Optical Character Recognition (OCR) software serve a pivotal role in converting document formats, such as PDFs, or physical documents, that are difficult to edit, into editable and searchable formats that can be read by machines. Commonly utilized for extracting text from PDFs and images, these applications transform it into editable formats such as Word, Excel, or plain text files.
By leveraging AI/ML capabilities, OCR software can also automate data extraction from documents/images and convert them in editable format that fit in workflows.
Logistics is a critical function in the supply chain, involving the planning, execution, and control of the movement of goods and materials from one location to another. Logistics processes have traditionally been manual and paper-based, leading to inefficiencies, errors, and delays in operations. However, with the advent of new technologies such as automated retrieval systems, robotic process automation(RPA), intelligent document processing and OCR (optical character recognition), logistics automation is becoming increasingly feasible.
Logistics OCR software should be able to automate the document processing workflow of documents such as Purchase Orders, Freight Invoices, Shipping Labels, Bills of Lading, etc. to reduce the manual workload, eliminate errors, and save time.
Here are some of the best Logistics OCR software in 2024.
Capture data from all logistics-related documents instantly and automate data workflows with Nanonets. Reduce turnaround times and eliminate manual effort.
What is OCR in Logistics?
One of the pivotal hurdles faced by the logistics sector revolves around the management of logistics documents. Purchase orders, invoices, bills of lading, and various other paperwork demand meticulous attention, yet manual processing can be time-consuming, error-prone, and resource-intensive. In this labyrinth of paperwork, the need for a transformative solution is undeniable. One solution is to digitize data from documents using specialized optical character recognition (OCR) software.
One of the biggest advantages of OCR technology is that it can help reduce errors and improve the accuracy of data entry. When humans enter data manually, they are prone to making mistakes such as typos, misspellings, and transpositions. These errors can have serious consequences, particularly in logistics where accuracy is critical for the delivery of goods to stay on time and within budget. OCR technology can help eliminate these errors by automating the data entry process and reducing the need for human intervention.
The Best Logistics OCR Software in 2024
Let’s look at some of the best Logistics OCR software available on the market.
1. Nanonets
Nanonets provides an AI-powered OCR solution for logistics organizations that can accurately extract data from Purchase orders, invoices, and bills of lading, and convert them into structured digital data. It can help logistics organizations improve the accuracy of patient data and reduce manual data entry errors.
Nanonets uses advanced OCR, machine learning image processing, and Deep Learning to extract relevant information from unstructured data.
Pros:
Cons:
- Table capture UI can be better
Build your own custom OCR models or schedule a demo to learn more about Nanonets’ OCR use cases!
2. ABBYY Flexicapture
ABBYY FlexiCapture is an OCR software that can help insurance firms digitize paper-based purchase orders, invoices, and bills of lading. The software can extract data from various document types, including proposal forms, and customer documents, and convert them into structured digital data.
Pros:
- Recognizes images very well
- Easy to store hard copy results in the system
- Seamless integration ERP systems
- Automates data extraction
Cons:
- Initial setup can be difficult and complex
- No ready-made templates
- Difficult to customize
- No resources available
- Could have better integration with RPA solutions
- Low accuracy with low-resolution images/documents
3. ABBYY Finereader
An OCR software that supports PDF file editing. The program can convert image documents into editable electronic formats.
Pros:
- Keyboard-friendly OCR editor
- Exports to multiple formats
- Unique document-compare feature
Cons:
- Lacks full-text indexing for fast searches
- Requires a learning curve
- Can be expensive
- Inability to view the history of document changes
Need an OCR software to extract data from logistics documents? Check out Nanonets in action!
AWS Textract extracts text and other data from scanned documents using machine learning and OCR. It can also identify, and extract data from forms and tables.
Pros:
- Pay-per-use billing model
- Ease of use
Cons:
- Can’t be trained
- Varying accuracy
- Not meant for handwritten documents
5. IBM Datacap
IBM Datacap makes it simple to capture, recognise and classify business documents to extract important information from them. Datacap has a strong OCR engine, and customisable rules. It can work across scanners, mobile devices, multifunction peripherals and fax.
Pros:
- Configures complex applications in data capture
- Scanning mechanism
- Ease of use
Cons:
- Very little online support
- UI could be more intuitive
- Setup can be cumbersome
- Creating a customized flow isn’t straightforward
6. Kofax Omnipage
Kofax Omnipage is a PDF OCR solution that is able to automate high-vloume. It specialises in extracting from tables, matching line items, and smart extraction.
Pros:
- Robust set of tools for enhancing images
- Highly accurate
Cons:
Start using Nanonets for Automation. Try out the various OCR models or request a demo today. Find out how Nanonets’ use cases can apply to your product.
7. Docparser
A cloud-based document processing and OCR software. Docparser can automate low-value tasks and workflows.
Pros:
- Easy to setup
- Can integrate with Zapier
Cons:
- Webhooks fail occasionally
- Requires training to pick up the parsing rules
- Not enough templates
- Zonal OCR approach – can’t handle unknown templates
- Slow to load pages
8. Adobe Acrobat DC
Acrobat DC provides a comprehensive PDF editor with an in-built OCR functionality.
Pros:
- Stability/compatibility.
- Ease of use
Cons:
- Expensive
- Not an exclusive OCR software
Why is Nanonets the most complete Logistics OCR software?
Nanonets OCR software is easy to use and set up. The intelligent automation platform can handle unstructured data and the AI can also handle any data constraints easily.
The benefits of using Nanonets OCR in logistics go just beyond better accuracy, experience, and scalability.
- Data capture and entry – Nanonets OCR can be used to accurately capture data from Purchase Orders, Freight Invoices, Shipping Labels, and Bills of Lading within seconds. The extracted data can directly be connected to any logistics management software, reducing the need for manual data entry and improving accuracy.
- Documentation and storing – Nanonets OCR can easily create digital and editable copies of all types of shipping documents. These documents can then be easily stored and retrieved whenever required.
- Quality control – Nanonets OCR can provide multiple approval steps before a document is ingested into the system or sent for approval. This helps in identifying errors early and reducing the resources and costs required for rework.
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- Source: https://nanonets.com/blog/best-logistics-ocr-software/