The continuous debates on what is better for businesses, RPA solutions or IDP solutions, should come to an end. In the digitized world, manual document processing has become a thing from the past and businesses are more concerned about the choice of the automation technology to address their needs.

Why Do Businesses Need IDP and RPA?

Businesses all over the globe have been exploring ways to optimize and automate the workflow. Emerged in the early 2000s robotic automation solutions helped businesses to accelerate the docflow and improve operational efficiency. Despite the evolution of RPA technology, it still had limitations as it relied on pre-set templates and rules. The need for more versatile and flexible instruments resulted in the Intelligent Document Processing technology uprising.

How do RPA and IDP influence business processes?

  1. Accelerated workflow. Automation of time-taking repetitive operations saves time that can be dedicated to other, more strategic tasks that require human attention.
  2. High accuracy. In fact, both RPA and IDP technologies significantly improve accuracy of processing docflow by minimizing errors that happen due to the lack of concentration and tiredness in humans due to large volumes of repetitive tasks.
  3. Cost efficiency. Automated, fast and accurate workflow allows redistribute valuable human resources and focus on data-driven planning. Improved operational efficiency leads to enhanced performance and results in higher ROI.  
  4. Workflow optimization. Intelligent automation of workflow processes helps to eliminate unnecessary coordination between departments as the entire process of data processing is centralized.

What Is Robotic Process Automation (RPA)?

As the name implies, RPA represents a technology that deploys pre-trained bots for automation of time-consuming operations, such as:

  1. File transfers
  2. Data entry
  3. Screen scraping
  4. Massive email campaigns
  5. Automated responses
  6. Standard report generation, etc.

RPA document processing is rule-based. This means that bots need pre-set rules to follow. On average, RPA automations results in 85% improved productivity and 59% cost reduction.

Trained bots replace humans in the most tedious and repetitive tasks; however, RPA falls short when it comes to unstructured documentation. This is where IDP enters the stage.

What Is Intelligent Document Processing (IDP)?

The IDP technology has been designed to automate data capture, extraction, and classification from unstructured sources. Based on OCR technology and enhanced with AI, ML, and NLP algorithms, IDP can recognize unstructured and handwritten data, interpret it, and export for further processing.   

IDP document processing consists of three essential stages: document classification, data extraction, and information validation.

  1. The technology can read diverse document formats, including PDFs, emails, images, etc.
  2. IDP understands unstructured documents and transforms them to extract the required data. It recognizes handwriting and signatures.
  3. Self-learning capabilities of the IDP technology ensure continuously improved precision in processing new document types.

As a result, IDP’s higher accuracy level helps enterprises to extract data from a wider range of documents faster and more accurately and free up personnel to focus on decision-making instead of tedious routine.  

RPA vs. IDP: Key Differences

IDP and RPA share a common objective — automation of document processing and operational efficiency improvement. However, the functionality differs significantly:


Functionality RPA IDP
Accuracy 70-85% 98%+
Processing time 2-5 min/document 30 sec-1 min/document
Human intervention Regular, human-in-the-loop Occasional, for flagged documents that require reviewing
Document types Structured Structured, unstructured, semi-structured
Self-learning capabilities No Yes
Technology Rules-based automation AI, ML, OCR, NLP –based automation

Automation Using RPA and IDP Combo

A large chunk of data across various sectors is unstructured and cannot be processed by RPA. IDP comes to the rescue: in a RPA-IDP combo AI-driven IDP is considered as “the brain” and RPA is called “the hands”. By automating routine tasks RPA simplifies and accelerates daily workflow, while IDP takes automation to the entirely new level as it can recognize and classify doc types, understand data and categorize it.

Advantages of enhancing RPA with IDP:

  1. Unlimited integration capabilities. Innovative IDP solutions offer unlimited integration capabilities with various systems and third-party applications.
  2. Hyper-automation. IDP can be seamlessly integrated with available RPA.
  3. Advanced IDP platforms, like the Graip.AI’s solution, require minimal IT support.
  4. Enhanced KYC. End-to-end IDP automation connects all major workflow processes and coordinates with other systems. Seamless integration of IDP helps to develop a custom-tailored KYC process that prepares the data for further analysis.

RPA vs. IDP: What to Choose?

While both technologies are used for automation of the docflow, differences in their functionality should be determinative for making a final decision.

When considering automation technologies to implement, business owners should keep in mind:

  1. Business goals. Before deciding on an automation solution, companies need to analyze what operations and processes require automation, considering expansion prospects.
  2. Document types. Enterprises deal with diverse types of documentation, whether structured or unstructured. Doc types should be a determinative factor while choosing a technology.  
  3. Industry-specific needs. Some industries have strict policies and regulations; hence, compatibility and built-in security features should be taken into consideration.
  4. Growth prospects. Scalability of a chosen solution is crucial for future business growth.   

Graip.AI— Innovative IDP Platform

IDP automation with the cutting-edge Graip.AI platform can be a game changer for enterprises across diverse industries.

Why Graip.AI?

  1. Any documents (structured, semi-structured, and unstructured) in any format.
  2. AI-powered processing: data capture and classification, data validation and enrichment, data integration and verification.
  3. Advanced reporting and analysis
  4. Unlimited integration capabilities (CRM, ERP, CPQ, and other systems)
  5. API-friendly system
  6. Enhanced security
  7. Client success manager and 24/7 customer support

Stay ahead of competitors and open new business horizons with the self-learning Graip.AI platform — template-free and custom-tailored to your needs, the platform will help to understand 5x more data and provide insights for data-driven decision-making. 

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