How much time is your business spending on manually entering data that is time-consuming and error-prone? Numerous firms are actually having trouble with this problem, as seen by the numbers.
According to 2021 data from the US Bureau of Labor Statistics
, US companies collectively
spend $5.3 billion annually
on wages for data-entry keyers. It’s an issue that not only drains resources but also leaves room for costly errors.
Thankfully, there is a transformative solution on the horizon:
Optical Character Recognition (OCR)
and Natural Language Processing (NLP). These groundbreaking technologies are ready to liberate your business from the limitations of manual data entry. OCR empowers you to effortlessly convert printed or handwritten text into machine-encoded data, while NLP enables computers to understand, interpret, and generate human-like text.
Together, they form an invaluable partnership that can revolutionize data processing, extraction, and
document verification
tasks, leading to improved efficiency, cost reduction, and more informed decision-making.
Join us as we explore and discover the outstanding benefits and exciting use cases of OCR and NLP solutions in this blog. Your business’s future is brighter than ever, and we’re here to help you unlock its full potential!
At its core, Natural Language Processing (NLP) is a field of AI and machine learning that focuses on the interaction between humans and computers using natural language. Its primary goal is to enable computers to understand, interpret, and produce human language in a way that is both meaningful and useful.
The technology behind NLP is a fascinating blend of linguistics, computer science, and machine learning. These techniques are the building blocks that enable NLP to decode and understand human language, making it a powerful tool in the realm of data and communication. Below, you can find some of the techniques that power NLP:
Optical Character Recognition (OCR)
is the technology used to convert printed or handwritten text from scanned documents and images into machine-readable text. OCR’s primary purpose is to recognize and convert visual representations of text into a format that can be processed by computers.
But here’s where the magic truly happens: OCR and NLP often work as a formidable team that creates a seamless document processing workflow. With OCR bringing the text into a digital format and NLP adding layers of understanding and intelligence. This dynamic duo transforms dusty archives into valuable, business-ready information.
If you still wonder how NLP is used and what its practical applications are, you’re in the right place. Below, we’ve compiled a list of the most common and impactful business use cases of NLP-powered OCR solutions. Keep in mind that this is our selection of the list that we think can be helpful for your business (of course, there are many more use cases):
