Intelligent Document Processing: Use Cases, Benefits, Implementation Guide
15 Jul 2025
17 Min
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Intelligent document processing (IDP) transforms the way you handle unstructured data by applying AI to read, extract, and analyze documents at scale. From invoices and contracts to insurance claims and onboarding forms, IDP helps your company automate workflows, reduce human error, and boost productivity across industries.
We have already put IDP into practice at Cleveroad, streamlining internal document workflows like Non-Disclosure Agreement (NDA) processing, State of Work (SoW) templating, employee leave requests, invoice validation, etc. We also delivered several IDP integration projects for our clients from Insurance and Healthcare domains, helping them streamline claims processing and reduce manual workload.
Based on our hands-on experience, we’ve compiled this detailed guide that walks you through 5 best IDP use cases for various industries, their strategic benefits, and a proven implementation process to get your business going with intelligent document processing.
Key takeaways:
- Intelligent Document Processing (IDP) combines OCR, NLP, and machine learning to extract, classify, and validate data from unstructured documents with minimal human input.
- When integrated with Robotic Process Automation (RPA), IDP enhances workflow automation by eliminating repetitive tasks and enabling end-to-end document lifecycle management.
- IDP is widely used across industries, from invoice processing in finance and EHR data extraction in healthcare to customs forms classification in logistics and claims automation in insurance.
- A successful IDP implementation requires clear business goals, data source preparation, PoC validation, and phased deployment with human-in-the-loop mechanisms for handling exceptions.
What Is Intelligent Document Processing?
Intelligent Document Processing (IDP) is a computer-automated, AI-driven technology that automatically captures, classifies, extracts, and processes data contained in structured, semi-structured, and unstructured documents. While legacy tools (e.g., rule-based data extraction systems, or traditional OCR) are limited to reading static text, IDP learns context, data variation, and improves accuracy over time through the use of Optical Character Recognition (OCR), Natural Language Processing (NLP) technology, Machine Learning (ML) algorithms, and rule-based automation.
IDP systems work through documents that are pulled from a variety of sources: scanned documents, hand-written papers, PDFs, email, or web forms, and through a variety of automated procedures:

How IDP-equipped software works
Modern IDP solutions can learn from corrections and user feedback, which means they get smarter with each document processed. This makes them ideal for large-scale document-heavy operations across different industries.
So, if your business aims to eliminate manual data entry, reduce errors, and accelerate decision-making, intelligent document processing serves as a foundational layer in end-to-end automation for your company, as proven by numerous intelligent document processing examples across finance, healthcare, and logistics.
Why invest in IDP
Adopting intelligent document processing is a strategic move for businesses aiming to reduce costs, increase data accuracy, and improve process agility. Let’s look at what current research and market insights say on the perspectives of IDP usage:
- According to Diginomica, more than 80% of enterprise data is unstructured. IDP plays a critical role in extracting value from this data for automation and analytics.
- McKinsey research states that companies using IDP report a 30–50% reduction in manual processing time for document-heavy workflows.
- The global IDP market is projected to reach $6.8 billion by 2027, growing at a CAGR of 37.5%, considering MarketsandMarkets data.
- A Docsumo statistics aggregator found that implementing IDP in business workflows results in ROI growth of 30%-200% in the first year of automation.
These stats highlight one clear direction: IDP isn't a trend, but an efficiency driver. Whether for finance, healthcare, insurance, or logistics, companies investing in intelligent document automation gain measurable benefits in speed, accuracy, and compliance.
Leading experts emphasize that IDP delivers tangible results with minimal disruption to existing workflows, as noted by Amy Jones:
Amy Jones
U.S. Public Sector AI Lead, EY
IDP offers a low-effort, high-reward opportunity to enhance existing systems. By incorporating AI-driven IDP, agencies can eliminate these bottlenecks, streamline operations and ensure more accurate, real-time information throughout the process.
IDP and RPA: why they should cooperate
Pairing Intelligent Document Processing (IDP) use cases with Robotic Process Automation (RPA) creates a powerful synergy that drives end-to-end automation of complex workflows. While IDP focuses on extracting, classifying, and understanding unstructured content from various formats (such as PDFs, scans, or handwritten forms), RPA automates the rule-based business processes.
Together, they allow enterprises to process documents at scale and with precision. For instance, in claims processing, IDP can extract relevant data from forms or supporting evidence, while RPA bots input the data into back-office systems, trigger decisions, or generate responses with zero human intervention for the tasks to be properly finished.
This combination is particularly impactful in financial services, where accuracy, speed, and compliance are critical. Whether it's invoice automation, account opening, or KYC validation, intelligent document automation use cases are significantly enhanced when integrated into automated RPA pipelines.
Another key strength of the combo is adaptability. A well-trained intelligent document processing solution can handle data variations and exceptions, while RPA handles routine workflows. As enterprises increasingly rely on generative AI development services for decision support, having IDP and RPA handle the data processing foundation ensures consistency, scalability, and auditability.
In short, Intelligent Documents Processing in conjunction with Robotic Process Automation is becoming an alternative way for businesses to significantly streamline document-based workflows. It turns document-driven tasks into seamless, touchless flows, reducing manual effort, improving throughput, and accelerating digital transformation initiatives.
Discover more use cases of RPA in banking sector while reading our guide!
Major Benefits of Using Intelligent Document Processing For Your Business
Implementing IDP allows companies to move beyond manual document management and unlock strategic value across operations. Here are the key benefits that address both the goals and pain points of modern businesses regarding the IDP topic:
Minimized human errors and improved data accuracy
By using AI to extract relevant information from both structured and unstructured data, IDP reduces reliance on manual input. This leads to higher accuracy and reliability, critical for decision-making and reducing the risk of non-compliance.
Unlike traditional OCR or rule-based extraction tools, IDP adapts to variations in document layouts and formats, enabling consistent performance even across different document types. With built-in validation steps and confidence scoring, IDP solutions also flag uncertain fields for human review, helping teams focus only on edge cases while maintaining overall process quality.
Reduced operational costs through automation
Intelligent document processing use cases can dramatically lower overhead by minimizing repetitive manual labor in activities like invoice management or HR onboarding. Organizations leverage IDP to optimize staff workload and boost operational efficiency across various departments.
Faster document turnaround and workflow acceleration
IDP streamlines the document process for the high-volume segment, reducing the amount of time spent pulling and routing information out of documents by a significant amount. For the banking, insurance, and logistics domains, all of which have the turnover directly impacting customer satisfaction as well as regulatory compliance, it certainly does make a significant difference.
Eliminating the bottlenecks, the Intelligent Document Processing reduces days-long waits to just a couple of minutes. Data-driven intelligent workflows powered by IDP work their way back and forth through systems and teams effectively, in loan approval, freight documentation and so on.
Seamless integration with existing systems
Modern IDP tools easily plug into ERP, CRM, and document management platforms, preserving your current workflows. You can use AI to enhance legacy systems without full-scale replacements, allowing faster ROI and smoother transitions.

Benefits of IDP integration for businesses
Key Intelligent Document Processing Use Cases Across Industries
Intelligent Document Processing (IDP) is gaining acceptance across industries where document-intensive workflows are a bottleneck. As a way to process several document types, IDP helps streamline operations, enhances accuracy, and cuts down manual effort. Below are the most relevant use cases of intelligent document processing per industry.
Healthcare
In healthcare, IDP addresses both operational and compliance needs by processing different document types securely and accurately, from intake forms to insurance claims and beyond. Here are core intelligent document automation use cases for Healthcare:
- Patient onboarding: Intelligent document processing can automate the extraction of insurance details, ID scans, consent forms, and health histories during digital registration, feeding the data directly into EHR systems to ensure seamless patient data synchronization across platforms.
- Claims processing: Intelligent document processing accelerates health insurance claim cycles by capturing billing codes, diagnosis info, and physician notes from scanned claim forms or PDFs.
- Clinical documentation: IDP helps pharma and research teams extract structured values from lab reports and handwritten medical notes, speeding up compliance and approval pipelines.
- Regulatory compliance: Intelligent document processing supports HIPAA-aligned data workflows by applying automated processing rules for storage, access control, and audit logs.
- Post-care engagement: IDP transforms patient feedback, discharge instructions, and follow-up forms into structured data for future treatment improvement and analytics.
Operating with these IDP use cases, healthcare providers can improve billing accuracy, shorten revenue cycles, and reduce regulatory exposure: all while delivering a better patient experience. And with IDP's adaptability to various document types, it scales effortlessly from individual clinics to large and complex hospital networks.
Explore our guide on EHR software development to find out how to create an ultimate system where IDP for healthcare benefits you the most
Financial services and banking
Banks and financial institutions are still deploying Intelligent Document Processing (IDP) to make the operations more accurate, reduce fraud, and address ever-evolving regulations. With large volumes of sensitive, structured, and semi-structured data, data integrity is ensured while facilitating speedier, compliant processes.
Let’s consider just a few of the intelligent document automation use cases that make core banking operations easier:
- Invoice processing: Retrieves accounting fields such as invoice numbers, subtotals, vendor details, and payment terms and directly uploads them into ERP systems, facilitating faster approval and reducing manual errors in accounts payable.
- Loan processing: Automates the borrower data from pay stubs, tax forms, and bank statements, speeding up loan approvals and credit scoring decisions.
- KYC Onboarding: Automates the verification of identities by capturing and validating data from passports, driver's licenses, and utility bills, while performing watchlist screening.
- Compliance and audit: Facilitates cognitive automation for matching transactions and validating data stored, establishing a traceable digital audit trail and reducing compliance overhead.
Financial institutions use the intelligent document processing as well to process contracts, standardize client onboarding, and extract investment portfolio metadata. As the IDP platforms evolve further, they allow multi-language document processing and real-time fraud detection triggers, becoming enablers of financial digital transformation.
Insurance
The insurance sector benefits significantly from IDP due to its dependency on document-heavy workflows, ranging from onboarding to claims processing. Insurers frequently deal with various documents, including scanned forms, handwritten notes, and third-party data that must be analyzed quickly and accurately. Let’s explore the most common intelligent document processing use cases in insurance domain:
- Policy application review: IDP automates the extraction of fields such as applicant names, coverage levels, and medical history from policy documents, cross-validating them with internal CRM or policy management systems.
- Claims assessment: The system parses handwritten, scanned, or digital claim forms, verifies content against policy data, and flags anomalies or incomplete fields for human review.
- Risk analysis: IDP enables insurers to automate the extraction of historical claims, payment trends, and behavioral patterns to assess fraud risk and pricing strategies.
- Customer communication: Incoming emails, feedback forms, and contact center transcripts are categorized and processed automatically, transforming document content into structured formats for faster routing and resolution.
These IDP use cases help insurers reduce manual intervention, cut processing times, and increase customer satisfaction, which directly improves operational efficiency and long-term retention.
Explore how to benefit from IDP in insurance: read our recent guide and learn more!
Logistics and supply chain
IDP empowers logistics and supply chain businesses to handle large volumes of transport documents, customs paperwork, and vendor invoices with speed and accuracy. With operations spread across regions and time zones, automating document workflows is key to timely deliveries and cost efficiency. Here are the most widespread intelligent document automation use cases you should consider:
- Bill of lading processing: Extracts container IDs, cargo weight, consignee and shipper details from scanned PDFs, speeding up cargo validation and reducing delays at ports.
- Customs clearance: Validates declarations, commercial invoices, and certificates of origin to ensure cross-border compliance and minimize human error.
- Vendor invoice processing: Automates ingestion and classification of invoices, matching them with POs and GRNs (Goods Receipt Notes), and routing them into ERP systems.
- Freight booking documents: Captures data from shipping manifests, delivery orders, and PODs (Proof of Delivery), ensuring visibility across the logistics chain.
By adopting an IDP platform, logistics firms improve SLA compliance, minimize shipment delays, and gain real-time insight into transport documentation status. This is crucial for modern, data-driven supply chain management.
Legal and professional services
Legal firms and service providers handle a constant invasion of case files, contracts, and client forms, which is ideal for IDP optimization. Here are the most widespread IDP use cases in legal industry:
- Contract review: IDP automates the extraction of clauses, dates, and obligations from legal contracts.
- Case file digitization: Converts scanned case notes, witness statements, and court filings into searchable formats.
- Client onboarding: Speeds up document intake and identity verification for new clients.
- Document classification: Organizes thousands of case-related documents by type, date, and relevance.
By integrating IDP into legal operations, firms can significantly reduce document handling time, improve accuracy in contract analysis, and streamline client onboarding: all while maintaining compliance and minimizing administrative overhead.
Industry | Key IDP use cases |
Healthcare & life sciences |
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Financial services & banking |
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Insurance |
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Logistics & supply chain |
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Legal & professional services |
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Analyzing all these examples across different industries, you can see that deploying IDP software enhances productivity, accuracy, and document governance. Across all the domains given above, intelligent document processing use cases empower teams to scale operations, handle compliance, and deliver services faster. Whether you're processing claims, invoices, or contracts, the right IDP solution transforms how fast your company engages with documents and delivers real ROI.
Intelligent Document Processing Success Stories in Global Companies
Many global companies have already embraced Intelligent Document Processing (IDP) to automate routine operations, reduce human error, and scale their document workflows. Below are real-world examples of how enterprises across industries apply IDP to drive measurable results in activities like speeding up claims handling in insurance or simplifying contract management in legal departments.
Coca-Cola
Coca-Cola’s bottling system utilized Ripcord’s robotic document automation and AI platform to process an estimated 25 million proof-of-delivery documents annually as part of its supply chain and accounts receivables. This IDP project allowed Coca-Cola to consolidate an array of vendors and eradicate manual data entry. As a consequence, they saved an estimated $1 million each year and increased data accuracy in document processing between 40–50%.
Pfizer
Pfizer completely transformed their R&D documentation processes when they adopted electronic intelligent document solutions (MSB Docs) for lab notebooks and regulated documentation. The new e-signing and electronic document process did away with paper-based approvals: previously involving manual shipment for signatures. The end-result was 85% cost reduction, about 90% faster document processing, drug development pipelines acceleration, and a total documentation efficiency improvement of 95%.
HBSC
Global banking giant HSBC implemented an AI-powered IDP solution from IBM (by means of optical character recognition and robotic process automation) to automate the validation of trade finance documents, like invoices and insurance certificates, in Global Trade and Receivables Finance. The system extracts 65+ data points from each set of trade transaction packs, speeding up processing of nearly 100 million document pages every year. As indicated by ComputerWeekly, automation quickened transaction speeds, making them safer for customers, and reduced errors while enabling staff to spend more hours on value-add work. Compliance risk was also reduced through higher consistency in checks for AML/KYC on trade documentation.
These high-profile intelligent document processing use cases all show how IDP can drive cost reduction, increased accuracy/compliance, and higher productivity, in establishing smart automation of documents. At Cleveroad, we apply similar principles in designing IDP solutions for clients, starting from business-specific PoC implementations and guiding our clients to large-scale integration with custom workflow, third-party solutions, as well as regulation needs. Our experts ensure AI models employed not only function accurately but make measurable business impact across industries.
How to Integrate IDP in Your Business Solution: Step-by-Step Guide
Whether you're working with tax forms, invoices, contracts, or medical records, IDP provides a scalable way to increase throughput while reducing manual overhead. Here is how intelligent document processing achieves the bottom-line benefits when you have a reliable tech partner to implement.
Step 1. IDP use case selection
Start IDP implementation by outlining your business case, document flows, and desired outcomes. In this stage, your tech partner’s solution architects and domain experts work closely with your internal team to map current challenges and define success metrics. The step includes:
- Analyzing your aims, needs and current problems you want to solve
- Selecting relevant IDP use cases (e.g., invoice triage, contract validation) that’ll help you receive the real value in your business context
- Pinpointing specific needs (e.g., compliance needs, personal data protection, etc.)
Step 2. Data analysis and preparation
At this stage, we analyze the document samples your system will process: their structure, formats, frequency, and noise level. We clean redundant data, normalize document layouts, and convert formats to ensure they’re compatible with the selected IDP system. This step helps increase model accuracy and prevents downstream errors during automation.
Step 3. PoC IDP solution stage
To test whether an IDP solution will bring you real value, we create a lightweight Proof of Concept (PoC) of an AI-powered intelligent document processing solution. This PoC validates whether the IDP model can perform data extraction (e.g., vendor names, payment amounts, or account numbers) from real-world document sets.
We typically use pre-trained AI and machine learning models (e.g., Amazon Titan, Claude via Amazon Bedrock, or Google Vertex AI PaLM), customize them for your domain, and evaluate their performance on live datasets. The goal is to prove the accuracy of field-level extraction, confidence scoring, and low latency showing tangible gains in faster processing and reduced error rates.
Validate your IDP solution with our business-driven AI PoC development services
Step 4. IDP solution development and deployment
Once the PoC succeeds, we move into building a production-ready solution. Our developers use modular IDP platforms, AWS technologies and AI services (e.g., Amazon Bedrock, Amazon Comprehend, Amazon S3, Amazon Textract) to deliver features like:
- Real-time OCR with NLP-based classification
- Auto-routing of document data to internal systems
- Human-in-the-loop workflows for exception handling
As an AWS Select Tier Partner, Cleveroad gains early access to AWS innovations, tools, and technical support, which helps us build scalable and compliant IDP solutions faster and more efficiently. For example, we’ve successfully applied intelligent document processing into our recent project.
One of our clients, Prime Path Medtech, a US medical device maker, needed a fully automated Quality Management System (QMS) to validate and track complex document workflows across departments. Through the strength of intelligent document processing, our experts designed a module-oriented QMS infrastructure that automates document flow, ensures traceability, and assists with FDA and ISO compliance. We’ve implemented the IDP capabilities to do that and help Prime Path Medtech reduce manual overhead and significantly improve quality control cycles.
This is how Client Liaison Officer from Prime Path Medtech™, Breanne Butler, sees the cooperation with Cleveroad:
Breanne Butler, Client Liaison Officer at Prime Path Medtech™
Step 5. Maintenance and enhancements of IDP solution
Once deployed, your IDP solution will continue to evolve. Maintenance covers model re-training, performance monitoring, and adapting to new types of data and document formats. As your business grows, so will your IDP ecosystem, while potentially expanding into new intelligent document processing examples like legal disclosures, insurance claims, or supply chain documents.
By choosing Cleveroad for IDP implementation, you get long-term support with model performance reviews, security patching, and the ability to scale the solution across departments or regions. Contact us to turn manual paperwork into structured insights that drive speed and efficiency.
Why Hire Cleveroad for IDP Implementation
Cleveroad is a skilled software development company headquartered in Estonia, Central Europe. We’ve been providing smart, business-driven software solutions for different industries (including Fintech, Healthcare, Logistics, Retail, eCommerce, and others) for over 13 years.
We help our clients automate document-based workflows by applying Intelligent Document Processing (IDP) technologies to enhance business efficiency, data precision, and customer satisfaction. If your business involves handling vast amounts of documents, we’ll help you identify and implement the most profitable IDP use case into your corporate ecosystem to streamline your business workflows and integrate.
By partnering with Cleveroad, you gain access to:
- Experts with an in-depth understanding of best document automation practices for B2B, B2C, and D2C business models, and tech capabilities to implement them using IDP
- Collaboration with an acknowledged IDP solution development vendor holding ISO/IEC 27001:2013 and ISO 9001:2015 certifications which ensures our adherence to world standards in data security management and quality assurance
- Seamless integrations with software like SAP ERP, Xero, Google Maps, and payment systems, so your document workflows stay integrated and consistent
- Access to advanced technologies like AI, NLP, OCR, and machine learning for auto-classification, data extraction, and routing of unstructured documents
- Full-cycle IDP development covering tailored IDP use cases identification, data preparation, PoC development and testing, and full-fledges solution development and fine-tuning
We'd like to present another of our accomplished IDP implementation cases: AI-driven Document Intelligence. Our client, who was a major Norway-based insurance company, approached us seeking a method to streamline their work process, as to claims processing. We designed and implemented an AI-based IDP system that classifies policy and claim documents automatically, accurately capturing the data to ensure compliance.
By deploying AI-driven document intelligence, our client reduced manual processing time by up to 75%, significantly increasing work efficiency and decreasing the likelihood of human errors.

AI-driven document intelligence system designed by Cleveroad
Integrate a resilient IDP solution into your business workflows
Cleveroad AI experts will help you build a robust IDP system to automate data extraction, integrate with internal workflows, and meet industry regulations
Intelligent Document Processing (IDP) is a data optimization technology that automates information extraction, categorization, and verification from unstructured documents using AI, NLP, and OCR. Organizations can automatically process document-based workloads, reducing manual work and minimizing the number of errors.
Intelligent document processing use cases include document classification, form extraction, insurance claims, bill payment, and onboarding workflows. It streamlines repetitive work such as routing, data entry, and validation in document-intensive processes.
Industries that can best benefit on Intelligent Document Processing (IDP) are:
- Financial services: Automate loan application, KYC, and compliance reporting processes in order to decrease turnaround time as well as human errors.
- Healthcare: Extract and aggregate data from patient charts, lab, and billing, streamlining clinical processes and administrative throughput.
- Insurance: Streamline claims processing, policy administration, and underwriting through the extraction of structured data from forms and reports.
- Logistics & supply chain: Digitalize and verify shipping papers, invoices, and customs forms for faster, smoother operations.
- Legal services: Classification and extraction of information from contracts, case files, and legal letters to speed up review procedures and reduce manual work.
Not necessarily: with cloud-based offerings and AI Proof of Concept services, companies can justify their IDP benefit at zero upfront cost. An incremental approach serves similarly to keep risks contained and scale investment proportional to real business value.

Evgeniy Altynpara is a CTO and member of the Forbes Councils’ community of tech professionals. He is an expert in software development and technological entrepreneurship and has 10+years of experience in digital transformation consulting in Healthcare, FinTech, Supply Chain and Logistics
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