The Ultimate Guide to Document Processing with AI and IDP

AI document processing is one of the ways to implement intelligent solutions in your business. Utilizing AI for document processing will automate manual efforts and complete paperwork more accurately.

Manually processing these documents is a time-consuming and error-prone task, hindering productivity and potentially impacting your bottom line. At Binariks, we understand this struggle. Having helped numerous clients streamline their operations through innovative solutions , we've witnessed the transformative power of artificial intelligence in document processing.

For instance, one of our clients, initially specializing in document management software for fax-dependent businesses, evolved into a comprehensive document and data automation solution, particularly benefiting healthcare clients. Yet, they were still focused exclusively on B2B activities and wanted to change their business model.

We also addressed HIPAA compliance and UI design challenges, delivering an exceptional MVP prototype. Our solution facilitated the client's transformation, empowering users with streamlined document automation capabilities aligned with their vision.

This comprehensive guide explores the world of AI-powered document processing (AI-DP) and Intelligent Document Processing (IDP). We'll equip you with the knowledge to understand how AI tackles document management challenges and discover some AI document processing tools that can revolutionize your business.

What is AI-powered document processing

Artificial intelligence fundamentally changed the approach to paperwork, and the AI market was valued at $1.4 billion in 2022. This number is constantly increasing and is anticipated to reach $12.8 billion in 2032. By using AI to automate document processing, businesses save a lot of trouble, which is why investing in AI has become the new trend.

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Let's break down the terms and clarify how AI-powered document processing stands out.

• AI Document Processing (IDP): This refers to a holistic approach that leverages artificial intelligence technologies like machine learning and computer vision to automate document processing tasks. IDP goes beyond simply extracting text (OCR) – it can classify document types, extract specific data points, and even understand the context of the information within the document.
• Unstructured Document Processing (UDP): This term encompasses a broader category that includes IDP. UDP refers to processing documents of various formats – emails, PDFs, scanned images, etc. – often lacking a standardized structure. While IDP falls under the UDP umbrella, it specifically uses AI to handle these unstructured documents.
• Optical Character Recognition (OCR): This is a foundational technology used in both IDP and other document processing methods. It essentially converts scanned images or photographs of text into machine-readable text. While OCR is a crucial step, IDP builds upon it by employing AI to understand the extracted text and its context within the document.

Here's an analogy to illustrate the differences:

Imagine you're sorting through a pile of receipts from different stores. OCR would be like simply reading the numbers and text printed on each receipt. IDP, on the other hand, would not only read the text but also understand it. It would categorize each receipt by store name, identify purchase details, and potentially extract the total amount spent.

While OCR focuses on text extraction, IDP utilizes AI to unlock the meaning and context within documents, transforming them into valuable and usable data for your business.

How does AI-based document processing work?

Here's a glimpse into the typical automated document processing workflow:

Uploading and pre-processing

• Users can upload documents through a user-friendly interface, which typically supports various file formats, such as PDFs, scanned images, and emails.
• The system performs initial checks on the uploaded document, ensuring it's a compatible format and free of any significant corruption.
• Pre-processing steps like image rotation or noise reduction might be applied to optimize the document for accurate data extraction.

Document classification and data extraction

• The AI engine kicks in, leveraging machine learning models to analyze the document and identify its type. This could be an invoice, a purchase order, a contract, or other pre-defined category.
• Once classified, the system employs advanced algorithms powered by Natural Language Processing (NLP) and Optical Character Recognition (OCR) to extract specific data points from the document.
• This extracted data can include names, addresses, dates, amounts, product details, and other relevant information based on the document type.

Data validation and error handling

• The extracted data undergoes validation checks to ensure accuracy. This might involve pre-defined rules, data cross-referencing, or even integrating with external databases for verification.
• The system can flag potential errors for human review or automatically suggest corrections based on established data patterns.

Integration and output

• The validated data can be seamlessly integrated with existing business systems, such as ERP or CRM software. This eliminates the need for manual data entry, and streamlines information flow across your organization.
• Users can access the extracted data through a user-friendly interface for further analysis, reporting, or triggering automated workflows.

Post-processing

After the AI extracts data from your documents, the mission is not quite accomplished yet. The extracted data might require some post-processing to ensure accuracy and usability. This may involve a human review to validate the extracted information, address inconsistencies, and train the AI model for improved future performance.

Additionally, the data might be formatted or normalized to ensure it seamlessly integrates with your existing systems and workflows.

This simplified breakdown illustrates how everything works in the AI document processing journey, freeing your employees from tedious tasks and empowering them to focus on more strategic initiatives.

Key components and technologies

• Machine learning trains models for the automated interaction with documents. These models are constantly learning to extract data accurately, recognize patterns, and optimize the automation of these processes. ML works with an enormous quantity of data. Also, it can help identify types of documents and adjust their processing for specific layouts.
• Deep learning, a branch of machine learning, also takes part in AI-powered document management. It can extract valuable data from the documents. However, its algorithms require a lot of time and resources for training. Besides, DL infringes privacy to show how it reached a particular outcome, so DL is seldom used.
  
• Computer vision operates visual data within documents, interpreting logos, signatures, watermarks, images, etc. Computer vision utilizes its algorithms to extract visual elements and classify documents. It also works with optimal mark recognition or optical character recognition to improve the definition of the meaning in the whole document.
• Natural language processing (NLP) empowers computers to interpret human language. NLP technologies can also teach machines to generate human language and process complicated language structures. They understand names or addresses from unstructured data.
• Robotic process automation (RPA) can also be used in intelligent document processing. RPA does high-volume, repetitive, and rule-based tasks with documents. Combining RPA with AI-based components gives new opportunities to design complicated solutions in document processing.

Now let's consider some functionalities you can expect from such a software:

• Automated data extraction: IDP systems can extract various data points from documents with high accuracy, including names, addresses, dates, invoice totals, product details, and more. This eliminates the need for manual data entry, saving time and minimizing errors.
• Document classification: IDP leverages machine learning document processing to automatically categorize documents based on their type (invoices, contracts, receipts, etc.). This streamlines document organization and simplifies the retrieval of specific information.
• Intelligent search: IDP systems enable you to search for specific data points across a vast collection of documents. Thus, you can quickly locate relevant information without manually sifting through each document.
• Enhanced data validation: IDP systems can highlight potential inconsistencies or errors in extracted data, allowing for easy review and correction. This ensures the accuracy and reliability of the processed information.
• Advanced analytics: Some IDP solutions offer built-in analytics capabilities that allow you to analyze the extracted data and gain valuable insights. You can identify trends, track spending patterns, and improve your decision-making.

Remember: the specific functionalities offered by a document processing automation solution will vary depending on the chosen platform and its capabilities.

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Use cases of AI document processing

Automating repetitive tasks is just the tip of the iceberg when it comes to AI-powered business document processing. This technology goes beyond streamlining workflows – it unlocks a world of possibilities for companies across diverse sectors. In this block, we will explore some interesting cases.

Banking, financial services, and insurance (BFSI)

Loan application processing, insurance claim reviews, and anti-money laundering (AML) checks could really use tasks automation.

• Data extraction from mortgage, credit card, or loan applications ;
• Automating insurance claims processing , delivering meaningful data to authorized persons;
• Capturing billing data from tax documents and invoices;
• Tracking receipts and loading extracted data to pipelines.

Use case: SimFin shared its way of adopting IDP solutions. The company started to use machine learning technologies in 2017 and revolutionized its approach. Now, it applies next-gen IDP solutions updated in August 2023. With their help, SimFin reduced the time spent sorting through documents. The quality of the data entered has also improved (source ).

Government

Managing massive volumes of citizen documents, from applications to vital records, requires significant time and resources. AI-powered document processing (IDP) can streamline these processes and enhance efficiency.

• Extracting information from legal documents;
• Capturing data from public records or census data;
• Verification and approvement of application documents;
• Issuing credentials and sending notifications through messages or emails.

Use case: Mass Vitals, a company from Massachusetts, stores and processes vital documents such as birth and death certificates or marriage and divorce ones. The company needed to decrease the time spent on document searching, convert papers into digital form, and secure them. With the help of AWS cloud and AI document processing, they reached their goals (source ).

IT and telecom

The onboarding process for new customers and managing network infrastructure documentation can be cumbersome and error-prone. AI for business documents offers solutions to automate these tasks and improve accuracy.

• Streamlining KYC processes and onboarding new customers;
• Automating network equipment documentation processes;
• Extracting data from agreements and supporting documents;
• Improving accuracy in billing processes.

Use case: AT&T, the world's fourth telecommunication company from the USA, was involved in AI from its beginning. Later the company developed its solutions, combining RPA and IDP for more intelligent automation. Now, their developments manage contracts by extracting data from agreements and uninterrupted customer support (source ).

Healthcare

For this sphere, IDP offers functionalities to automate data entry, ensure regulatory compliance, and maintain accurate and compliant EHR.

• Self-operating management of Electronic Healthcare Records (EHRs) ;
• Automated credential checking for medical staff;
• Maintaining medical documents in keeping with HIPAA or GDPR compliance;
• Extracting insights from clinical trials .

Use case: Epic Systems is a healthcare company based in the USA. In August 2023, Epic announced integration with Azure OpenAI and Ambridge Generative AI Tool for automating EHR. Epic’s goal is to shorten the time spent filling out health records. NLP technology lets the company automatically record medical conversations and convert them into text with further export to EHRs (source ).

Examples of document processing implementation

At Binariks, we understand the challenges businesses face in managing ever-growing document volumes, and we can help your business automate business document processing. Our team has a proven track record of helping companies across various industries streamline their workflows and unlock valuable data insights. In this block, we will show you some of our success stories.

Multi-channel document automation product

Our client started with fax-based document management in 2005 but switched to cloud computing in 2011, focusing on centralized document management, especially for healthcare and life sciences. It was tough to move from serving businesses to directly aiding consumers, so we created a standout feature: one-click document completion, which makes tasks easier.

With Binariks' help, we tackled challenges like HIPAA compliance and UI design and delivered a top-notch prototype. Our solution, with a user-friendly interface and streamlined document automation, made the transition to consumer-focused services smooth. These changes mark a significant step towards our client's vision and further expansion.

By partnering with Binariks, you gain access to our expertise, a commitment to innovation, and a key to overcoming your unique challenges. Contact us today to discuss your specific needs and embark on your journey toward a more efficient and data-driven future!

7 benefits of AI in document processing

1. Save time and costs. Intelligent document processing reduces processing time by decreasing manual work. AI technologies save costs, especially in the most productive seasons, when businesses need to hire temporary employees. Besides, AI can speed up daily processes.
2. Process extensive volumes of duties. Artificial intelligence in document processing may be applied to different responsibilities simultaneously. It reduces employees' workload in various departments and frees time for other tasks.
3. Increase accuracy and efficiency. By automating manual work, IDP can reduce human errors. Only if AI cannot solve the problem can it inform staff. Then, the employee helps solve the issue, spending time correcting a specific mistake.
4. Enhance flexibility of processes. Applying new changes to pipelines by using AI document management is much easier. You only have to reconfigure the algorithm, and all the processes will change. Moreover, AI easily integrates into any system or tech stack.
5. Make more intelligent decisions. IDP automates mundane tasks, analyzes extracted data, and gives essential insights. Because of that, business managers can make balanced decisions based on accurate statistics.
6. Improve customer satisfaction. Document processing with AI lets you gain customer loyalty. It decreases the average time response and errors in papers. Quick reaction assists in building trustful and strong relationships with customers.
7. Constant improvement. In the summer of 2023, a new disruptive milestone occurred in IDP. A later version of IDP had to make templates for every document to analyze it. Now it is templateless, which means you can process documents of any kind and type faster and cheaper.

Core challenges of implementing AI in document processing

Security risks

Converting papers into digital format may cause security concerns, especially BFSI documents, invoices, medical papers, etc. That is why implementing IDP in your business requires additional cybersecurity measures.

Therefore, Binariks can encrypt your data and ensure better security. We also provide access control to improve sensitive data processing.

Data inaccuracy

Correct data input causes accurate data management. Nevertheless, the process of verification often shows errors in the input data. They were caused by manual data input, lousy quality of scanned documents, or handwritten text.

Binariks uses various technologies, such as NLP, OCR, etc., to improve input data quality.

Integration issues

Implementing AI-powered document solutions into existing businesses may be challenging. Some legacy issues must be complied with, as every industry has its rules for managing data.

Binariks provides extensive technical support and constructs integrated systems with high-level compatibility.

Permanent maintenance

IDP requires continuous updating. If you make changes or optimize your usual workflow, you must apply new rules to your intelligent document processing solution. Moreover, AI document processing sometimes requires additional training if the change is significant.

Binariks assists in maintaining intelligent document processing solutions and offers support.

Constant scaling

The amount of data is continuously increasing during business. Thus, it requires the scalability of AI-powered document solutions. Moreover, these volumes of data need to be stored somewhere.

Binariks can implement cloud-based IDP solutions, which help store and manage all data.

Popular AI document processing tools

1. Amazon Web Services:

• Cloud architecture: Leverage scalable cloud infrastructure for on-demand processing power.
• Scalability: Easily adapt your processing solution to handle growing document volumes.
• Various functionalities (Lambda, Textract): Build a customized solution using pre-built services like Lambda for functions and Textract for data extraction.

2. ABBYY FlexiCapture:

• OCR (Optical Character Recognition): Convert scanned documents and images into editable text.
• Machine learning: Automate data extraction and enhance accuracy over time with machine learning algorithms.
• Multilingual support (200+ languages): Process documents in a vast array of languages, ideal for international businesses.
• Flexible deployment (cloud & on-premise): Choose between cloud-based deployment or installing the software within your own IT infrastructure.

3. Google Document AI:

• Machine learning: Automate document processing tasks with the power of machine learning.
• HITL (human-in-the-loop) technology: Ensure high data extraction accuracy through human oversight during model training.
• Cloud-based: Operate entirely on the cloud, eliminating the need for software installation on local machines.
• Integration with Google Cloud: Connect seamlessly with other Google Cloud services for efficient document capture and management.

4. Kofax TotalAgility:

• AI: Utilize AI technologies to automate document processing tasks and decision-making.
• Document processing: Handle various document types, including invoices, contracts, and applications.
• Workflow automation: Automate repetitive tasks within document processing workflows to streamline operations.
• Regulatory compliance (GDPR, HIPAA): Ensure adherence to data privacy regulations for enhanced document security.
• Mobile capture: Capture documents conveniently using mobile devices for on-the-go processing.

5. IBM Datacap:

• Data extraction: Extract specific information from documents, including unstructured data sources like emails or social media posts.
• Classification: Categorize documents based on type for improved organization and retrieval.
• Unstructured data handling: Process data that lacks a predefined format, expanding your document processing capabilities.
• Redaction: Remove sensitive information from documents automatically for data security purposes.

Summary

Artificial Intelligence has great potential to change the document world. It is continuously developing to improve document processing faster and better. IDP is used in various industries now. Small and midsize enterprises are gaining momentum in utilizing AI technologies. They simplify work and earn more. Large enterprises are actively in IDP to maintain billions of documents.

Consider implementing artificial intelligence in your business with the help of Binariks. We can assist any industry in adopting AI technologies, and our team can build convenient pipelines with IDP in a short amount of time. If you find the adoption process challenging, we can help you overcome it. Contact us today to discuss the fastest path to artificial intelligence!