Technical FAQs
Seventy-six percent of companies surveyed plan to prioritize machine learning (ML) and artificial intelligence (AI) deployments in 2021. Despite increased uptake, however, there is still a great deal of confusion surrounding these advanced concepts. In order to understand how organizations hope to leverage ML and AI in their technology initiatives, it’s helpful to take a step back and examine how they work and how they differ from each other.
What Is Machine Learning?
Machine learning uses statistics-driven algorithms to find patterns in massive amounts of data. These algorithms are designed to improve over time as they process more data to enable more accurate outputs. Machine learning is widely used to produce predictive recommendations — companies such as Google, Netflix, and Facebook collect data about user behaviors and feed it into machine learning algorithms which then produce targeted search results, movie recommendations, or advertisements.
The key to machine learning success is data. The more data available to ML algorithms — and the higher-quality this data — the better they’ll be able to identify patterns in current datasets and apply them to new data sources.
Most machine learning methodologies fall under one of two broad categories:
- Supervised Learning: Developers classify and label data to guide the algorithm’s inputs and outputs to ensure specific patterns are recognized. This method is time and resource intensive because it requires data scientists to capture, control, and curate data sources.
- Unsupervised Learning: This approach provides ML algorithms with unlabeled and unclassified data and allows them to identify patterns based on unique data characteristics. Developers don’t interfere with the learning and pattern recognition process, instead evaluating the outputs for accuracy and modifying code as needed.
Why Does Machine Learning Matter?
Machine learning helps organizations leverage the massive amounts of data they’ve accumulated. This information is drawn from a variety of sources, including disparate forms and documents, data produced through customer transactions and service calls, and the ongoing operational data produced by staff as they interact with IT resources.
Thanks to both the rapid uptake of cloud computing and availability of large-scale data collection and analysis tools, these data volumes are increasing exponentially. As a result, aggregate assessment is now critical — companies need a way to rapidly and reliably derive patterns from available data, and apply these patterns to predictive action.
This is the evolving role of machine learning. By creating, testing, and deploying ML algorithms capable of rapid pattern analysis and application it’s possible for companies to benefit from this continual data influx rather than being constrained by the bounds of traditional data evaluation. To facilitate this process, many next-generation software tools and services are either equipped with built-in ML frameworks or are capable of interfacing with them.
Key Machine Learning Applications
The applications of machine learning are vast, but they tend to produce the best results when paired with existing processes that supplement human efforts or automate low-value, but labor-intensive, functions in the workplace. In effect, it has the potential to do almost anything a human mind can do, given enough time.
Improved Data Capture
Capturing data from internal documents and customer-submitted forms can be cumbersome and time-consuming. It can also lead to wasted time and effort if data is incorrectly entered, duplicated, or accidentally deleted. By pairing machine learning tools with forms processing solutions like Accusoft’s FormSuite for Structured Forms, developers can build applications that identify, collect, and capture key data more efficiently and accurately. For example, a robot process automation (RPA) bot can be set up to receive extracted form data from FormSuite and then populate that information into the appropriate fields within an application. This not only accelerates forms processing workflows, but also greatly reduces the risk of data entry error. Properly implemented, automated data capture can act as a springboard for improved data insight and decision-making thanks to improved accuracy and consistency.
Streamlined Content Creation
By combining machine learning algorithms and data sources with document editing tools, it’s possible to streamline key processes such as the creation of complex, compliance-bound content. One in-practice example is the use of Accusoft’s PrizmDoc Editor within the LegalSifter contract review and creation platform. By pairing its AI technology with PrizmDoc Editor’s document assembly capabilities, LegalSifter was able to quickly locate repetitive clauses and suggest replacements to create an automated contract creation experience for end users.
What Is AI, and How Does It Relate to Machine Learning?
The terms artificial intelligence and machine learning are closely related and often used interchangeably, but they’re not identical.
Artificial intelligence refers to technologies that are capable of performing tasks like photo recognition or data pattern analysis with similar (or better) outcomes than human beings. Machine learning refers to the creation, testing, and refinement of the algorithms needed to support AI tools. In many ways, then, ML functions as a distinct process that helps make AI possible.
As noted by Toward Data Science, it often helps to think of AI, machine learning, and deep learning like a set of concentric rings. The smallest, inner ring is deep learning, which helps inform the middle ring of machine learning by providing layered neural network structures that improve the process of pattern recognition. The final, outside ring is AI, which depends on both deep and machine learning to deliver real-world results.
Artificial intelligence tools can be broken down into two basic types:
- Generalized AI: These tools are capable of solving problems bounded by a clear set of rules. Using the ML algorithms that underpin the larger AI structure, general AI applications can act on stimuli — such as a security alert from an IT network — and respond appropriately by creating and logging reports or looping in human agents.
- Narrow AI: These solutions are designed to solve specific, small-scale tasks. Building on the security example from above, a narrow AI application might see tools responding to specific threat events such as DDoS or ransomware attacks by deploying targeted, defensive responses that close active sessions, capture attack data, and prevent future connections from the same IP address.
In practice, narrow AI tools can outperform their human counterparts in completing specific tasks, but are unable to translate this expertise into applicable action at scale. General tools come closer to mimicking human intelligence but are still a long way from replicating the depth and breadth of human thinking.
Limitations of AI
Much has been made about the potential of AI technologies to take the place of human staff, leading to a generalized sense of worry about the future of these tools at scale. Recent research, however, found that substantial confusion remains around not only the deployment of AI but the definition itself. In fact, one study found that 40 percent of AI startups in Europe were not actually using AI. In some cases, increasing market interest in AI tools encouraged the use of this term to help startups capture attention, in much the same way that rapid cloud adoption spurred the creation of a host of “cloud” companies that offered nothing of the sort.
Uncertainty around AI itself, however, also plays a role in this disconnect. Given the massive potential of AI to help companies solve both specific and generalized problems, the term can be applied in almost any context and made to fit almost any description.
Unlocking the Future
After spending many years confined to research projects and future-focused technology articles, both machine learning and artificial intelligence are making their way into the applications and software companies are deploying every day. As developers look ahead to building the next generation of technology solutions, they must not only think about how they can better leverage ML and AI principles, but also how to implement features that take advantage of them.
Accusoft’s collection of versatile SDK and API integrations deliver powerful viewing and image processing capabilities that help applications streamline workflows and enhance productivity. To learn more about how Accusoft can help you enhance the workflow in your machine learning or artificial intelligence projects, contact us today.
The insurance market is booming. As noted by research firm Deloitte, the property and casualty (P&C) sector saw a massive income uptick in 2018 and steady growth last year that’s predicted to carry forward through 2020. To help manage the influx of new clients and handle more claims, many firms are spending on insurance technology (insurtech) — digital services and solutions that make it possible to reduce error rates and enhance operational efficiency. InsurTech SDKs are important components of this transformation.
Both in-house insurtech solutions and third-party platforms often excel in specific areas but come up short in others, putting insurance firms at risk of writing off potential gains. While solution switching and ground-floor rebuilds offer one route to success, there’s another option that’s more custom to your business needs: software development kits (SDKs). Here’s a look at three top SDKs that offer customized functionality potential.
FormSuite for Structured Forms: Solving for Data Capture
Time is money. The faster insurance companies accurately complete and file documents, the greater their revenue potential. And as noted by KPMG, the need for speed is more pressing than ever. Many insurance sectors have seen substantial increases in both claims and new applications as the COVID-19 crisis evolves.
As a result, accurate and agile forms processing is critical to keep up with demand. If current insurance software can’t quickly capture forms data, recognize standard form fields, and let users easily create standard form libraries, policy processing falls behind.
FormSuite for Structured Forms makes it easy for developers to build in form identification and data capture that includes comprehensive form field detection with OCR, ICR, and OMR functionality and the ability to automatically identify scanned forms and match them to existing templates.
ImageGear for .NET and C/C++: Simplifying Conversion
Conversion is critical for insurance firms. Depending on the type and complexity of insurance claims, companies are often dealing with everything from Word documents for initial client assessments and .GIF or .JPG images of existing damage to contractor-specific PDFs or spreadsheets that detail necessary materials, time, and labor costs. The result? A mash-up of multiple file types that forces adjusters to spend valuable time searching for specific data instead of helping clients get their claims process up and running. This makes it difficult to recognize value from emerging digital initiatives.
Accusoft’s ImageGear for .NET and ImageGear for C/C++ empower developers to integrate enterprise-class file viewing, annotation, conversion, and image processing functions into existing applications, allowing staff to both quickly collaborate on key tasks and find essential data across a single, easy-to-search document.
ImageGear: Streamlining PDF Capabilities
While insurance technology offers substantive opportunities for end-users to capture, convert, and retain data, this technology can also come with the challenge of increased complexity. According to recent research from PWC, for example, firms looking to capitalize on insurtech potential must be prepared to rapidly develop new product offerings and embrace the expectations.
As a result, companies need applications that streamline current functions and allow them to focus on creating cutting-edge solutions. For example, PDF is a file format that is still used by enterprises worldwide to maintain document format consistency and maximize security. When it comes to converting multiple files into a PDF, software can be expensive and introduce data security issues.
This can all be solved with an SDK like ImageGear, which makes it possible to integrate the total PDF package into any document management application, both reducing overall complexity and freeing up time for staff to work on new insurance initiatives.
Insurtech forms the framework of functional futures in policy applications, claims processing, and compliance reporting, but existing software systems may not provide the complete capability set companies need to make the most of digital deployments. These top SDKs offer insurance IT teams the ability to integrate key services, improve speed, and boost security at scale. Learn more about Accusoft’s SDKs at www.accusoft.com/products.
TAMPA, Fla. – Accusoft, the leader in document and imaging solutions for developers, is proud to announce its beta release testing program, which provides participants with real-time access to its latest product developments.
Customer input is a key factor in Accusoft’s mission to build better software integrations that deliver functionality like OCR, image cleanup, forms processing, file manipulation, and viewing solutions. Thanks to the new beta program, participants will get early access to brand new products and have the opportunity to provide feedback on the latest features for existing products. Developers can also customize what types of betas they would like to opt into so they can focus on products most relevant to their business.
“Our previous betas for PrizmDoc Editor and PrizmDoc Cells were extremely beneficial for everyone involved, “ says Mark Hansen, Product Manager. “Our team received rapid feedback that helped make our products better, while participants had the opportunity to shape those products to meet their specific requirements.”
By signing up for the beta program now, you can participate in the active beta for PrizmDoc Forms integration, which will allow you to repurpose (or use) your PDF forms to easily create, customize, and deploy as web forms anywhere. You’ll also be the first to know about new product offerings and have the ability to opt into beta releases for Accusoft’s existing products, such as ImageGear, FormSuite for Structured Forms, and PrizmDoc Suite.
To learn more about Accusoft’s exciting new beta program, please visit our website at https://www.accusoft.com/company/customers/beta-release-program.
About Accusoft:
Founded in 1991, Accusoft is a software development company specializing in content processing, conversion, and automation solutions. From out-of-the-box and configurable applications to APIs built for developers, Accusoft software enables users to solve their most complex workflow challenges and gain insights from content in any format, on any device. Backed by 40 patents, the company’s flagship products, including OnTask, PrizmDoc™ Viewer, and ImageGear, are designed to improve productivity, provide actionable data, and deliver results that matter. The Accusoft team is dedicated to continuous innovation through customer-centric product development, new version release, and a passion for understanding industry trends that drive consumer demand. Visit us at www.accusoft.com.
On July 12, 2022, Accusoft announced the latest update to PrizmDoc, its industry-leading document processing integration. The PrizmDoc 13.21 update improves existing features and adds key functionality related to format support, redaction capabilities, content conversion, and more, allowing developers to offer enhanced functionality within their applications.
One of the main improvements in this release is to PrizmDoc’s Content Conversion Service (CCS). PrizmDoc now provides the ability to convert PDF documents to MS Word (DOCX) documents, making shared collaboration easier than ever before.
Other features and updates in this release include:
- High-Efficiency Image File Format (HEIF, HEIC) support for viewing, redaction, and conversion to JPG/JPEG, PDF, PNG, SVG and TIFF.
- PrizmDoc Viewer Markup Burner API now provides the ability to burn in redaction reason text for transparent (draft mode) redactions and provides the ability to remove PDF AcroForm fields.
- Improved performance of the PAS GET MarkupLayers API when using AWS S3 storage, which significantly reduces network traffic between PAS and S3.
PrizmDoc provides customizable document processing to help developers deliver in-browser document creation, editing, and collaboration functionality, to enhance their software applications.
For more information about PrizmDoc or to download a free trial, please visit our website.
About Accusoft:
Founded in 1991, Accusoft is a software development company specializing in document processing, conversion, and automation solutions. From out-of-the-box and configurable applications to APIs built for developers, Accusoft software enables users to solve their most complex workflow challenges and gain insights from content in any format, on any device. Backed by 40 patents, the company’s flagship products, including OnTask, PrizmDoc™ Viewer, and ImageGear, are designed to improve productivity, provide actionable data, and deliver results that matter. The Accusoft team is dedicated to continuous innovation through customer-centric product development, new version release, and a passion for understanding industry trends that drive consumer demand. Visit us at www.accusoft.com.
Forms have long been used to provide organizations with important information about their customers. For a financial services or insurance company, that information might be used to determine eligibility for a loan or set a policy rate. Legal teams and healthcare providers, on the other hand, often use them to quickly gather information that could be relevant to a client’s case or a patient’s care. By building form workflow automation into their applications, developers can provide these organizations with the tools they need to improve efficiency and provide better service to their customers.
A Better Way to Capture Data with Form Workflow Automation
At its core, a forms workflow is designed to capture data from completed forms and route that information to the appropriate destination. That end point will vary based on the application. In some cases it could be used to autopopulate database entries. Other systems may feed it into machine learning algorithms to identify trends or provide predictive insights. Before any of that can happen, however, automated workflows with forms recognition capabilities need to be in place to identify various form types and extract information from them using various forms of optical recognition.
The primary benefits of workflow automation are speed and accuracy. By building a forms workflow within their applications, developers can help their customers process submitted forms much more efficiently than they could by hand. Even if manual data entry wasn’t so prone to human error, it would still be a waste of valuable resources to have skilled employees performing such a repetitive, routine task. Automating this sort of work is often the first step in maximizing performance in other areas of an organization because it frees up resources that can be directed toward higher-value tasks.
Say Goodbye To Paper (Mostly)
Organizations have talked about going “paperless” for decades, but they frequently find it much more difficult to do so in practice. That’s largely because physical forms continue to be used across many industries. Converting these paper forms into digital format as quickly as possible is critically important. Without some way of incorporating them into an automated workflow, inefficiencies and manual errors will continue to creep back into business processes.
A forms workflow needs to be able to handle scanned forms images in addition to purely digital documents. Robust forms identification tools are essential for this process because they have the ability to match any submitted form to a library of predefined templates. Without identification capabilities, applications would need to be given specific information about every form. At best, submitted forms would need to be manually presorted before they could be scanned and uploaded for processing rather than being converted into digital format all at once and identified automatically.
Recognition and Extraction
Once forms are scanned, uploaded, and identified into an application, the data capture process can begin. While digital forms can easily send information contained in fields to the proper destination, a scanned form is just a static document image. Even if the form was filled out digitally and never existed as a paper document, the fields may not be responsive or the entire form may be nothing more than a flattened PDF image. In these cases, the only way to reliably capture data is to implement some type of optical recognition.
Optical Character Recognition
For machine printed text, forms workflows can deploy Optical Character Recognition (OCR) to identify and extract information from an identified form. High-quality OCR engines can read multiple languages, allowing them to capture data from almost any source and send it to the next phase of an automated workflow. When extracting text, OCR tools can be set to carry out full-page extraction, which pulls text from the entire form, or zonal extraction, which focuses the data capture effort on a smaller, predetermined area. The latter approach is much more common with forms processing because it allows the application to set parameters on each zone to enhance performance. If the OCR engine is instructed to look for only numbers in one field and specific regular expressions in another, it will be able to identify and extract text faster and more accurately.
Intelligent Character Recognition
Of course, many physical forms submitted for processing will not be filled out with standardized digital fonts, but rather by hand using a pen or pencil. For these handwritten forms, Intelligent Character Recognition (ICR) will need to be deployed to read and extract field contents. Although identifying handwritten text is a much more challenging undertaking, the combination of a powerful ICR engine and good form design can greatly improve accuracy and processing times to keep information moving through automated workflows.
Optical Mark Recognition
Forms frequently use checkboxes or fillable bubbles to indicate important information. When scanned images are run through a forms workflow for processing, applications need to be able to quickly identify the presence of a mark and apply the conditional information associated with it. Today’s forms workflow tools utilize Optical Mark Recognition (OMR) to detect the presence or absence of marks automatically. They can also check the entire form to determine what information might be missing, such as essential fields or signatures.
Unlock Your Form Workflow Automation Potential with the FormSuite Collection
Building an automated workflow for forms processing requires a variety of software tools and specialized imaging expertise. It’s a challenging task that becomes even more difficult when developers are facing tight deadlines for other application features. With the right forms workflow SDKs, software teams can rapidly integrate the features needed to identify a variety of forms and capture vital data using full-page or zonal text recognition.
Accusoft’s Forms Collection bundles our powerful forms toolkits into a single, easily deployed package. Whether you’re using FormFix to identify and align forms, cleaning up scanned images for better recognition results with ScanFix Xpress, or deploying fast, accurate OCR and ICR with SmartZone, FormSuite provides all the SDK resources your team needs to unlock your application’s workflow automation potential. Learn more about what’s included with the FormSuite Collection by downloading our detailed fact sheet.
Today’s organizations gather information from a variety of sources. Structured forms remain one of the most popular tools for collecting and processing data, and anyone who has filled out such a form recently has likely encountered the familiar bubbles or squares used to indicate some form of information. Whether these marks are used to identify marital status, health conditions, education level, or some other parameter, optical mark recognition plays an important role in streamlining forms processing and data capture.
What is Optical Mark Recognition?
Optical mark recognition (OMR) reads and captures data marked on a special type of document form. In most instances, this form consists of a bubble or a square that is filled in as part of a test or survey. After the form is marked, it can either be read by dedicated OMR software or fed into a physical scanner device that shines a beam of light onto the paper and then detects answers based on how much light is reflected back to an optical sensor. Older OMR scanners detected answers by measuring how much light passed through the paper itself using phototubes on the other side. Since the phototubes were very sensitive, #2 pencils often had to be used when filling out forms to ensure an accurate reading.
Today’s OMR scanners are much more accurate and versatile, capable of reading marks regardless of how they’re filled out (although they struggle if the mark is made with the same color as the printed form). More importantly, OMR software has made it possible to capture data from OMR forms without the need for any special equipment. This is especially helpful for processing forms information that exists in digital format, such as PDF files or JPEG images.
The History of Optical Mark Recognition
One of the oldest versions of forms processing technology, OMR dates back to the use of punch cards, which were first developed in the late 1800s for use with crude “tabulating” machines. The cards typically provided simple “yes/no” information based on whether or not a hole was punched out. When fed through the tabulating machine, a hole would be registered and counted. This same basic principle would allow more complex machines to perform basic arithmetic in the early 1900s before serving as the foundation for early computer programming by mid-century. Entire computer programs were stored on stacks of punch cards, which would remain in use until well into the 1970s when more powerful machines made them obsolete.
Although OMR operates on the same principle as a punch card, it instead uses scanning technology to detect the presence of a mark made by a pencil or a pen. This form of identification was first popularized by IBM’s electrographic “mark sense” technology in the 1930s and 1940s. The concept itself was first developed by a schoolteacher named Reynold Johnson, who wanted to streamline test grading. He designed a machine that could read pencil marks on a special test paper and then tabulate the marks to generate a final score. After joining IBM in 1934, Johnson spearheaded the development of the Type 805 Test Scoring Machine, which debuted in 1938 and revolutionized test scoring in the education sector. In production until 1963, the 805 could score 800 sheets per hour when run by an experienced operator.
The 805 registered marks by using metal brushes to sense the electrical conductivity of graphite from the pencil lead. While effective, it had limitations in terms of reading speed and flexibility. When Everett Franklin Lindquist, best known as the creator of the ACT, needed a machine that could keep up with Iowa’s widespread adoption of standardized testing in the 1950s, he developed the first true optical mark reader. Patented in 1962, Lindquist’s machine detected marks by measuring how much light passed through a scoring sheet and was capable of scoring 4,000 tests per hour.
Throughout the 1960s, OMR scanning technology continued to improve and spread to a variety of industries looking for ways to rapidly process data. In education, however, the OMR market would soon be dominated by the Scantron Corporation, which was founded in 1972 to market smaller, less expensive scanners to K-12 schools and universities. After placing the scanners in educational institutions, Scantron then sold large quantities of proprietary test sheets that could be used for a variety of testing purposes. Scantron was so successful that their distinctive green and white sheets have become synonymous with OMR scanning for generations of US college students.
The next major innovation in OMR technology arrived in the early 1990s with dedicated OMR software that could replicate the drop-out capabilities of commercial scanners. Part of the reason why scanners used proprietary, pre-printed forms was so they could use colors and watermarks that would not register during scanning for more accurate reading. Thanks to OMR software, it became possible to create templated forms and then remove the form image during the reading process to ensure that only marked information remained.
Take Control of OMR Forms with Accusoft SDKs
Accusoft’s FormFix forms processing SDK features powerful production-level OMR capabilities. It not only detects the presence of check or bubble marks, but can also detect markings in form fields, which is particularly useful for determining whether or not a signature is present on a document. Capable of reading single or multiple marks at 0, 90, 180, and 270 degree orientations, FormFix can also recognize checkboxes and be programmed to accommodate a variety of bubble shapes. Its form drop-out and image cleanup features also help to ensure the highest level of accuracy during OMR reading.
For expanded forms functionality, including optical character recognition (OCR) and intelligent character recognition (ICR), developers can also turn to FormSuite for Structured Forms. Featuring a comprehensive set of forms template creation tools and data capture capabilities, FormSuite can streamline forms processing workflows and significantly reduce the costs and errors associated with manual data entry and extraction.
Find out what flexible OMR functionality can do for your application with a fully-featured trial of the FormSuite SDK. Get started with some functional sample code and explore FormFix’s features to start planning your integration.