providing accurate and structured data outputs, Unstract ensures compliance with procurement regulations and simplifies audit preparation. The platform creates a digital trail of all processed documents, promoting transparency and accountability.
6. Cost-Effective Processing
   Unstract’s automated data extraction capabilities reduce the cost of manual labor and prevent errors that could lead to financial discrepancies. With its token optimization feature, the platform also minimizes expenses associated with processing large documents.
7. Enhanced Decision-Making
   By extracting real-time insights from purchase orders—such as vendor performance and pricing trends—Unstract empowers businesses to make data-driven decisions. This leads to better supplier relationships, optimized procurement strategies, and cost savings.

Unstract simplifies the complexity of working with unstructured data. It efficiently extracts and transforms content into actionable formats, providing the foundation for deeper analysis.

Sign up for our free trial if you want to quickly try it out. More information here.