Our AI solutions

We offer the full range of Intelligent Document Processing - bundled in various AI solutions: from separating, classifying and extracting your documents to content analysis.

Level 1

Document separation

Automatic separation of related processes into individual business documents. With document and page separation, individual documents are identified in multi-page documents. These can then be downloaded individually.

Classification

We use machine learning technologies to classify documents automatically. This determines what type of document it is. For example, it can be used to assign your incoming mail to specialist document types.

 

Data extraction

Easily turn your documents into structured data. We use image and text analysis techniques to identify and read data from your documents quickly and efficiently. You can then process this data further in your systems via JSON file.

Anonymization

Anonymization permanently removes personal data from documents in a way that cannot be reconstructed, in order to protect the privacy of the persons concerned and to ensure data protection.Using an algorithm pre-trainedby Buildsimple ,documents are stripped of personal and numerical references and the corresponding digits are replaced by random sequences of letters and numbers.

Strikethrough recognition

With this solution you can automatically search a large number of documents for handwritten deletions. As a result, you get a list of which pages contain deletions and which do not. In contract management, for example, this can reduce the effort required for manual viewing or even the risk of undetected manipulations.

Signature recognition

This solution makes it possible to quickly and automatically identify signatures on documents. By recognizing signatures, companies can, for example, speed up application processes, prevent fraud and forgery, and ensure the integrity of documents.

Sentiment analysis

With sentiment analysis, moods or emotions expressed in a document can be automatically detected and classified. This can be used to automatically identify a complaint in the insurance industry, for example. 

Content analysis

Document content analysis is a useful way to analyze and gain insights from large amounts of text data. For example, by analyzing customer experiences, you can identify patterns in your customers' needs and interests.

Context analysis

With the method of Natural Language Processing (NLP), texts in documents can be analyzed and interpreted. This allows the content of documents to be understood and placed in the appropriate context. 

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