Pre-Evaluation Extension

In this article, we explore the transformative power of the Pre-Evaluation Extension—an innovative solution developed by KAPTO that enhances the accuracy and uniformity of extracted data.

The Pre-Evaluation Process modifies the data to ensure it is corrected and presented uniformly. This data is returned to KAPTO as an additional correction, replacing the AI data.
 
The Pre-Evaluation Extension modifies data to ensure it is corrected and presented uniformly. The goal of the Pre-Evaluation Process is to improve the accuracy of the data by correcting any errors or inconsistencies that may exist in the original data.

When KAPTO extracts data from a document, it uses machine learning algorithms to recognise the structure and content of the data. However, there are often errors or inconsistencies in the original data, which can result in inaccurate results. For example, there may be misspelled words, incorrect formatting, inconsistent units of measurement, and highly errored images. These errors can significantly impact the accuracy of the extracted data, making it difficult to use for downstream processes.

To address these issues, the Pre-Evaluation Extension applies a series of data corrections to the extracted data. This process involves analysing the data to identify any errors or inconsistencies and correcting them to ensure that the data is uniform and accurate.

The Pre-Evaluation Process analyses the extracted data to identify inconsistencies or errors. Once identified, the Pre-Evaluation Extension applies a series of corrections to the data.

Another key feature of the Pre-Evaluation Extension is that it allows for human input to correct any errors or inconsistencies that may be missed. This is particularly important in cases where the data is highly complex or requires specialised knowledge to correct. By allowing human input, the Pre-Evaluation Extension ensures that the extracted data is accurate and reliable.

Once the Pre-Evaluation Process is complete, the corrected data is returned to KAPTO as an additional correction, replacing the AI data. By improving the accuracy and uniformity of the data, the Pre-Evaluation Extension enables more effective use of the data and reduces the risk of errors and inaccuracies.

By customising the Pre-Evaluation Extension to meet the specific needs of different industries and allowing for human input, KAPTO enables more effective use of the extracted data in downstream processes. The Pre-Evaluation Extension significantly reduces the risk of errors and inaccuracies, leading to better decision-making and improved business outcomes.

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