Bestellungen automatisieren mit KI


By using Natural Language Processing (NLP), the processing of incoming orders can be automated and significantly accelerated - thus enormously increasing both productivity and customer satisfaction.

In many companies, processing incoming orders is still a time-consuming and manual process. Employees have to transfer data from e-mails and sometimes even from incoming faxes and letters into ordering systems. This is not only inefficient, it also often leads to errors in processing and thus to delays for the customer.

Automation of incoming orders and AI technology

Using AI technology at the order entry point, processing can be largely automated.

The AI is able to read and understand emails or other text documents and extract the relevant information. By using Natural Language Processing (NLP) with Deep Learning methods, data can be read in a structured manner even from complex, long or differently structured documents such as extensive service specifications and transferred to the ordering system, for example.

From the type of goods to the quantity of goods to the customer’s data - the important information is available automatically and quickly (almost immediately), regardless of the form of the orders, and the orders can be processed without delay. At the same time, the error rate is very low. Matching with existing data from leading systems is also possible - which speeds up processing even further.

Data extraction systems already in use are often based “only” on optical character recognition (OCR) technology. These can be used to extract rule-based data from predefined layouts. However, especially in the case of purchase orders, the formats are rarely uniform and there are many possible variants. This usually means a lot of manual rework or high effort in defining templates for a wide variety of layouts. Reading data from continuous text or handwritten text is usually not possible at all.

AI-based systems, on the other hand, read like a human (only faster) and work very precisely regardless of the format and structure of the documents.

Automating orders with AI in practical use

Using an AI system to automate order entry can be particularly useful when orders are in different forms - i.e., different document types, formats, or even languages.

For example, the AI model used in the AI system can be trained to recognize certain keywords or phrases in an email order and output the corresponding information such as customer name, item number and quantity as data.

Both incoming orders and change requests for existing orders can be processed. The latter, in particular, is often time-critical and the fast processing of the data enables a quick response.

The extracted data can be directly matched with information in leading systems - such as SAP. Using AI, for example, the correct project number can be assigned directly - even if the order only contains the product name. The AI recognizes which data belong together. This additionally saves a lot of time.

In addition, an AI system can even make predictions. For example, the system recognizes frequently asked questions or inquiries from customers and initiates the next process step (workflows). Through the structured analysis of human communication in text form, the processes involved in processing orders can thus be optimized even further.

Advantages of using AI to automate orders

1. Automation & Productivity Increase

AI systems for automating order entry are able to automatically read emails and other text documents and extract the relevant information. This allows the order entry process to be automated - employees need to do less manual diligence.

2. Accuracy & Reduced Error Rate

AI systems for automating order entry can work more error-free. Their use therefore significantly reduces the error rate in the entire order processing.

3. Time Saving & Faster Processing

AI systems for automating order entry are able to automatically read emails and other text documents and extract the relevant information. This allows the order entry process to be automated - employees need to do less manual diligence.

4. Shorter lead times & higher customer satisfaction

Faster data availability also means faster responses to customer inquiries, faster processing of orders and is thus a decisive factor for customer satisfaction. Reducing the error rate also ensures higher quality.

5. Predictions & Pattern Recognition

AI-based systems can analyze human communication and make appropriate predictions, e.g., recognize frequently asked questions or requests from customers and suggest appropriate response templates or workflows.

6. Security & Transparency

By automating data capture alone, companies gain more security, because the information is consistently evaluated with the same speed and precision. The current status of incoming orders is transparent at all times - almost in real time and independent of the current order volume.

Automate orders with the AI system kinisto

With kinisto, information from orders can be converted into structured data and quickly processed further - regardless of the input channel, the formats or the structure of documents. kinisto goes a big step further than conventional systems for classification and data extraction. Based on Natural Language Processing (NLP) with Deep Learning methods, kinisto recognizes information in context and makes it usable.

As a specialist for AI technology in practical use, tetrel will be happy to advise you on the topic and your specific case!

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