Innovating Healthcare with a Total Experience Strategy
For years, the user experience (UX) and customer experience (CX) have been treated like completely isolated concepts. However, organizations, particularly those within the healthcare space, have recently realized that this approach has stark limitations.
In actuality, healthcare with a total experience strategy should be the standard approach for providers across the entire ecosystem. Below, we examine how organizations can innovate in the healthcare field by adopting such a strategy.
What Does Total Experience (TX) Mean for Organizations?
Before we delve into innovating healthcare with a total experience strategy, it is essential to lay the foundation for this discussion by addressing the key tenets of TX. TX provides a smooth user experience for both patients and employees, especially clinicians, across multiple platforms, channels and technologies. It combines four critical components of client, employee and systems architecture.
The four main goals that TX aims to improve include:
- Customer Experience (CX)
- Employee Experience (EX)
- Multi-experience (MX)
- User Experience (UX)
At its core, "total experience" is a concept that is founded on a straightforward principle – the experiences of all stakeholders across an entire organization are interconnected. This concept includes the experiences of consumers or patients, employees, organizational leaders, etc. In theory, organizations can enhance the experience of everyone who engages with the organization by addressing these interactions as interrelated.
Healthcare provider CIOs can advance a TX strategy across their digital journeys by engaging clinical, and corporate stakeholders to develop an organizational TX roadmap that will enable healthcare workers to reimagine these journeys while avoiding clinician burnout.
How Can Organizations Shift Their Focus to the Total Experience?
If organizations want to develop a cohesive total experience strategy, they must address the four pillar components of brand interactions.
Thought leaders at McKinsey theorize that predictive analytics will be integral to enhancing experiences with brands in the future. Once healthcare leaders understand these journeys, they can implement meaningful changes to improve the total experience.
Accomplishing this will require organizations to streamline internal and client-facing business processes by utilizing hyperautomation. The hyperautomation strategy allows organizations to:
- Effectively collect and structure data to use it to guide decision-making
- Improve data leveraging capabilities to help leadership use analytics
- Understand the experiences of shareholders, employees, users and customers to illuminate areas for improvement
This business strategy involves using several carefully selected technologies to automate as many tedious processes as possible. Taking a hyperautomation approach – automating everything that can be automated – can reduce the burden on employees while also increasing operational efficiency.
How Does TX Relate to Healthcare?
While healthcare is a universal industry that everyone must use, stakeholders must prioritize positive brand experiences. However, the healthcare system is often overburdened. Protecting business continuity can be a significant challenge between worker shortages and an ever-increasing demand for services.
Therefore, organizational leaders must strive to innovate healthcare with a total experience strategy. Such a strategy will create a better working environment for providers. A proper total experience strategy will also facilitate better interactions between the healthcare organization and its patients.
This approach will lead to less employee turnover and improved morale. Additionally, a comprehensive total experience strategy will help maximize the productivity of every team member. In addition, an extensive experience strategy will increase an organization's ability to provide care for patients with better and faster access to data and resources. This increase will improve patient outcomes while simultaneously insulating the organization from costly legal action.
Use Cases for Healthcare with a Total Experience Strategy
Healthcare organizations can apply a data-driven approach to several clinical and non-clinical processes to improve the total experience. These use cases are as follows:
Clinical Use Cases
By implementing the right technologies, healthcare organizations can enhance the quality of care in ambulatory environments. This model will reduce processing time and increase the accuracy of communication. These technologies make traditionally tedious processes such as indexing or searching patient records much more efficient. In turn, this expedites the delivery of care and improves patient outcomes.
Additionally, data-driven strategies powered by innovative technologies can eliminate the need for faxing orders and prescriptions. Instead, care providers and others involved in the healthcare journey can seamlessly share information much more efficiently.
Data-driven tactics can also improve record-keeping and document batching capabilities. Healthcare organizations can use intelligent document capture tools to classify vital documents. This automation minimizes confusion while allowing the organization to maintain more accurate electronic health records.
Non-Clinical Use Cases
On the non-clinical side, data capturing technologies and hyperautomation can significantly improve administrative tasks, such as invoicing processing.
Healthcare invoices are notoriously tedious to process due to the volume of documents. Intelligent document processing solutions can transform information trapped in documents into data to help healthcare organizations expedite this process and improve the total experience for patients, employees and vendors.
Additionally, coupled with the TX strategy, data-driven processes can reduce the burden on human resources personnel. This will improve morale, increase compliance and optimize the accuracy of vital documents.
IDP: Facilitating Better Healthcare with a Total Experience Strategy
While many considerations must be addressed when evolving healthcare with a total experience strategy, data collection is one of the most vital.
Healthcare organizations cannot implement a comprehensive experience strategy unless they can efficiently capture, classify and extract data into a usable, structured format. In order to accomplish this, they must adopt sophisticated, intelligent document processing (IDP) solutions.
The best solutions will allow healthcare organizations to:
1. Transform Data into Actionable Intelligence
IDP technology, which is the foundation of any hyperautomation initiative, can allow organizations to process and convert massive amounts of information efficiently.
Leading IDP technology leverages machine learning, artificial intelligence and natural language processing software to extract information from a broad range of documents, including physical forms and digital files.
Once the information is extracted, it is transformed into actionable data that can be applied to decision-making and reveal insights into the experience of users, employees and patients.
2. Easily Integrate with Key Business Systems
Additionally, premier IDP solutions will easily integrate with existing business systems such as electronic health records (EHR) and enterprise resource planning (ERP) technologies. This integration will allow healthcare organizations to eliminate data silos and improve information transparency across all brand experience touchpoints.
3. Increase Productivity and Accuracy
IDP technologies will ultimately lead to increased productivity and improved accuracy of data. This clarity will allow healthcare organizations to deliver a higher quality of care to patients while also optimizing the impact of each staff member. In addition, improving data accuracy will have a cascade effect that benefits all core business processes.
Start Your TX Strategy with IDP
If you are ready to revolutionize healthcare with a total experience strategy, stakeholders must invest in proven intelligent document processing and hyperautomation technologies, such as Ephesoft Transact.
Our leading-edge solutions are trusted by organizations operating in a broad range of industries, including the healthcare sector. Get a free trial of our intelligent document processing solution or contact us to learn more.
Jump On Board with These 5 Automation Tech Trends
Global events – a thirst for remote access and a labor shortage among them – have intensified the desire for maximum automation. Executives worldwide say that since the start of the pandemic, the adoption of digitization and automation technologies has accelerated (1). Those events also exposed weaknesses in legacy systems, further igniting change and advancement.
Hyperautomation and cloud solutions continue to spur the need for even more nimble AI. Low-code/no-code solutions are coming to be seen as essential for future AI and ML tools. On the horizon is the maturing of integration platform as a service (iPaaS) – and bold new worlds of harnessing “the unknown” for intelligent document processing (IDP).
How much progress has been made? And, what will this year bring? Here are the five big trends to watch.
Trend # 1: AI is Still Huge and On the Rise
The AI software market encompasses applications that leverage AI, from machine learning (ML) to deep learning. AI represents a broad range of methodologies that teach a computer to perform tasks as an “intelligent” person would do them. With applications across endless sectors and industries, “worldwide artificial intelligence (AI) software revenue is forecast to total $62.5 billion in 2022, an increase of 21.3% from 2021, according to a new forecast from Gartner, Inc. (2).”
Demand for AI technologies and associated market growth is closely tied to organizational AI maturity levels. “Enterprises continue to demonstrate a strong interest in AI, with 48% of CIOs in the 2022 Gartner CIO and Technology Executive Survey responding that they have already deployed or plan to deploy AI and machine learning technologies within the next 12 months (3).”
One avenue of development and implementation: The notion of “citizen technologists” (e.g., citizen data scientists and citizen integrators) as well as the evolution of the citizen developers who can now leverage AI using low-code/no-code tools, without requiring in-depth technical or AI expertise. The promise: low-code/no-code tools make the technology more accessible and democratizes AI.
This stands to be what observers say will be an evolutionary year for AI as the technology becomes more accessible, easier to build and deploy.
Trend # 2: The Forecast - Mostly Cloudy
Recent events worldwide have fueled cloud growth, lending strength to such market drivers as platform technologies, customer experience (CX) and digital supply chain. Workforce shortages continue to create more demand for automated solutions and cloud platforms to make up for the loss of labor. The lingering global pandemic continues to expose issues with legacy on-premises ERP and accelerate interest in new cloud counterparts of ERP.
Expect an ongoing rise in adoption of hybrid and multi-cloud services in 2022, with the expectation from companies that they can integrate their data across these environments, as well as manage cloud spending and performance. Confidence in the security of public cloud is also on the rise. Cloud has proven itself during times of uncertainty with its resiliency, scalability, flexibility and speed. Hybrid, multi-cloud and edge environments are growing and setting the stage for new distributed cloud models and wireless communications advances could push cloud adoption higher, especially in such areas as mobile banking, healthcare and governments.
Gartner has forecasted that global end-user spending on worldwide public cloud services will hit $482 billion this year. “Additionally, by 2026, Gartner predicts public cloud spending will exceed 45% of all enterprise IT spending, up from less than 17% in 2021(4)”. Vendors are ready to accelerate market appeal and adoption by adding hyperautomation capabilities in the form of low-code/no-code toolkits, as well as to create packaged integrations with commonly used applications to reduce implementation costs and ongoing maintenance overhead.
Trend # 3: Hit the Hyperdrive into Hyperautomation
Hyperautomation looks to automate everything that can be automated – an approach that organizations continue to strive for to help companies pinpoint, vet and automate as many business and IT processes as possible. Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms, including:
- Artificial intelligence (AI)
- Machine learning
- Intelligent document processing (IDP)
- Event-driven software architecture
- Robotic process automation (RPA)
- Integration platform as a service (iPaaS)
- Business process management (BPM) and intelligent business process management suites (iBPMS)
- Low-code/no-code tools
- Packaged software
- Other types of decision, process and task automation tools
The global hyperautomation market is expected to continue significant growth in part due to increasing demand for RPA technology. But research suggests that the next step is to fully integrate RPA with AI and machine learning tools to achieve hyperautomation and reduce the need for human intervention. This should help hyperautomation reach its estimated market target of $46.4 billion by 2031.
Expect the continued growth of hyperautomation initiatives to increase the need for high-performing fusion teams, multidisciplinary groups that blend technology or analytics and business domain expertise, and share accountability for business and technology outcomes.
Trend # 4: Enterprise Automation and Integration: Enter iPaaS
Cloud-based integration platforms and hybrid on-premises/cloud models of this service aim to overcome the challenges with custom integration work, complex coding and server-based challenges. As the importance emerges of low-code/no-code applications that provide great benefit without requiring that deep-technical expertise to achieve results, the time is getting increasingly right for integration platform as a service (iPaaS).
iPaaS solutions are low-code/no-code cloud tools that connect systems in a modern, scalable way to easily flow data from various systems, such as IDP, into business applications and workflows across the enterprise to achieve seamless end-to-end automation. iPaaS provides interoperability at scale which is essential to hyperautomation.
Enterprise automation has evolved to combine powerful tools. Combining IDP and iPaaS, for instance, allows the business to use one capture system for the whole enterprise. Data can be shared and repurposed between multiple departments and then sent to business intelligence (BI) systems or ECM/Content Services for long-term document and data management.
The iPaaS software market is anticipated to rise at a considerable rate during the forecast period, 2022 to 2029. This year, in 2022, the market is growing on course and, with the rising adoption of strategies by key players, the market is expected to rise over the projected horizon (5). Analysts project the iPaaS market size is expected to continue its growth from $3.3 billion last year to almost $14 billion by 2026 (6).
Trend # 5: IDP Has Potential to Skyrocket
Intelligent Document Processing (IDP) is the process of automatically transforming documents from unstructured or semi-structured formats into structured data that can be digested by any application. Significant value comes from eliminating manual data entry, significant time and cost savings and improved data accuracy. IDP forms one of the building blocks to enable hyperautomation, since all automation projects require data in a structured format. This foundation and the critical need for actionable data will set the stage for IDP to become a breakout, core technology.
Overall adoption of IDP is expected to hit 55%-65% annually through 2022, with an under-penetrated unstructured IDP segment growing at a faster rate than semi-structured (7). Through this year, look for IDP vendors to continue to focus on achieving the elusive 100% straight-through-processing (STP) rate with innovative AI models, helping to propel the global IDP market size from about $800,000,000 last year to $3.7 billion in 2026 (8).
The IDP market has also focused in the last few years on the “known” – known document types, expected data and predictable document flow. There is immense value in having a solution that can use technology to tackle the unknown – that which is using computer vision technology to quickly understand any document type, often referred to as a universal document. Leaders in the IDP industry are working toward being able to process this well using advanced and adaptive AI.
Summary
Everyday comfort with advanced technology is combining with powerful tools to collect and present unprecedented amounts of data to change the very fabric of decision-making in business – and elsewhere. There are always bumps in the road but automation’s evolution will continue to gather speed much faster and broader than anticipated. Hold on and don’t let go!
Download the full report here.
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Footnotes:
(1) “What 800 executives envision for the postpandemic workforce,” McKinsey Global Institute, 2020.
(2) “Gartner Forecasts Worldwide Artificial Intelligence Software Market to Reach $62 Billion in 2022,” Gartner Press Release, November 2021.
(3) Ibid.
(4) “Gartner Says Four Trends Are Shaping the Future of Public Cloud,” Gartner Press Release, August 2021.
(5) “iPaaS Software Professional Market 2022 Global Share, Growth, Size, Opportunities, Trends, Regional Overview, Leading Companies, And Key Country Forecast to 2029,” Precision Reports, 2022.
(6) “Integration as a Platform Service Market with COVID-19 Analysis, by Service Type, Deployment Model, Organization Size, Vertical and Region – Global Forecast to 2026,” ReportLinker, 2021.
(7) “Intelligent Document Processing (IDP) for Unstructured Documents Going Beyond Templates and Rules,” Everest Group, 2021.
(8) “Intelligent Document Processing Market by Component (Solutions, Services), Deployment Mode (Cloud, On-Premises), Organization Size, Technology, Vertical (BFSI, Government, Healthcare and Life Sciences), and Region – Global Forecast to 2026,” Intelligent Document Processing Market, 2021.
Intelligent Document Processing FAQs
For many companies, processing huge amounts of data in a wide range of formats and sources can feel overwhelming. Intelligent document processing (IDP) helps alleviate and eliminate that stress by leveraging machine learning algorithms and artificial intelligence to read and understand documents.
With IDP growing in popularity, there are a lot of questions that come with it. Here are the answers to some of the most frequently asked questions about IDP to help you better understand what it is, how it’s used and its benefits.
Why Is Intelligent Document Processing Becoming a Necessity?
For even small and medium-sized companies, the sheer volume of paperwork and documents that need processing can create stacks of incomplete tasks and require hours of tedious work to accurately transcribe the information. IDP streamlines that process to help companies save time, money and resources. IDP helps your company focus on what matters rather than on time-consuming manual tasks that can (and should) be automated.
What Is the Difference Between OCR and IDP?
Optical character recognition (OCR) converts an image of text into machine-readable text. This is great if you only want to have the document digitized, but it has its restrictions. The biggest downfalls of OCR solutions are that 1) the document must be based on a specific template, and 2) OCR only focuses on digitization.
This means that a document has to be formatted according to approved rules or OCR cannot process the document. And once the physical document is digitized, OCR does not make the data searchable, extract context or interpret the data, so it still requires time and attention to be processed.
While OCR can process some documents, it falls short when dealing with semi-structured, unstructured or handwritten documents.
IDP is a major advancement that utilizes OCR for only part of its document processing solution. It also utilizes machine learning in concert with advanced AI technologies to mimic cognitive abilities. Not only can IDP capture and digitize documents correctly, but IDP can also classify the document and extract all relevant data. That data is then automatically distributed to the correct workflows as necessary.
While IDP can be more expensive, it is more useful than OCR and requires significantly less manual interface to achieve better results for a broader range of documents.
Which Technologies Are Applied to Develop IDP Solutions?
An IDP solution actually consists of a series of other technologies working in unison to supplement and strengthen each other. By doing so, IDP doesn’t have to reinvent the wheel by recreating an existing solution.
Some of the technologies that are included in an IDP solution include:
- OCR
- Artificial intelligence (AI)
- Machine learning (ML)
- Neuro-linguistic programming (NLP)
- Computer vision
IDP solutions require a repository to store documents once they are digitized. This can utilize software and technologies like ERP, ECM, iPaaS, RPA, CRM, LOS, EHR/EMR and any other repository or application.
Is IDP Data Validation Accurate?
Data validation ensures that the IDP process is accurate and that no information is lost. Ephesoft’s IDP solution extracts meaningful data from any document, format and/or source. With ML working in tandem with AI, data validation becomes almost 99.9% accurate.
Does IDP Extract Data from Unstructured Content?
Yes, IDP can extract data from unstructured content. Unlike OCR, IDP can recognize and capture content in semi-structured, unstructured and complex documents and then extract the context of the document from the content.
Can IDP Process Handwritten Text?
Yes, IDP can process handwritten text. IDP is so powerful that it can simultaneously process mixed documents that combine digital and handwritten text. In fact, Ephesoft users report 88% accuracy with cursive handwriting recognition.
Does IDP Recognize Cursive Writing?
IDP can process handwritten text in any writing format, including cursive. With machine learning and AI, IDP can establish a continually growing database of rules that help it digitize everything from a doctor’s chicken scratches to the most elegant cursive in a handwritten letter.
Is IDP Scalable?
Yes, IDP is scalable. IDP has the capacity to process as many documents as necessary. In fact, the longer your company uses an IDP solution, the more accurate and efficient it becomes. Due to machine learning, IDP solutions can gain a repository of data that helps inform and refine future document processing tasks.
Is IDP Secure?
Ephesoft’s IDP solution can be trusted with sensitive documents. The IDP solution does not store any personal or sensitive information at any point in the digitization process. It is important to remember that IDP focuses on document processing—not storing or securing the information. While Ephesoft’s IDP solution is a secure process, it is not a storage solution for documents once processed.
Can IDP Be Used in the Cloud?
Yes, IDP can be implemented as part of a company’s cloud-based system, but it can also be used in a hybrid cloud environment.
Are There Other Names for IDP?
IDP is sometimes referred to as intelligent document automation (IDA). Both processes leverage AI and ML with document capture software to streamline and automate the processing process.
For more information on Ephesoft’s intelligent document processing solutions, please visit our webpage or learn more about Ephesoft Transact.
Focus on Interoperability and Rip Off the RPA Band-Aid
For years, robotic process automation (RPA) technology has been the gold standard for creating a seamless interaction between various programs. While this solution still has its value, emerging technologies provide enterprises with more efficient ways of sharing data between vital systems to drive automation.
As modern enterprises shift their automation approach away from only using legacy RPA-based solutions, they should turn their attention to technologies that create true interoperability between solutions in order to stay competitive.
What Is Interoperability?
Generally speaking, the term “interoperability” refers to the ability of various digital resources to connect and electronically exchange information with each other. Interoperability moves beyond the limited capabilities of RPA to enable truly dynamic interactions between enterprise systems.
Understanding the Enterprise Shift
The best way to understand interoperability is to consider the evolution of how data was shared between enterprise systems.
In its simplest form, a system that provides open interfaces and allows data to be freely passed in and out of the system would be considered “open.” Legacy enterprise software didn’t do a good job of supporting the easy sharing of data between systems. These legacy systems are typically described as “closed.” Sharing data between closed systems used to require “swivel chair” automation where an employee had to copy data from one system to another. This process was manual and error-prone.
Along came RPA which helped with automating the task of moving data from one system to another by focusing on recording mouse clicks and screen scraping to create “bots” that mimicked a task frequently done by a person. RPA's sweet spot has been in its ability to connect legacy enterprise systems that were closed or that didn’t provide a means for sharing data.
Today, most modern enterprise systems are being designed and developed with a focus on interoperability. These “open” systems will change how we approach connecting systems. As organizations embrace automation, modernize their enterprise systems, and, most importantly, adopt cloud solutions, the focus will shift from legacy approaches for data sharing, like RPA, to more flexible and powerful approaches to connecting their systems, such as integration platform as a service (iPaaS) solutions.
It’s More Than Connections
But connecting your systems isn’t enough. Data types and data volumes in organizations continue to grow. Much of this data is being stored across a vast sea of data silos. And, even more of it is unstructured and lacks the meaning necessary to make it discoverable or computable.
Interoperability isn’t just about connecting systems but also about connecting systems to the data they need. Intelligent document processing (IDP) solutions help unlock the valuable data trapped inside unstructured documents making it available to the systems that need it. It’s this combination of integration solutions, like iPaaS and IDP solutions, that will revolutionize how organizations approach automation in the future. Enterprises must work with structured data to have true interoperability.
Can RPA Be Saved?
For companies that have already invested in RPA initiatives, a similar approach to interoperability can be applied. RPA is typically used to automate redundant tasks. However, RPA requires structured data and is unable to work with unstructured data. This unstructured data consists of information that does not necessarily conform to set standards or rules that machines can understand
To convert this data into a usable format, organizations must deploy IDP solutions. Using RPA and IDP together creates a starting point for interoperability. While many other technologies can be connected and used outside of RPA and IDP, these two often form the cornerstone for interoperability. Therefore, the bandaid only has to be ripped off if RPA is left alone without the right data and integrations.
Practical Applications of Interoperability Solutions
Technology that facilitates more dynamic interoperability and data sharing can improve various aspects of an organization's day-to-day operations. These are three common use cases of interoperability technology.
Accounts Payable
When using traditional RPA technology, enterprises can automate repetitive tasks such as entering the details of an invoice into the AP system. But RPA solutions require using structured data, so they are limited if the data is not already in the right format, which will require manual data entry or the need for IDP. When RPA and IDP are combined, they eliminate the need to enter data into financial systems manually. But what happens when the user interface for the system changes? Or the data structure changes? RPA requires a constant effort to keep businesses up and running. While this is undoubtedly beneficial, interoperability technology can take processing invoices a step further.
By utilizing a combination of iPaaS and IDP solutions, organizations can automate more processes. They can also connect all of the various solutions and software that they are using. Their accounting or ERP software can then perform more dynamic tasks, such as identifying and reconciling discrepancies between what has been ordered, delivered and billed. These interconnected programs can process invoice exceptions, approve documents based on historical trends and identify instances of fraud.
Organizations across all industries can benefit from these enhanced accounts payable processing capabilities.
Customer and Account Onboarding
Both customer and account onboarding are some of the most tedious and time-consuming processes for businesses. Due to the complex nature of new customer onboarding, only a few aspects of this process can be automated. However, IDP technologies provide organizations with access to more structured data, facilitating better interoperability.
Taking an approach built on interoperability allows organizations to automate tasks such as analyzing public records, validating identifying documents and linking data silos to create a 360-degree view of new clients.
This technology can significantly streamline the entire onboarding process. The result? A more enjoyable experience for clients and significant cost-savings for the enterprise.
Digital Mailroom Automation
While it may be hard to believe, many organizations still receive and process a lot of mail. The only thing that really has changed is that mail comes in many forms, both paper-based and digital. Businesses have deployed RPA technology to help with automating this function with varying degrees of success. However, advancements in technology have made it possible for companies to move beyond the basic RPA bandaids. Specifically, intelligent document processing technologies enable businesses to transform all the incoming mail documents, whether paper or digital, into structured data that can then be shared with the appropriate system via an iPaaS solution. This data will allow companies to streamline their operations through interoperability.
Benefits of Focusing on Interoperability to Drive Automation
Achieving greater interoperability of core systems can offer significant benefits for organizations across many different industries. Specifically, approaches built on interoperability of systems can help enterprises within the banking, insurance, mortgage, healthcare and government spaces by allowing them to:
1. Enhance Productivity
The better each piece of software communicates, the more productive each staff member will be. Interoperability allows employees to speed up processes and tasks so they can spend more time with customers and less time performing redundant, time-consuming tasks.
2. Reduce Costs
Interoperability will also result in massive cost savings for enterprises. Interoperable systems are less brittle and can easily evolve as the business needs and systems change over time. This flexibility will prove more cost-effective over time compared to organizations that have invested heavily in RPA and have to deal with the looming RPA “bot sprawl” and legacy applications.
3. Improve Customer Experience
The most significant advantage of enhancing interoperability capabilities through intelligent data processing is improving the client experience. This will strengthen an enterprise’s brand image and accelerate responses, which will ultimately lead to more profitability.
Take Advantage of Interoperability
Corporations of all sizes need to look beyond simple RPA band-aids to full-enterprise, structured data solutions. By prioritizing how data interacts across all platforms, interoperability can be achieved and businesses will run smoother, more efficiently and with an improved bottom line.
If you would like to learn more about the importance of system interoperability and our IDP solutions, contact Ephesoft. We provide our clients with solutions designed to enhance productivity, reduce costs and enhance the customer experience.
Ephesoft Transact 2020.1, Mobile and Cloud HyperExtender are Released Globally
Improving customer experience and solving customer’s business, content and process challenges are at the core of Ephesoft’s mission. The internal process for next-gen technology stems from listening to our customer’s feedback, current and new business challenges, wish list items and our own R&D. Since Ephesoft’s humble beginnings in 2010, our founder and CEO Ike Kavas has instilled the drive for innovation and growth. Stagnation is not an option. Today, I’m excited to share with you some of the latest and highlighted features of Ephesoft Transact 2020.1.
Highlighted features in Ephesoft Transact 2020.1 include:
- Web Services: Additional API web services are available with Ephesoft Transact 2020.1, providing enhanced programmatic functions within Batch Classes and Document Types. These APIs allow customers to maintain similarities between document types and index field extraction rules at a much larger scale for those large Batch Classes.
- Magnification Mode: Magnification Mode enhances text magnification on both the Classification and Validation Review screens. This allows easier view options for users, which will review and validate efficiently.
- Importing Global Document Types: The Import Batch Class dialog box now includes new options for handling Global Document Types in the Batch Class import process. This upgrade preserves the administrator’s preferred Document Type in the host environment and maintains all index fields and extraction rules as defined during the Batch Class import.
- Silent Installer for Web Scanner: A property file-based silent installer has been created to allow IT administrators to push out installations or upgrades to the Web Scanner client software remotely to the end-user workstations. When utilizing the silent installer end-user workstations no longer need to manually uninstall and install a newer version of the Web Scanner Client.
- Language Support: With the ongoing customer expansion in the APAC region, we are working on expanding our languages. Simplified Chinese, Traditional Chinese and Thai are in Beta.
Also included in this release are two add-on modules: Ephesoft Cloud HyperExtender and Ephesoft Mobile.
Ephesoft Cloud HyperExtender
While the initial release of Ephesoft Cloud HyperExtender was in 2019 in the United States, the platform has undergone many enhancements with the latest version of Ephesoft Transact 2020.1. Customers typically use the Cloud HyperExtender to increase performance by off-loading the OCR function into the cloud. OCR is the most power-intensive process, so by pushing data up to the cloud, users can process their content up to 10 times faster.
Ephesoft Mobile
Ephesoft Mobile provides an easy and reliable way to ingest and upload files into Ephesoft Transact from any mobile device, accelerating workflow and business processes. Ephesoft Mobile uses your mobile device’s camera to capture documents. It includes new and enhanced features such as an improved user interface, live edge detection, foolproof image cropping and enhancement filters to allow your mobile-centric customers to connect with Ephesoft Transact and deliver real-time productivity. Whether you decide to use our fully functional Mobile application or the SDK to create your own mobile application, we have you covered.
For more information on Ephesoft solutions, please visit https://ephesoft.com/products/ or contact us here. For documentation, please visit our Ephesoft Docs.