Document Automation - KlearStack AI

Understanding Digital Document Processing

Enterprises are now taking steps towards digital transformation. They have started converting manual and physical data and started adding it to the systems. This is what Digital Document Processing is all about. But this needs thorough planning and the right document-processing solution for your enterprise.

Digital document processing transforms analogue data to a digital format so that these documents can be adapted and integrated into the day-to-day business processes of your enterprise. Through the usage of an intelligent document processing system that has the ability to extract and store data at the backend, an enterprise can have a digital copy of the analogue data and replicate the original structure and its contents.

What is Digital Document Processing?

Digital document processing is ideal for converting documents that have the same formats all throughout. Government IDs & passports are some of the many identical formats which can be transformed into digital documents with 100% accuracy. However, with the advancement in Artificial Intelligence (AI) and Machine Learning (ML) technologies, it has become efficient to extract data from unidentical formats such as invoices, receipts, purchase orders and so on.

AI and ML technologies have allowed enterprises to achieve more than just extract data from documents. Digital document processing has the ability to classify and validate information as well. It speeds up the digital document processes further through the use of automation. It also helps to structure the unstructured data.

Robotic Process Automation (RPA) and Natural Language Processing (NLP) are additional tools that also allow for transformation to happen swiftly from analogue to digital, with a reduction in errors.

How Does Document Digitization Process Work?

Digitization of document process can be done through computer vision, neural networks or manual processes. Usually, the process of digitizing analogue data into digital data is done by following these steps:

1. Categorization and Extraction:

Digital document processing solutions are rule-oriented. Programmers create certain pre-defined extraction rules before the actual work starts. This can include defining a category or a format of the documents. Once these are defined, the team can then extract the layout and structure from the documents.

2. Extraction of data from document:

There are many methods that different teams use to automate text extractions. Optical Character Recognition (OCR) scans the document for the typed text from manual documents and transforms it into data. Smart character recognition, a type of handwritten text recognition (HTR), can also recognize standard text along with different fonts and styles of handwriting.

3. Detect and Rectify Document Errors:

OCR technology is not 100% error-free. Extracted data may, at times, require a manual review as well. If a document is not processed or errors are identified in the data extraction process, the document is flagged. The flagged document can be reviewed by a human and through manual data entry, it can be fixed.

4. Storing data and Documents:

The extracted document is then stored in a format that will allow it to be integrated with the existing applications.

Digital Document Processing: Best Practices to Follow

Whether your enterprise is in the manufacturing industry or providing financial services, below mentioned are some universal best practices to follow to leverage digital document processing solutions to the fullest.

Document Categorization:

Organize and author documents according to their function. This help in the clarification of relative information for concise data extraction.

Data Conversion:

Unstructured and semi-structured data need to be converted into structured data which can then provide useful information for further automation enhancement.

Integration and APIs:

Once the data is digitally stored, it is important that it is accessible by the concerned teams. Discussions need to take place internally to understand the business needs and what integrations will be required for it.

Limitations of Digital Document Processing

Using One Format Only:

Digital document processing uses pre-defined rules of data extraction to transform manual data into digital form. This type of data capture works very well for structured documents. But for large volumes of unstructured data or documents that have inconsistent formats, the process can have errors and require frequent manual checks.

Dependency on Processing Experts:

When issues and errors arise, they are flagged for manual checks. This can be again a time-consuming affair and might require additional human resources for this.

Continuous Improvement:

Document processing systems do not have much operational visibility into how your document process is functioning. It may not highlight the errors that are usually slowing the process down.

Conclusion

We have understood how digital document processing works, and what are its benefits and got insights into its limitations as well. Enterprises are looking for these solutions to reduce the burden of processing documents manually and automating them.

KlearStack AI is an intelligent document processing platform that understands the document contextually and has the ability to extract data from unstructured documents as well. This allows users of KlearStack AI to extract information from documents such as government ids, and passports as well as purchase orders, invoices and receipts. To know more about KlearStack AI, schedule a demo with our experts.

Automate Document Centric Business Processes With KlearStack

Anyone who has run a business for a considerable time will understand that documentation is more than just a formality. This is true to such an extent that there are businesses that have grown around documentation and information handling alone.

Now we have entered an era where data is everything, probably even more precious than gold. For something that has so much value attached to it, its processing should not be casual. Long story short, document-centric processes in organizations should be automated to make them more conducive for data analysis. Automate document centric workflows to extract more value out of your business.

Document Centric Processes With A Scope For Automation

● Electronic Form Filling

One of the most important document-centric processes in a business is populating the fields in a digital form. Customers have to fill different kinds of forms to avail the services that are offered by a business. For example, in a banking set up, customers fill forms for opening new accounts, applying for loans, getting net banking facilities, etc.

The details mentioned in all these forms are different. The most complex problem, however, is that since all databases are now electronic, there will have to be one designated professional in all departments who will read these details from the physical forms and then type everything in the relevant fields. Without automation this process is highly cumbersome and prone to errors.

KlearStack provides a robust solution to automate document centric business process like this. Our artificial intelligence-based OCR solution is not only capable of extracting text out of physical documents and digitizing it, but also helps businesses in populating the different fields of electronic forms automatically. Machine learning plays a big role for this methodology to work accurately.

● Document Review

Not more than a decade back when paper-based record-keeping was more prevalent, every business had to invest in archiving it’s documents. Record-keeping was essential, not only for the purpose of legal technicalities, but also for referencing and revisiting older cases.

If we take the example of a legal firm, all such documents were mandatory to keep because time and again, lawyers need to revisit old case files for the purpose of referencing. The problem with the older system of archiving was that with physical documents, it took hours to scout through files just to find that one single paragraph that was relevant for a particular problem.

KlearStack presents a solution for this problem with optical character recognition. We enable the digitization of all types of physical documents, old and new. Be it handwritten documents or printed ones, our tool can digitize the text present in them highly accurately and automate document centric business processes. Once this is done, we compile everything in a searchable format. Entering only a few key words will help you find what you actually require within seconds.

● Image Collection and Analysis

With smartphones becoming more popular, a lot of the professional duties have also been transferred to mobile-based applications. The collection and representation of data can be done on mobiles itself. Moreover, sharing of information is also being done by the same means, very commonly via images.

If a business requires to extract information from images directly without having to type it, it will require optical character recognition. KlearStack helps to automate documents centric businesses in not only scanning and extracting information out of images, but also compiling relevant images and classifying them as per usage.

Machine learning and artificial intelligence enables our tool to segregate components within the image itself, so that only relevant outputs of text digitization are given to the end-user.

● Data Analysis From Document Database

The pertinent question still remains that why do businesses that are entirely document-centric need such extensive documentation in the first place. The end use case of such extensive documentation is not just record-keeping, but also carrying out decision analytics.

Analysis will also occur manually if the process behind preparation of the documents and databases was completed manually. As one can imagine, if manual documentation takes hours to complete, analysis will just add to that time frame, over and above.

Another problem is that simply changing your physical documentation styles to a digitized style, will not reap you enough results for proper analysis. What we want to indicate here is that your company will require a tool that performs the basic optical character recognition process 100% accurately, but is also enabled by artificial intelligence to extract insights from the information.

KlearStack, in a nutshell, provides this utility to its customers by using and leveraging the benefits of natural language processing, machine learning, text analytics, etc. We make our tool capable of generating actionable insights from the information that it is digitizing.

Summing Up

KlearStack has been the torchbearer for bringing about automation in document centric business process. Automate document centric business processes with KlearStack’s AI-based OCR solutions. From data capturing to optimizing documentation-based workflows and providing crucial insights for analysis, KlearStack helps with everything. For more details, feel free to reach out for a free demo.

Document Automation Using Straight Through Processing

We live in a fast-paced, on-demand world where we want almost everything to happen instantaneously. Be it calculations or searching a document on desktop or on drive, we want such activities to happen in no time. Business processes, over the period of time, have evolved immensely and have been able to automate many such operational processes. Straight-Through Processing is one such aspect that provides the much required edge to end-to-end document processing automation.

Intelligent document automation is the need of the hour as digitization of the physical documents promises to help businesses achieve non-linear growth. Reduced paper clutter on your desks will help increase the ability to focus on core aspects of business and fill the industry gaps by outsourcing mundane tasks such as data entry and filing invoices and receipts. Straight-Through Processing adds an additional level of intelligence to the document process wherein documents that match certain criteria are automatically processed without any human intervention.

Before we deep dive into document automation and Straight-Through Processing even further, let us first understand the issues with existing document processing methods.

Challenges of Processing Documents

When it comes to processing documents manually, challenges are plenty. Here are some of the many challenges of processing documents without any automation:

High Error Rates:

Documents that are processed manually, may contain a lot of errors as these documents are manually entered into the system one by one. Invoices and receipts have much crucial information that has to be highly accurate such as unique document numbers, total billing amount, item descriptions and so on. If these details are not accurately added to the system, it may lead to many issues with vendors and other partners.

Accuracy can be only improved through the adoption of appropriate technology and organizations that do adopt such automation solutions, will reduce their margin of error drastically.

Operational Inefficiencies:

Various types of operational inefficiencies can occur if there is no automation in place for processing documents. Inefficiencies such as sending the invoices or receipts on time, payments being processed without final check of documents, untimely coordination between accounts department and other departments, etc. Such management related issues can slow down the growth of the business for the organization at large.

Backlogs:

One of the key issues of not having document automation is the issue of clearing documents on time. Since documents are processed manually, the time taken to clear each and every document is quite high. And if a peak business season arrives, then the backlogs will keep on increasing. This becomes a direct hurdle for business growth. Organizations are not able to scale up in such scenarios as they are not able to process documents that they have in their stockpile currently.

Lack of Business Focus:

As mentioned above, backlogs and operational inefficiencies can occur if there is no document automation in place. Apart from that, for organizations to increase their revenues, they need to think of new avenues that they can focus on and scale up in. But such critical thinking may not take place if the firm is struggling to service the existing clientele due to lapses in the documentation.

It, therefore, becomes highly important for organizations to outsource or automate document-related activities if they are looking to increase their service offerings.

Underutilisation of Human Resources:

Processing documents manually is a mundane and monotonous task. Such tasks may also lead to a decrease in employee morale over a period of time if there are dedicated personnel performing such activities on daily basis.

Critical thinking and ways to use human resources to their full potential should always be an aim for a firm and therefore, such activities should be considered for automation. An increase in turnover rate due to a decrease in employee morale may not be the most suitable way for an organization to progress.

Automating Businesses with Straight through processing (STP)

Intelligent Document Process (IDP) is the way forward to automate document driven processes. Using advanced AI-driven technology that can detect and extract information intelligently, even from handwritten documents, will drastically reduce the overall processing time for documents and improve operational efficiency.

Straight Through Processing adds an additional level of maturity when it comes to processing documents. OCR technology can help extract information accurately and contextual AI can help to capture information from any and all kinds of invoice or receipt templates.

But what Straight Through Processing really does is that it enables end-to-end automation for documents that match certain data validation criteria. This removes/minimizes the need for human intervention and the information from the documents is stored on the cloud directly.

Straight Through Processing enables segregation of information that match the unique set of criteria set by the organization and based on the set criteria, information from documents is extracted, processed and stored automatically.

Document Classification, Data Extraction based on WYSIWYG (What You See Is What You Get) principle and Postprocessing (Data Validation and Data Transformation) are the three main crucial stages of document automation. Once the extracted information is matched with the set criteria, Straight Through Processing takes place. KlearStack AI can directly store information on QuickBooks or SAP. If the KlearStack API is used, then the information can be stored on any software or tool.

Conclusion

KlearStack AI can enable complete automation for several types of documents. Our self-learning AI-driven technology will ensure that data is not only accurately extracted but also contextually understand the document and fill in the information appropriately. If you would like to know more about our solutions, click here and connect with us.

Intelligent Document Automation – A Better Way to Paperless AP Automation

In the previous articles, we have seen how traditional and template-based OCRs drastically failed the idea of setting up a paperless AP automation. The impact of template-based OCRs was so horrible that the employees literally switched their Google searches back to “how to convert PDF to Excel manually”!

Accounts payable (AP), being an important department in an organization, has faced some of the scariest experiences with OCRs. Since traditional OCR solutions are dependent on a set of rules and unable to interpret data or understand its context, employees had to perform all these tasks manually. After converting the scanned documents to spreadsheets, employees manually check and verify all the documents for data integrity and then route them for stakeholders’ approval.

If OCR solutions are unable to deliver the promised value, how to achieve paperless AP automation?

To your surprise, OCR scanning is not outdated, yet. Instead, it can be integrated with Artificial Intelligence (AI) to produce a better way to paperless AP automation. When AI combines with OCR scanning, the data extraction software doesn’t depend on rules or templates. AI provides OCR engines with the ability to scan documents intelligently and interpret the document fields rather than depending on their positions.

The process is referred to as intelligent document automation wherein the AI-enabled OCR solutions understand the context of data before extraction, irrespective of the document (invoice) format, layout, and structure. Therefore, the use of templates reduces to zero percent making the paperless AP automation processes entirely seamless. It also makes the AP department free of performing repetitive, yet important tasks of maintaining templates, validation and verification of scanned invoices.

Benefits of Intelligent Document Automation in Accounts Payable

Apart from this, intelligent document automation also provides some other benefits to the organizations. Let’s take a look.

1. Saves time and money

With AI-enabled OCR solutions, employees don’t have to spend time creating thousands of templates for every other invoice structure. They just feed the invoice into OCR and the latter itself learns from the data set to extract relevant field data from the invoice. Moreover, the time invested in manual verification and approval of invoices is no more a heavy burden.

Similarly, you won’t have to spend money on employee training. Since, human intervention is significantly reduced in case of intelligent document automation, labor costs reduction becomes a by-product.

2. Improves accuracy and productivity

AI-enabled OCRs are self-learning ML models that do not require manual validations to confirm data integrity. Since they can interpret and understand the context of data, there is no room for errors. The in-built intelligent document decision support system automatically looks for errors and rectifies them.

Owing to a decrease in manual invoice processing, the AP department can now focus on other important financial matters, while AI-enabled OCR solutions do the needful. It enhances the overall productivity of the workforce by delegating repetitive tasks to OCR solutions.

Hence, the next time you search, “how to convert scan to Excel automatically,” focus on intelligent document automation instead of plain OCR scanning.

How to achieve paperless AP automation with KlearStack’s Intelligent document automation solution?

When it comes to implementing paperless AP automation in your organization, KlearStack is your go-to solution.

KlearStack is a cloud-based data extraction / data capture software that integrates the power of template-less, end-to-end automation, and document decision support with OCR scanning. It enables businesses to harness the power of intelligent document automation by leveraging computer vision, text analytics/NLP (Natural Language Processing), and adaptive learning.

When one of our clients asked us, “how to convert scan copy to Excel without human intervention,” here’s how KlearStack came up with a solution.

The Client’s Problem

The AP team at the client’s company was processing invoices at an approximate rate of $12 per invoice. Considering the number of invoices processed per month to be a thousand, nearly $12,000 on an average were invested in mere invoice processing.

Further, template creation and manual verification of invoices led to late payments and the client missed out on early payment discounts.

Guess what was the worst of all! The client’s business reputation was at stake as they received 36% vendor calls and emails for payment reminders.

KlearStack’s Intelligent Document Automation Solution

The client subscribed to KlearStack as a means for intelligent document automation. We gave them with our very simple image-quality prerequisites so KlearStack can interpret the text with high accuracy.

Since, KlearStack is entirely template-less and uses adaptive learning to understand the context of data, the client could insert all types of invoices in the AI-powered OCR and the latter scanned and converted the invoice into spreadsheets effectively. The client used KlearStack APIs to seamless integrate invoice data in their end-to-end AP workflow.

As a result, the client observed 200% improvement in AP team’s productivity, 20 times reduction in setup costs, zero capex, and 100% interoperability with REST APIs.

The best part is, we could achieve 90-95% accuracy in invoice processing and ~70% reduction in manual efforts within 90 days of implementing KlearStack’s intelligent document automation solution for the client.

If this is something you are willing to accomplish for your organization, book a consultation call with us today. We will tell you more about how KlearStack is a best fit for your invoice processing needs.

Reduce TCO of paper-based processes with paperless document automation

In the previous blog, we established a firm foundation for a paperless office in the form of invoice automation. Taking it forward, this post talks about the costs associated with paperless document automation. Since every organization has 20% structured and 80% unstructured data with vendor invoices forming a non-trivial part of the latter, reducing costs related to invoice processing is our primary goal.

The vendor invoice processing method we discussed in the previous article was entirely paperless and it brings its own costs along. In fact, the three other approaches – manual data entry, traditional OCR solutions, and template-based OCR solutions don’t even come close to the AI-based invoice processing technique in terms of TCO (Total Cost of Ownership).

Also, when it comes to managing the accounts payable (AP) processes, organizations look for the cheapest available solutions, at the time of buying decision. So, what do you think is the most affordable yet efficient means to handle AP processes – manual data entry, traditional OCR solutions, template-based OCR solutions, or AI-based intelligent document processing (IDP)?

Well, don’t stress out! We are here to help you with a fact-based comparison of all the four document processing techniques so that you can decide which is the best paperless document automation solution for your organization.

Manual Document Processing

Manual document processing involves a human to receive the document, manually enter the document data into internal systems/Excel sheets, process the document, send it for approval, and complete the desired action.

For instance, if we consider invoice processing, there’s no invoice reader or software that can convert invoice data automatically into Excel sheets for calculation. The AP department staff has to manually perform all the operations. So, we calculated the cost incurred in the entire process and even referred to few studies made by others. The average cost of processing came out to be $12 per invoice.

Not only that, manual invoice processing led to 32% late payments and 36% vendor calls/emails to remind the company of due payments.

Now, if you multiply the cost per invoice and the delay in payments to the number of invoices you process each month (maybe hundreds, thousands, or millions), you can get an estimate of the total monthly expense in invoice processing. Just don’t freak out for the time being.

Traditional OCRs for Document Processing

When OCR was first introduced to kick-start paperless document automation, it was not traditional as it did reduce the manual data entry tasks. OCR is a data extraction software which reads text from any image (scanned or photographed) automatically while reducing human intervention to an extent.

But that was not all. Traditional OCRs were unable to interpret the data they extract and also lacked the capability to store it in an organized manner. They could just scan the image and extract everything on the document only to feed a cluttered information in the internal systems.

In invoice processing, traditional OCRs could convert PDF invoice to Excel but failed to interpret the type of data and where it needs to be stored for easy processing. As a result, the AP staff had to manually interpret the extracted data and make edits to turn the clutter into analyzable data.

Hence, the costs were never reduced. Instead, the cost of setting up OCRs and again manually interpreting the extracted data added to the total expense. Invoice processing was never fully-automated with traditional OCRs.

Template-based OCR for Document Processing

As mentioned, 80% of an organization’s data is unstructured and it’s hectic to structure it manually or using traditional OCRs. Hence, the innovators came up with a template-based data extraction tools. In this, the user needs to define a template for each unique layout of document. These template-based tools are integrated them with traditional OCRs. Consequently, the OCR could now extract the document data based on the template structure and feed into the internal systems for further processing. The image/ PDF invoice data extraction process was going great for a while.

But here’s the rub. There’s no fixed structure for any document – even those of the same type. Let’s take the case of invoices. Every vendor has a different format for invoices. The fields in the invoice also vary with the type of purchase made. That said, it’s impossible to provide one template each for every invoice format.

Due to variability of the documents, template-based OCR could only automate invoice processing up to 40% and save 20% of the costs. The invoices that did not follow the already fed template were processed incorrectly and the AP staff was back on the job again, rectifying the mistakes and validating the extracted data for authenticity.

Template-based OCRs failed to interpret the data and were unable to understand the context of a field’s data. Instead they focused on the positioning of the fields in the invoice and made mistakes when the field positions were different from that of the template. This again required human intervention for correcting the mistakes.

Was affordable invoice automation still a far cry?

AI-enabled Document Processing

AI text recognition/ document interpretation became the first end-to-end automated document processing technique with the ability to interpret document data irrespective of the documents’ layout and text. It can understand the context of the data and eliminate the need for templates.

AI-enabled document processing is actually an integration of template-less OCR solutions and AI-based intelligent data interpretation. It combines machine learning along with natural language processing and computer vision to understand the context of data before and after OCR extraction and store it in internal systems with an added advantage of document decision support. That said, your unstructured documents can be mined into actionable insights with AI-based document processing.

So, if you use AI-enabled IDP SaaS solutions, you are actually boosting your business productivity up to 200% and reducing TCO up to 300%. What’s more? You can expect 90-95% of accuracy within 90 days of implementing it. Moreover, you are free from any template maintenance costs, hardware costs, and up-front license costs.

Given all the four scenarios of document processing, it is clear that manual processing can never be a cheap and efficient approach. Also, paperless document automation is very difficult with manual document processing.

Hence, we are left with OCR-based solutions with AI-enabled intelligence integrated with it. The fourth model, AI-based document processing, is indeed the best way to avail cost efficient yet productive paperless document automation.

Paperless Document Automation : KlearStack Way

KlearStack is an AI enabled data extraction and interpretation software with a perfect fusion of template-less, end-to-end automated, document decision support. It is a comprehensive solution to paperless document automation with an ability to reduce document processing costs while increasing the productivity of the business.

KlearStack uses AI text recognition along with ML and NLP techniques to interpret the document data and provides actionable insights after feeding it to the internal systems. Hence, if you have made up your mind for a paperless document automation solution with low TCO, KlearStack is your go-to solution.

Book a free consultation call to know more about how KlearStack can help you achieve paperless document automation.

Stay tuned for our next blogs on starting a paperless office.

Go Green with Yellow – How to Bring Paperless Office Culture?

Not long ago, the revolution of digitization started and many of the industries started moving towards paperless technologies for efficient management and optimal use of the resources. With the advent of cloud storage and digital document management, creating and sharing of the virtual documents have become the new norm. The papers are being replaced with the shareable documents that can be stored, shared, and signed digitally to completely avoid the hassle of physical document management. But there are multiple industries like legal, finance, healthcare, and banking that still employ the traditional paper-based document processing and that leads to increased costs and inefficient management of the documents.

Going paperless not just contributes to saving the environment but it also helps in making a complete shift in information sharing and processing in an organization. As the industries are realizing that the management of paper-driven information is expensive and not reliable, the shift towards paperless management is paving its way. The advantages of going paperless are numerous but the shift doesn’t happen overnight and may require a technological overhaul and changing the key business processes to adapt to the new culture.

Practical Strategies for Paperless Office

Some of the practical strategies that will help in making a shift and reducing the paper load in the industry are discussed below:

1. Redefining Business Processes:

To reduce the volume of paper in the industry, the first step is to identify the processes that are heavily reliant on the paper and then create alternate processes to reduce paper usage. Starting with the internal documents that are circulated inside the organization and then moving towards the external ones like contracts and proposals. As digital signature has got the same validity as the traditional one, using the electronically signed documentation can optimize the documentation workflows. Making digital copies of the meeting notes, handbooks, product manuals on the notes, and cloud will reduce the need for hardcopies and will also improve the sharing of information between departments.

2. Making a Technological Change

Every change comes with a better and equipped system to alter the processes and the transition to the paperless culture is possible by opting for the technical solutions which can optimize the unstandardized processes. As an influx of information and data is generated in industries every day and most of that is unstructured making it almost impossible to channelize it for resourceful purposes. People in the accounts and finance department are flooded with the paper-based invoices and payment orders and manual processing leads to delays and reworking.

By upgrading to the latest technologies (like Intelligent Data Extraction and Intelligent Document Processing), it becomes easier to handle the information and also structure the processes. Artificial intelligence and machine learning-based data extraction technology can automate the invoicing and payment order processing, reducing the need for paper-based invoices and receipts. Klearstack is based on intelligent document processing technology and has a self-learning model to increase the accuracy of the data extraction to 90% in 90 days. To support the goal of paperless office culture, making a shift in the infrastructure is imperative for every organization.

3. Taking Everyone With Change:

Without taking everyone on board, it won’t be possible to bring a change in the organization. Clearly define the objectives behind the change and convince everyone in the team to engage and support the activities. If the employees think about going paperless as just another exercise, it won’t drive any result. The management has to put the effort into educating their staff about the purpose of reducing paper processing in the industry and the benefits they can reap with the new paperless technologies. Setting actionable initiatives and engaging everyone to reduce the use of paper to create efficient processes, eliminate redundant data-entry tasks for a sustainable work environment.

Finally training the staff to use the newly employed software for data extraction and processing and setting a familiarity with the newly laid processes will help in paving a way to paperless culture in the industry. By simplifying the workflow with psychological and technological change in the organization, maximum benefits can be derived. Taking ideas and feedback from the staff about the change in the workflow and involving them in the process will lead to higher returns. However, no organization can completely eliminate the papers but by improvising the system with intelligent data processing and electronic document management system, the use of paper can be greatly reduced.

Switching to AI-based data extraction models like Klearstack will automate manual processing in the office and achieve paperless office culture within the organization. To know more about Klearstack solutions, download the free e-book now.

Conclusion :

It’s high time that organizations across all domains and irrespective of the organization size should adopt such AI based tools to reduce the wastage of resources and leakages in the cash-flow. To learn how KlearStack can help achieve your organization a complete paperless office culture , schedule a demo with our automation experts today!