How To Extract Data From Packing List With AI And Intelligent Document Processing (Complete Guide)

The world of eCommerce revolves around many types of documents. Some of the major documents include packing lists, purchase orders, bills of lading, sea waybills, etc. Now, extracting data from packing lists is another challenge that requires a proper technological approach. But the question still remains: how to extract data from packing lists?

Utilizing technology such as OCR, Intelligent Document Processing, and the new tech revolution such as AI has made data extraction from packing lists very easy, accurate, and efficient for businesses.

However, handling packing lists manually is a slow and error-prone task, especially when you’re dealing with hundreds or thousands of shipments every month. The risk of human error is high and can lead to serious business setbacks.
In this blog, we will explain in detail how to extract data from packing lists using AI and IDP, how packing lists and SKU lists are two different documents, what challenges you may face with packing list data extraction, top tools for packing list data extraction, and how tools like AlgoDocs offer an effective solution for packing list data extraction.

A packing list is a document that provides details of the products lined up for shipment. This includes details such as product names, product descriptions, product quantities, weight, dimensions, number of boxes, and other relevant information.
The packing list is usually prepared by the seller or the warehouse and is included with the shipment process. It serves as a reference for everyone involved in the shipping process, including logistics providers, customs officers, and the buyer.
Packing lists are typically generated in digital formats such as PDFs, spreadsheets, or Word documents, but they are often printed or scanned, especially in traditional supply chain settings. Because of this, the quality and format of the document can vary significantly.

In the eCommerce industry, the packing list is not just a formality—it’s a crucial document that supports the entire order fulfillment process. Here’s why it matters:

1. Order Verification:
   • Helps verify that the correct items and quantities are shipped.
   • Prevents order mismatches and customer complaints.
2. Inventory Management:
   • Supports stock tracking and inventory control.
   • Assists in identifying discrepancies between what was picked and what was shipped.
3. Logistics Coordination:
   • Enables warehouse teams and shipping providers to organize packages efficiently.
   • Streamlines dispatch and delivery operations.
4. Customs and Regulatory Compliance:
   • Helps international shipments clear customs smoothly by providing product details.
   • Ensures compliance with import/export regulations.
5. Returns and Disputes Handling:
   • Used to confirm the contents of returned shipments.
   • Acts as proof in case of disputes regarding missing or damaged items.

SKU list – A SKU list is created and maintained at the individual business level, which shows how many products are available in their inventory to sell in the market. This list contains product details such as product title, product dimensions, weight, SKU ID, product image URL, and other information. Various types of businesses use different types of SKU lists, which can be for their online or offline business inventory.

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Packing list – A packing list is generated to list all items that will be shipped by the shipping or logistics company. A packing list includes various information such as the number of items to be shipped, their quantity, number of boxes, tracking number, etc. It basically serves as a receipt that indicates the number of detailed items.

Packing list data extraction means extracting key-value information from a packing list document with the help of automated tools such as packing list OCR, intelligent document processing tools, or AI and ML-based tools. A typical packing list document contains details such as item descriptions, quantities, product dimensions and weights, sender and receiver address details, shipping dates, and delivery terms.

These extracted data from packing lists are later used for record-keeping, tracking, billing, and other business activities by businesses or shipping companies.

Previously, packing list data extraction used to be a tedious process as most of the data extraction was done manually by humans. The manual process took more time and the possibility of human error was high. This resulted in many setbacks for businesses due to slower extraction speed, inaccuracy in extracted data, increased extraction costs, and other challenges.
But the modern data extraction approach has shifted from manual methods to AI-based methods, which have significantly improved workflow efficiency for businesses.

While packing list documents are major documents for shipping and logistics businesses, extracting and organizing data accurately remains a challenge due to:

1. Document Format Variation:

A packing list document can come in various formats or layouts. Every logistics provider designs packing list formats in their own way. This could be due to region, language, preference, business type, or other external factors.

2. Unstructured or Poorly Formatted Data:

Packing list documents are often generated in unstructured formats, and extracting data from these documents creates many challenges.

3. Scanned or Low-Quality Documents:

Document quality is another issue. Poorly scanned documents, documents of very low quality, and skewed fonts create many problems in data extraction.

4. High Volume of Documents:

While extracting data from one or two packing list documents seems feasible with manual methods, extracting 100 or sometimes 1000 documents at once isn’t possible manually. It’s slow, full of errors, and inefficient.

5. Language Barriers:

Multilingual packing list documents create hurdles in data extraction. Extracting data from regional language documents requires specific customization in OCR and data extraction tools. Manual methods require human extractors to have bilingual skills, which are hard to find.

6. Error-Prone Manual Processes:

Manual data extraction methods are full of errors. Human error can lead to serious consequences like data inaccuracy and mismatched information.

AI and Intelligent Document Processing (IDP) use advanced technologies such as machine learning, template-based OCR, and natural language processing (NLP) to automate data extraction from packing lists. With AI and IDP, you can:

Automatic Recognition of Document Structure:

With platforms like Intelligent Document Processing and AI, it becomes easier to detect and identify document types and layouts, allowing faster and more accurate data extraction.

High-Quality Accurate OCR:

While legacy OCR systems lack accuracy, modern OCR integrated with AI offers high-quality, accurate extraction from unstructured documents such as scanned image PDFs, handwritten notes, etc.

Multi-Language Support:

Modern businesses operate globally, and documents may contain regional languages. AI and IDP can extract data efficiently from regional-language packing lists.

Data Classification and Tagging:

With modern OCR tools, you can classify and tag specific data, tables, lines, fields, or rows. Technologies like Zonal OCR and IDP with AI capabilities can perform these tasks, saving time and cost.

Machine Learning and Continuous Improvement:

AI-based tools are trained on large datasets, improving their data extraction capabilities and delivering accurate, fast results.

Real-Time Processing:

AI and IDP tools process documents in real-time, far faster than traditional or manual methods. You can process 100 or more documents with just a few clicks.

Integration With Other Systems:

Extracted data can be sent directly to your ERP, CRM, or warehouse management system.

Gen AI for Easy Data Extraction:

Some AI tools can be complex for non-technical users. But the introduction of Gen AI has made packing list data extraction much easier. One simple prompt is enough to extract data from documents.

Using AI and IDP, businesses can save countless hours, improve accuracy, and scale operations with confidence.

• AlgoDocs: The best tool for automating packing list data extraction. Built with advanced AI and ML technology, AlgoDocs offers accurate and fast extraction. Its Gen AI feature allows even non-technical users to extract data easily. It integrates with third-party tools and supports PDFs, scanned images, and handwritten notes.
• Klippa: Extracts data from PDFs, handwritten notes, and more. Can be integrated with third-party tools.
• Nanonets: An enterprise OCR data extraction tool that works with invoices, bills, and packing lists. Integrates with external platforms.
• Affinda: Extracts data from invoices, bills, and logistics documents. Known for its user-friendly pricing model.
• KlearStack: Automates data extraction from various documents, including bills of lading, purchase orders, invoices, and packing lists.

AlgoDocs is an AI-powered document processing platform that simplifies packing list data extraction. It’s user-friendly, fast, and customizable. Key benefits include:

1. No Technical Skills Required:
   • Designed for business users without coding knowledge.
2. Flexible Input Formats:
   • Supports PDFs, scanned images, Excel, Word, and more.
3. Advanced OCR and AI Models:
   • Works even with low-quality scans and complex layouts.
4. Custom Extraction Templates:
   • Allows custom rule creation and field extraction for multi-supplier workflows.
5. Real-Time Document Processing:
   • Instantly processes uploads and delivers structured data.
6. Secure and Cloud-Based:
   • Encrypted data, role-based access, and cloud storage.
7. Easy Integration:
   • Works with Zapier, Google Sheets, ERPs, CRMs, and more.
8. Smart Validation and Error Detection:
   • Flags missing or mismatched data automatically.
9. Cost-Effective and Scalable:
   • Pay-as-you-go model for all business sizes with easy scalability.

AlgoDocs is especially customized for eCommerce companies, logistics providers, freight forwarders, and manufacturers who need fast, accurate, and automated packing list data extraction.

As discussed above, packing lists are essential documents that ensure smooth and accurate delivery in eCommerce and logistics. But extracting data from these documents comes with many challenges.
Modern AI and IDP tools have revolutionized document processing. With features like OCR, machine learning, and automation, these tools make packing list data extraction faster, more accurate, and highly scalable.
If you’re looking to improve your operations, now is the time to explore how to extract data from packing lists using AI-powered solutions. Start with AlgoDocs and experience the difference for yourself.

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