OCR technology can read text for us and convert the information into useful data. Whether built into your favorite application for viewing and managing PDFs — combined with translation software, or built into a process management platform, OCR has many uses.
What is OCR?
In short, OCR (optical character recognition) reads the text within documents the same way humans do. However, unlike humans, OCR can recognize characters, numbers, letters, and words — in any font or language.
In the early 1980s, OCR was one of the first forms of artificial intelligence (AI) and has since evolved to become the first step of digital transformation. Today, OCR is the technology behind some of the most potent and widespread software tools.
Why you need OCR
Nearly all transactions and customer interactions take place on a digital platform. To truly digitally transform, businesses need OCR to evolve with the growing demands of customers and the rapid growth of unstructured data.
As a legacy technology, OCR can recognize virtually any type of character, letter, and number, regardless of font or language — eliminating the most time-consuming and painstaking aspects of data entry. It can even recognize the differences between typed and handwritten text — cursive and block letter.
The limits of legacy OCR?
Most new data enterprises collect and produce is "unstructured" — an area OCR struggles with the most.
It requires high-quality scanners.
OCR best suits high-quality scanned images with higher contrasts between texts and backgrounds. But what if the text is splotchy or the scan is low-quality? OCR's accuracy drops dramatically. Even with the best scanners & document quality, legacy OCR still reaches its limit at 60% accuracy.
It struggles with handwriting
When recognizing handwriting — OCR doesn't cut it as a standalone technology. Handwriting is messy and it’s often too illegible for experts to read faultlessly. Even after decades of research, most off-the-shelf OCRs still cannot accurately recognize styles of handwriting and signatures. Can't we do better?
How Automation Hero can help you with OCR
Standalone OCR can't recognize low-quality scans or handwriting any better than humans — but what if all the benefits of OCR could integrate with next-level AI technology to make OCR “intelligent?” That would be a giant leap forward for handwriting.
Enter Context-aware OCR. Automation Hero's custom patent-pending Context-aware OCR reads documents — especially handwriting — the same way as human experts. It allows any subject matter expert to dynamically bring their expectations about documents into each processing task — making the AI an expert at that document too. Now, medical practitioners, legal professionals, and business leaders can provide their expertise about documents to capture the holistic business context.
Context-aware OCR is 281% more accurate at handwriting recognition than the leading competitor's OCR — plus, our proprietary Context-aware OCR is more than 90% accurate at cursive recognition.
And, of course, when you focus on improving handwriting recognition as we do, performance and accuracy go up across the board for all machine-typed documents too.
In the table, Competitor 1 converted the handwriting into gibberish — while Competitor 2 didn't perform much better. On the other hand, Automation Hero's Context-aware OCR recognized and converted scribble with 100% accuracy, even with cursive scrawl and poor scan quality.
Powered by industry-leading AI, our all-in-one Hero Platform_ comes equipped with our Context-aware OCR. Our platform is built to handle your documents and unstructured data at scale.
Where Context-aware OCR wins
Context-aware OCR captures all essential information from invoices, purchase orders, tax forms, legal contracts, insurance claims, bills, and images containing handwritten text with greater accuracy and speed than base-line OCR can offer. Even if document scans are blurry or low resolution, our custom Context-aware OCR understands context. Here are a few use cases of what Context-aware OCR can do.
Handwriting recognition
Handwriting is incredibly tricky. But our OCR is different. We custom-built our OCR with an AI model that is "Context-aware". It uses context to read any document the same way as human subject matter experts. As a result, automation Hero is 281% more accurate at handwriting recognition than the market leader.
Bad or low-quality documents
Low-quality documents are more common as people use smartphone cameras instead of scanners to digitize paper. Humans use context clues to read and understand muddy text, but generic OCR tools don't have this reasoning capability. If a letter or word is too blurry for the software to recognize, it will skip over it without realizing it missed anything. Not Context-aware OCR.
Context-aware OCR reads any document
Designed by data experts who understand the fast-paced growth of unstructured data and the challenges businesses face to keep up with it, Automation Hero combines industry-leading AI with the most accurate optical character recognition (OCR) technology on the market.
Captures forms accurately
Base-line OCR scans each form and converts it into editable text — but if a character, letter, or handwritten word is too blurry, it skips over critical values, amounts, and due dates, without realizing it missed anything. Context-aware OCR captures the whole information picture about your form at the moment of automation to streamline the process accurately and efficiently.
Streamlines data intake
Typing hard-to-read handwriting into computers is one of the most time-consuming tasks for any front office or reception area. Context-aware OCR reads & converts handwriting in patient forms with the same expertise as medical staff for incredibly easy recordkeeping. It also digitizes patient history, diagnoses, test results, and other medical records with above-human accuracy. Beyond healthcare, Context-aware OCR streamlines form intake in every kind of office that uses paper.
Dynamic document management
Context-aware OCR provides a dynamic user experience for "on-the-fly" document management. Users can quickly give context inside the interface using a no/low code environment. At the moment of automation, it applies your context and improves results dynamically — making it easy to build up a context for any document and adjust it as you go. Tell Hero Platform_ what your automation is about, and it will maintain this contextual information for each new document.
FAQ about OCR
What does OCR mean?
OCR stands for “Optical Character Recognition.” OCR is the technology that can look at images of text and recognize patterns in arrangements of pixels as either letters or words.
What OCR is used for?
OCR technology eliminates the most time-consuming and painstaking aspects of data entry. However, generic OCR recognizes machine-printed characters far better than handwriting. As a standalone technology, OCR offers efficiency gains in nearly every industry for virtually every type of business process — particularly those with fixed-form structured data and machine-printed text.
Where is OCR most used?
As you might expect, the most significant impact of OCR is manual data entry tasks. OCR speeds up this essential business process and makes it convenient to turn words from scanned PDFs or images into text that can be edited or copied without manual retyping. Even with the limits of legacy OCR technology, it can help organizations streamline the digitalization of structured documents.
How does the OCR process work?
OCR's pattern recognition techniques work similarly to how people read. Eyes register text by observing the patterns of dark and light that combine to create characters. Then the brain analyzes the information to decipher words and find meaning — all in a fraction of a second. While scanning documents, OCR compares dark and light patterns to the characters in its database. Whenever patterns documents match with data in its knowledge graph, OCR converts them into machine-readable and editable text.
What are the advantages of OCR?
OCR has many advantages. OCR combines with other technologies such as AI, Robotic Process Automation (RPA) and is one of the architectural components in intelligent document processing (IDP). In addition, since OCR specializes in recognizing handwriting and machine-printed texts, OCR is traditionally one of the first steps to digital transformation.
How does OCR software increase revenue?
OCR doesn't just save time — it saves money. A study conducted by GreenBook found that typing is only 96% accurate for single-keyed data. The GreenBook study highlights the scale of errors possible with manual data entry. If a large-scale company processing 200 forms requires 10,000 keystrokes, a 96% accuracy rate translates to at least 400 mistakes. Workers manually reviewing errors resulting from OCR are significantly reduced compared to manual data entry. Every labor hour eliminated from data entry helps OCR pay for itself — translating into increased profits.
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