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The new generation
of intelligent capture

Discover the intelligent generation 2.0 capture solution by Open Bee, which allows data extraction and automatic classification of documents

Today 3 million supplier invoices are currently managed by the Open Bee Capture solution within accounting and financial services. To enable its customers to boost their digital transformation through the automation of business processes, Open Bee now offers the second generation of this solution simplifying the recognition and automating the filing of all document types.

Recognize all document types

Beyond invoices, the solution automates data extraction and classification of all types of structured and semi-structured documents. Therefore, whatever the nature or complexity of your document, its recognition is automatically improved to optimize its processing.

Multiple use cases

Until now, the tool was specifically used to process supplier invoices, file purchase orders, or even deliveries…

From now on, all document formats are concerned, especially the processing of ID or other administrative documents. This technological advance involves many business activities such as:

Information capture becomes a breeze with all incoming documents. The solution is also integrated into the cloud, so you can use the tool even when working from home with Smart Capture Cloud.

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Technology for multi-document capture

Deep learning and semantic recognition are at the heart of the tool

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Open Bee Capture is equipped with a cutting-edge multi-document recognition engine that leverages the power of deep learning and semantic analysis. This integration means that the tool is not static; it possesses self-learning capabilities that enable it to self-correct and continuously refine its performance, especially when faced with documents that are challenging to interpret.

The traditional method of manually identifying each frame in a document can be time-consuming and prone to errors. However, Open Bee Intelligent Capture transcends this approach through the use of auto-supervised learning. This innovative method allows the model to autonomously identify and learn from data, significantly reducing the time required for data labeling.

A natural organization of documents around keywords

Based on the combination of keywords and their position, this new engine can detect and categorize incoming documents according to a specific type and index (metadata) to be searched.

Users are not left out of the loop. On the contrary, they are provided with comprehensive customization options. You can tailor the automated recognition process with preferred keywords, establish links between keywords, enforce strict adherence to specific keywords, and position keywords according to your organizational needs.

Make document management a breeze with Open Bee

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The power of semi-supervised learning algorithms

The incorporation of semi-supervised learning algorithms takes the capabilities of Open Bee Capture even further. These algorithms can label a large database with minimal input, learning from a small set of labeled data through auto-supervised learning steps. This feature is particularly beneficial in the field of Document Management System (DMS), where it can be instrumental in determining classes or categories for documents.

For instance, an electricity provider may send various documents to customers, and the AI within Open Bee Intelligent Capture can recognize and classify these documents as invoices, payslips, or other types. This classification not only streamlines the document management process but also provides quick access to structured and crucial information for department heads, whether they are in HR, finance, legal, or any other service.

As we embrace this new era, the door swings wide open to a future rich with possibilities in artificial intelligence for document processing. The continuous improvement in self-learning and semi-supervised algorithms promises to revolutionize how we handle and process vast amounts of data, leading to unprecedented efficiency and organization in the workplace.

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