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Critical capabilities for intelligent document processing

AUG 25 2024   -   8 MIN READ
May 23, 2025
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8 MIN READ

Running a small or mid-sized business (SMB) comes with its fair share of challenges, especially when it comes to managing an increasing volume of documents. For many SMBs, handling invoices, contracts, and employee records manually is time-consuming, prone to mistakes, and ultimately unsustainable as the business grows.

Intelligent Document Processing (IDP), using AWS services like Amazon Textract and Amazon Comprehend, offers SMBs an automated, scalable solution to extract, classify, and process document data. Using AI, machine learning, and natural language processing (NLP), IDP reduces manual workloads and enhances accuracy, allowing businesses to optimize operations and scale efficiently without significant IT investments. 

As automation adoption grows, the global IDP market is projected to expand at a 33.1% Compound Annual Growth Rate (CAGR) from 2025 to 2030, reflecting the increasing demand for solutions that improve efficiency and competitiveness. In this article, we'll highlight the key features that SMBs should look for in an IDP solution to ensure smooth operations, support growth, and improve overall efficiency.

What is an intelligent document processing solution?

IDP uses AI, machine learning, and NLP to automate the extraction, classification, and processing of unstructured data from a variety of document types like PDFs, scanned images, and contracts. 

Unlike traditional systems, which rely on predefined templates or rigid rules, IDP understands the content within documents in a human-like way, automating tasks that would otherwise require manual intervention. For SMBs, this means a drastic reduction in the time spent on administrative tasks, less reliance on specialized IT resources, and improved data accuracy.

Why is IDP essential for SMBs?

Importance of IDP

Manual document processing quickly becomes inefficient and unsustainable for SMBs as the businesses grow. Here's why IDP is essential.

  • Time and resource optimization: IDP eliminates the need for manual data entry and document categorization, enabling SMBs to allocate resources to more strategic tasks. This is especially important for businesses without dedicated IT teams.
  • Improved accuracy: By reducing human involvement, IDP minimizes errors, improves the reliability of processed data, and helps businesses make more informed decisions.

Why SMBs should automate document management using IDP software

IDP automation offers SMBs key benefits by reducing manual tasks that help businesses operate more efficiently and securely. 

  • Faster document processing: Automation accelerates document handling, allowing quicker access to crucial information, reducing turnaround times, and improving workflow speed.
  • Cost savings: By cutting out manual data entry, businesses can reduce overhead costs related to labor and human error. This translates into more money that can be reinvested into growth.
  • Better compliance and security: IDP solutions ensure that documents are processed securely and in compliance with regulations such as GDPR and HIPAA, reducing the risk of data breaches and improving the security of sensitive business information.

Automation through IDP leads to improved operational performance and smoother business processes, enabling businesses to scale effectively.

What can IDP solutions do for SMBs?

IDP solutions are important for SMBs looking to refine their document management processes. These solutions automate data extraction, classification, and processing from various documents, helping businesses reduce manual work, minimize errors, and improve decision-making.

1, Automated data extraction

IDP solutions automate the extraction of key information from unstructured documents like invoices, contracts, and purchase orders. This capability is powered by AWS Textract, which uses machine learning to extract text and data from scanned documents accurately. For SMBs, this means:

  • Minimizing manual data entry: Automated extraction with AWS Textract reduces errors and the time spent on manual data input.
  • Increased efficiency: Quicker access to important business data allows SMBs to act faster and stay competitive.

AWS Textract provides advanced text extraction and handwriting recognition, which is perfect for SMBs handling varied document types without requiring manual intervention.

2. Document classification and workflow automation

Based on predefined rules or machine learning models, IDP solutions can automatically classify documents, such as invoices, purchase orders, or contracts. Powered by Amazon Comprehend, which uses NLP to understand the meaning of text, document classification becomes more accurate. 

  • Faster processing: Documents are routed to the correct department or workflow without human intervention, accelerating processing times.
  • Better organization: Automated classification with Amazon Comprehend helps SMBs maintain an organized system for managing documents, reducing delays and bottlenecks.

Using Amazon Comprehend, SMBs can categorize documents based on context and intent, allowing faster and more accurate classification. Partners like Cloudtech utilize Amazon Comprehend to personalize document classification workflows for SMBs, ensuring seamless automation and faster processing without adding complexity. 

3. Full end-to-end automation with AWS step functions

IDP solutions allow businesses to automate the entire document lifecycle, from receipt to final processing and archiving. With AWS Step Functions, SMBs can orchestrate workflows and ensure automation is seamless across all document handling processes. For SMBs with limited IT resources, this means:

  • Eliminating manual steps: Reduces human error and operational delays, improving overall productivity.
  • Increased operational efficiency: AWS Step Functions enables SMBs to automate multi-step workflows, allowing them to focus on more strategic initiatives rather than handling routine tasks.

AWS Step Functions coordinates between various AWS services, ensuring a smooth flow of data and automation without requiring complex development work.

4. AI-powered decision making with AWS machine learning services

IDP solutions use AI to analyze extracted data and generate actionable insights. For SMBs:

  • Improved decision-making: Using Amazon SageMaker for machine learning, businesses can train custom models to analyze large volumes of data quickly, helping SMBs detect trends and inconsistencies to make more informed decisions.
  • Increased business agility: Smarter, AI-driven insights from AWS AI services allow SMBs to respond faster to market changes and customer needs.

Amazon SageMaker and Amazon Rekognition enable SMBs to use AI to analyze both structured and unstructured data to improve decision-making speed and accuracy.

5. Seamless integration with existing systems via AWS cloud services

IDP solutions integrate smoothly with existing platforms like ERP systems, CRM tools, and document management systems, often using AWS cloud solutions. 

  • Smooth data flow across operations: Integration with AWS Lambda and Amazon RDS reduces the need for siloed data, allowing departments to collaborate more effectively.
  • Real-time information access: With AWS Cloud Integration, businesses gain access to real-time, accurate data, enhancing overall workflow efficiency.

AWS Lambda offers a serverless compute platform that automatically scales and executes code, making integrating IDP with existing business systems easier without additional infrastructure.

6. Scalable solutions for growing SMBs with AWS cloud infrastructure

IDP solutions are designed to scale with a business’s growth, handling increasing document volumes without adding extra IT burden. 

  • Scalable document processing: Amazon EC2 instances scale up or down based on your document processing needs, allowing SMBs to grow without worrying about infrastructure limits.
  • Effective growth: Amazon S3 provides scalable storage for large document volumes, and IDP systems can expand without the need for expensive hardware or IT staff. This makes IDP an effective solution for SMBs focused on long-term growth.

AWS Elastic Beanstalk enables automatic scaling for cloud applications, ensuring that SMBs can handle rising workloads without manual intervention or extra IT overhead.

How an IDP solution works: A step-by-step workflow for SMBs

How does IDP work

The IDP workflow involves several steps, ensuring that documents are processed accurately and integrated seamlessly into business systems. 

1. Document capture

The first step in the IDP workflow is document capture. SMBs often deal with physical documents that need to be digitized, such as invoices, contracts, or receipts. In this phase, documents are scanned and converted into machine-readable formats. Advanced scanning technology and document management systems eliminate manual handling, speeding up processing times.

Once captured, the system automatically classifies documents by type (e.g., invoices, contracts) and directs them to the appropriate workflow. This eliminates the manual effort of sorting and tagging, allowing businesses to process documents more quickly and with fewer errors.

  • Cuts down on manual document sorting
  • Improves document accessibility and retrieval
  • Prepares documents for further automated processing

2. Pre-processing

Once documents are captured, they undergo pre-processing. This step uses techniques like noise reduction, binarization, and deskewing to improve document quality. Whether documents are scanned or uploaded digitally, pre-processing ensures they are aligned and legible, reducing any imperfections that may affect the extraction phase.

For SMBs, high-quality documents are essential for optimal data extraction, particularly if the documents are from varied sources and formats. By enhancing document clarity at this stage, businesses ensure that the IDP solution will perform at its best.

  • Ensures documents are clean and ready for accurate data extraction
  • Reduces errors and the need for manual corrections
  • Increases overall document processing accuracy

3. Classification

Once pre-processing is complete, the next step is classification. At this stage, IDP uses machine learning to identify the type of document (such as an invoice, contract, or purchase order). This automated classification process eliminates the need for human intervention, ensuring that documents are categorized correctly and routed to the appropriate workflow for further action.

This step is crucial for SMBs looking to streamline their operations, as it reduces the time and labor spent manually organizing and sorting documents, allowing for faster document processing and better organization.

  • Automates the sorting and categorizing of documents
  • Improves overall document workflow and routing
  • Saves time by eliminating manual sorting tasks

4. Data extraction

The next stage in the workflow is data extraction, where the important information about the actual business is pulled from the document. IDP solutions can extract printed and handwritten text using Optical Character Recognition (OCR) and Intelligent Character Recognition (ICR). At the same time, Natural Language Processing (NLP) further analyzes the context and meaning of the text.

For SMBs, this means data from various documents, such as invoices, contracts, and receipts, can be captured quickly and accurately, reducing the need for manual data entry. With the increasing complexity of documents SMBs handle, this capability is a game-changer for improving operational efficiency.

  • Automates data extraction from both printed and handwritten documents
  • Increases speed and accuracy of data capture
  • Eliminates the need for manual data entry, saving time and reducing errors

5. Data validation

After the data is extracted, validation is performed to ensure its correctness. The IDP system uses AI-powered algorithms to verify the accuracy of extracted data, cross-referencing it with predefined rules, external databases, or internal business systems. For example, invoice amounts can be checked against purchase orders, and customer details can be validated against CRM records.

For SMBs, data validation is important for ensuring that the information they rely on is trustworthy and ready for business use. By automating this process, SMBs eliminate the risk of human error and ensure that their data is accurate and actionable.

  • Verifies data accuracy, reducing the risk of errors
  • Automates the validation process, freeing up resources
  • Ensures that the data can be safely integrated into existing business systems

6. Boosting operational efficiency with IDP

Once all the steps, capture, pre-processing, classification, extraction, and validation, are completed, the final result is an efficient, automated document handling system. This end-to-end automation ensures that documents are processed with minimal human intervention, reducing bottlenecks and improving overall workflow speed.

For SMBs with limited IT resources, IDP represents an opportunity to modernize operations without the need for significant infrastructure or manual resources. This allows businesses to scale faster, adapt to growth, and invest in more value-generating activities, such as customer engagement or strategic planning.

  • Boosts operational efficiency and minimizes bottlenecks
  • Frees up employees for higher-value tasks
  • Provides a scalable solution that grows with the business

By automating these steps, businesses can ensure smoother document workflows, minimise errors, and boost operational efficiency.

Future of intelligent document processing

IDP is evolving with AI, Machine Learning (ML), and Robotic Process Automation (RPA) to make document processing faster, more accurate, and secure. These advancements help SMBs automate tasks, improve data accuracy, and streamline workflows. Here’s what SMBs need to know about the key trends shaping the future of IDP. 

1. AI and RPA integration

AI and RPA integration significantly improve IDP systems for SMBs:

  • End-to-end automation: AI understands document content, while RPA automates tasks like data entry and sorting, reducing manual work.
  • Fewer errors: Automation minimizes human errors, improving data accuracy.
  • Faster decision-making: AI speeds up data processing, allowing quicker, informed decisions.

As AI improves, IDP systems will handle more complex data, making them smarter and more efficient for SMBs.

2. Future trends in enhancing IDP with AI/ML and RPA

Key trends will make IDP solutions more powerful for SMBs:

  • Smarter data extraction: NLP advancements will enhance document comprehension, improving data accuracy.
  • Continuous learning: Machine learning will refine models, making IDP systems more efficient over time.
  • Handling unstructured data: Future IDP solutions will better process images and handwritten text, making document handling easier.
  • More intelligent automation: AI and RPA will automate increasingly complex tasks, requiring less manual oversight.

This will enable smarter automation with minimal manual oversight, helping SMBs improve efficiency and streamline their document processing.

3. Increased focus on security: safeguarding sensitive information

Security will remain a top priority for IDP solutions due to the sensitive nature of the documents processed. 

  • Encryption: AWS key management service (KMS) provides strong encryption for data at rest and in transit, ensuring sensitive information remains secure during processing.
  • DDoS (Distributed Denial of Service) protection: AWS Shield helps protect IDP solutions from DDoS attacks, ensuring that your document processing services remain available and uninterrupted.
  • Regulatory compliance: IDP solutions help SMBs maintain compliance with data protection standards like GDPR and HIPAA through built-in security features, such as secure data storage and access controls.

These improvements will ensure that businesses can process sensitive documents with confidence, reducing the risk of data breaches.

Also Read: Top 4 Intelligent Document Processing use cases for SMBs in 2025

Conclusion

Many SMBs struggle with the inefficiencies of manual document processing. It leads to increased errors, wasted time, and higher operational costs. Relying on traditional methods to handle documents like invoices and contracts can create significant bottlenecks, making it difficult for businesses to stay agile and competitive. An Intelligent Document Processing (IDP) solution can solve these problems by automating key tasks, improving data accuracy, and speeding up document workflows, allowing businesses to focus on growth rather than manual work.

Cloudtech's IDP solution helps SMBs overcome key document processing challenges by automating data extraction, classification, and validation using tools like Amazon Textract and Comprehend. This reduces manual effort, improves accuracy, and ensures compliance. With Cloudtech's expertise, SMBs can modernize workflows, cut costs, and boost efficiency. Talk to Cloudtech today to discover how their IDP solution can drive business success.

FAQs

  1. What is the implementation timeline for an IDP solution?

The implementation usually takes a few weeks to a couple of months, depending on the complexity and volume of documents. This includes integration and employee training.

  1. How do IDP solutions handle documents with handwriting or non-standard fonts?

IDP uses Intelligent Character Recognition (ICR) and Natural Language Processing (NLP) to process handwriting and non-standard fonts, improving over time with machine learning.

  1. Are IDP solutions scalable for growing businesses?

Yes, IDP solutions scale easily to handle increasing document volumes as businesses grow, without requiring manual intervention.

  1. How secure are IDP solutions?

IDP solutions utilize advanced encryption, with AWS Key Management Service (KMS) for secure data encryption and AWS Shield for protection against DDoS attacks, which are widely used by SMBs today.

  1. What ROI can SMBs expect from implementing an IDP solution?

IDP offers significant ROI by improving efficiency, reducing manual labor costs, and minimizing errors, with savings typically realized within the first year.

With AWS, we’ve reduced our root cause analysis time by 80%, allowing us to focus on building better features instead of being bogged down by system failures.
Ashtutosh Yadav
Ashtutosh Yadav
Sr. Data Architect

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