Cut data entry time from Transport Docs by 60% with Wenda's AI

May 16, 2023

16 May 2023

Cut data entry time from Transport Docs by 60% with Wenda's AI

Processing Transport Documents (TDs) is a crucial process for properly storing and entering data about goods in transit within a ERP system or Warehouse Management System (WMS).

However, the data entry activity can require a considerable amount of time and human resources. But what if it were possible to reduce the time required for DDT data entry by 60%? This is where Wenda's Artificial Intelligence (AI) comes in, an innovative solution that promises to transform this process.

Let's then explore the challenges inherent in manual processing of TDs and emphasize the importance of adopting automated solutions to improve the efficiency and accuracy of the process. We will discuss the limitations of the traditional data entry procedure and the need to implement new solutions that simplify and speed up TD processing.
We will then focus on Wenda's AI as an innovative solution to overcome the challenges of TD data entry.
In fact, the advanced features and functionality of Wenda's AI allow automating the process of capturing and entering data from TDs, and help significantly reduce the time required for data entry, freeing up human resources for more strategic and high value-added activities.
Finally, we present a concrete use case of Wenda's AI in the processing of Transport Documents: through a practical example, we will see the tangible benefits that companies can achieve by using this solution.

Among the results obtained by companies that have adopted Wenda's AI for the processing of TDs, we highlight the effectiveness of the solution in significantly reducing data entry time and improving the overall efficiency of the process.

Automated solutions for Transport Document processing

In the logistics and supply chain industry, the processing of Transport Documents (TDs) is a crucial step in ensuring the proper management of goods and workflows. However, the traditional data entry operation of the data contained in TDs can require a considerable commitment of time and resources, slowing down back office activities and limiting the overall productivity of the company.
But the advent of automated AI-based solutions offers new opportunities to speed up TD processing and simplify Transport document management. These solutions allow TDs to be processed quickly and efficiently by automatically storing relevant data and entering it directly into the ERP, Warehouse Management System (WMS) or Transport Management System (TMS).

Implementing such automated solutions can lead to significant benefits, including a dramatic reduction in the time required for TD data entry, up to 60% less: "The combination of significant labor cost savings, new job creation and increased productivity suggests a labor productivity boom like those that followed the emergence of earlier general-purpose technologies such as the electric motor and personal computer"1.
This allows companies to optimize resources, focusing on higher value-added activities and freeing staff from repetitive and boring tasks.


Transport documents, however, are just one of many forms of documents that can benefit from AI-based automated processing.
These solutions can handle a wide range of documents, including proofs of delivery, invoices, airway bills and many others, simplifying and speeding up the entire document workflow.
In short, document automation is a key step in the digital transformation of companies and their ability to remain competitive in the marketplace. The elimination of repetitive tasks and automated document management enable increased staff productivity and improved quality of work performed.
By integrating AI-based automated data entry tools, companies can reduce human error, increase operational efficiency and improve data accuracy. This translates into increased business agility, better inventory management and improved customer satisfaction.

Document automation is a key step in the digital transformation of companies and their ability to remain competitive in the marketplace.

It is therefore evident how using automated AI-based solutions for TD processing is an effective way to speed up the data entry process, process transport documents and reduce the time required for back office activities by 60%.
These solutions enable companies to streamline operations, improve overall productivity2 and provide more efficient and accurate service to their customers.

Let us now turn to Wenda's AI, and see how this solution is an ideal option for saving time and increasing productivity.

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Wenda's AI: a solution to save time and increase productivity

Wenda's AI is an innovative solution for optimizing Transport document management, saving companies time, reducing data entry errors and increasing overall back-office productivity.

The AI model developed by Wenda for transport document processing is based on computer vision, allowing it to automatically identify and extract data from the documents themselves. This approach makes it possible to recognize relevant information from both the header and the detail of the document, such as the date and time of transport, shipper's name, delivery address, weight of goods, and many other specific details. In addition, Wenda has developed specialized AI models for different markets, considering the differences in the data to be extracted for food, metal, or plastic products-for example, the weight of oranges is different from the diameter of steel, and in plastic products there are micron measurements.
Because of this specialization, Wenda is able to provide AI models suited to the specific needs of each industry.

The cutting-edge technology behind Wenda leverages Artificial Intelligence for document processing and management through an approach called Intelligent Document Processing (IDP). This technology can recognize and extract information from different types of documents, such as text, images, and tables, enabling them to be used in other business applications.

The benefits of Wenda's AI are many. First, it enables the reduction of data entry errors, ensuring the accuracy and integrity of data extracted from Transport documents. In addition, the adoption of Wenda leads to a 60% reduction in the time required for back-office data entry activities, freeing up human resources for more strategic tasks. Thanks to the 24/7 continuity of operations offered by Wenda's AI, carriers, 3PLs, and manufacturers can easily read and process transport documents provided by principals or check the correspondence between the delivered goods and the order, regardless of their time zone or that of the principal.

In summary, Wenda's AI is a state-of-the-art solution for automated processing of transport documents, enabling reduced data entry errors, improved operational efficiency, and significant productivity gains.
So let's go deeper and explore a real-world use case of Wenda AI Document Processing to concretely highlight how this solution has helped improve business operations and achieve significant results.

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Wenda AI document processing: a real-world use case

Wenda offers a comprehensive solution for automated processing of Transport documents through the use of its advanced Artificial Intelligence model.
This supply chain AI model is specifically designed to automatically read and understand data in Transport documents from both the header and the detail. The power of computer vision enables it to identify and extract essential information such as the date and time of Transport, shipper's name, delivery address, weight of goods, and many other relevant details.

In addition, as already anticipated, Wenda's AI is based on IDP technology, which enables it to recognize and extract information from different types of documents, such as text, images, and tables, making it available for use in other business applications such as ERP, WMS, or TMS.

The process of using Wenda's AI follows several steps.
Initially, transport documents are scanned into digital formats such as PDF, enabling secure storage and automated processing. Next, the specialized AI model best suited to the specific TD type and industry is selected to ensure accurate understanding of industry-specific terms.

In the optimization phase, digital documents are prepared for the AI model: this module ensures that the documents have a standard layout, improves the quality of scans, and makes the data ready for AI.
Once the documents are ready, the specialized AI model goes into action: it analyzes the transport documents and uses natural language processing and Machine Learning techniques to identify and extract relevant details such as addresses, product information, weights/sizes, and references/SKUs.
Thus, context awareness allows the most meaningful information to be extracted from the Transport document.

Then, in the post-processing and output structuring phase, the raw data extracted from Wenda AI Document Processing are organized and structured according to the client's specific needs. Additional validation or standardization is performed to ensure data quality. The resulting output is compatible with the company's internal systems, such as Warehouse Management System (WMS), Transport Management System (TMS), ERP, and others.
Finally, structured data from Transport documents are shared with business applications and integrated into supply chain processes, so IT systems can be directly updated, process automations enabled, and overall efficiency of operations improved.

The use of Wenda's AI Document Processing, via the TD data extractor, thus enables optimization of supply chain processes, reduction of data entry errors, and efficient management of Transport documents, thereby facilitating the flow of information and contributing to smoother and more productive operations.

In conclusion, Wenda's cloud platform offers a unique experience to supply chain and logistics professionals in many industries, and can bring several benefits:

  • +50% staff productivity: you can reduce time spent on repetitive tasks and documents, increasing employee productivity; 
  • -20% inventory costs: you can improve visibility and accuracy of data, to reduce direct and indirect inventory costs;
  • -30% operational costs: you can implement various automations, gaining extensive visibility useful for reducing operational costs and risks;
  • + Reputation: you can gain control of your operations, increasing customer satisfaction and enhancing your brand image.

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Automated processing of Transport Documents with Wenda's Artificial Intelligence is an innovative solution to reduce data entry time by 60% and improve overall process efficiency. With the ability to automatically recognize and extract data from TDs, Wenda's AI simplifies and accelerates the capture and entry of information into ERPs, WMSs, or TMSs.
This enables companies to optimize human resources, freeing them from repetitive tasks to focus on more strategic and higher value-added activities.
Wenda's AI offers numerous benefits, including a 60% reduction in the time required for data entry, increased data accuracy, decreased human error, and improved management of transport documents.
With its cutting-edge technology and specialization for different industries, Wenda is an ideal option for companies that want to optimize TD processing, improve operational efficiency, and offer more efficient and accurate service to their customers.

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1. See the report by Goldman Sachs, (J. Briggs, D. Kodnani), The Potentially Large Effects of Artificial Intelligence on Economic Growth, 2023

2. See the article by Datagraphic titled How Does Automation Help Boost Employee Productivity?

3. See the article by IBM titled What is computer vision?: “Computer vision is a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs — and take actions or make recommendations based on that information. If AI enables computers to think, computer vision enables them to see, observe and understand.”