The definition of data extraction is “the task of automatically extracting data from unstructured or semi-structured documents”. With the advancements in technology, this task gets more important with each passing day. But, if the data is unstructured, how can it be processed automatically?
Document processing: enormous amounts of information and data!
Nowadays, we need to process enormous amounts of information and data. The first step is obviously to have an effective data management strategy, optimized for your company needs.
To keep up with the daily growth of information, AI and machine Learning are two important solutions to consider. They will provide you with increased efficiency, speed and reduce the human error.
Depending on the type of document, data fields such as “name, address, etc..” are placed in distinct parts of document. So, what to do when that information needs to be digitized and processed? That’s where AI and Machine Learning come in.
Using AI & Machine Learning for automated data extraction
Algorithms scan through the information using OCR (Optical character recognition), and label everything according to pre-defined labels (name, address, etc.). This way, hundreds, if not thousands of documents can be processed, organized, and optimized, with little to no human error and speeds that wouldn’t be possible by humans.
With machine learning, the human input can be minimized or even eliminated, since the AI is also in charge of verifying all the data extracted and stored.
By using these tools, your business will experience an increase in productivity, which in turn will give you an advantage over the competition.
TML: Texter Machine Learning – AI is essential to remain relevant!
The adoption of AI in modern organisations is essential to remain relevant and competitive, optimising efficiency, empowering new business opportunities and freeing critical human resources to specific value-added tasks.
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