Product filters operate in the background on e-commerce sites to streamline the customer journey. These filters allow users to pick and sort the products they are searching for by using filter options, such as color, size, style, and pattern. This helps to save time and allows customers to control their buying experience.

Did you know that a similar experience can be achieved by applying data extraction tools to software applications?

Filter Useful Information Using Data Extraction Tools

Most applications today are equipped with the capability to ingest key content from documents, but a robust extraction tool goes beyond that – allowing applications to auto-capture content, compare confidence levels, and make informed decisions.

A data extraction tool effectively extracts and converts content into useful electronic information from large batches of structured and semi-structured documents. Furthermore, it leverages new-age technology to enhance accuracy by learning from previously processed documents and providing visual indications of data inaccuracies, allowing users to make corrections accordingly.

Digital Voting for the Most Accurate Data           

Using multiple extraction engines, a software can capture and process incoming documents, extract data with precision, and carry out digital voting, or comparison. This is based on the confidence levels of the extracted data processed in each engine and eventually the most accurate data is populated into the system.

The AI-based digital voting algorithm:

  • Determines the confidence levels of each character from different engines. These values are stored in a table
  • Compares the extracted results
  • Picks the data with the highest confidence level and populates into the system, highlighting the greatest confidence value obtained

This helps users to verify and identify unacceptable or statistically insignificant confidence fields.

Data Extraction in Invoice Processing

A robust invoice processing system allows organizations to streamline the inflow of invoices received from various sources, such as email, paper, and portal.

Here’s how data extraction helps in invoice management system:

  • Invoices can be captured from different channels and introduced into the workflow
  • Invoices are then processed through multiple extraction engines
  • The tool then compares the extracted data and executes automatic voting functions on the backend
  • The most accurate critical data is populated onto a rich user interface for viewing
  • Preconfigured validations make it easy for users to post an invoice in ERP

Implementing a voting concept, for invoice management, can empower business users to be more efficient, productive, and compliant with regulatory requirements.

In Conclusion

Leveraging the appropriate extraction tool, based on business needs, can help users to efficiently manage huge volumes of data and streamline content-based processes, thereby promoting the overall success of the organization.