Automated Data Extraction and Aggregation Engine

Automated Data Extraction and Aggregation Engine


Insurance has become an essential component of business and human existence which is a controlling force in ensuring the well-being of both people and companies. An advanced insurance industry is a blessing for a country’s economic development. It actively encourages the health and safety of the economy and company. As an innovative business, we know the pulse of the insurance industry and support insurance companies in technology. We have been assisting the industry in the previous few years by offering distinct alternatives to make their job simpler.

Focusing on the main challenges that the insurance industry is facing today, we found that, with the increasing rate of information these days, there are continuous data updates before any proclamation. Picking up the accurate content has been an onerous task for the data collectors. Here we propose a real-time assistant which can monitor massive amounts of data and extract high valued information out of it and our ‘Automated data extraction and aggregation engine’ does exactly the same.

Regardless of the type of industry, the platforms that work closely with public belongings need to gather some bulk information such as large numbers of invoices and associated records handled by industries such as insurance, shipping, e-commerce, etc. Entering all invoice information can be very laborious, time-consuming, and a flawless result can hardly be expected.

This engine is implemented with OCR (Optical Character Recognition) on structured forms for identifying data elements and it converts different types of your documents, such as scanned paper documents, PDF files or images captured by a digital camera into editable and searchable data. In short, the engine enables users to automatically monitor, extract and deliver valued information from diverse sources available.

Besides keeping their data accurate and up-to-date users are also benefited by eliminating manual errors and time consumed while bringing down the costs that are invested in monitoring large volumes of data and data extraction.


  • Improves data quality
  • Minimize human errors in data entry
  • Optimize operational cost

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