AI Document Processing

AI Document Processing

AI technology automates and enhances document handling, ensuring accuracy, speed, and efficiency. From data extraction to intelligent document categorization, we streamline your workflow, reduce manual errors, and save valuable time.

Business benefits

Gen AI in Intelligent Document Processing

Gen AI in Intelligent Document Processing (IDP). Explanation
Gen AI in Intelligent Document Processing (IDP). Benefits
Intelligent Document Processing (IDP) before Gen AI
Intelligent Document Processing (IDP). Use Cases

Gen AI: The Next Frontier in Intelligent Document Processing (IDP)

Generative AI (GenAI) has revolutionized intelligent document processing (IDP) by enhancing its capabilities, accuracy, and efficiency. Before the introduction of GenAI, IDP relied heavily on traditional techniques like optical character recognition (OCR), natural language processing (NLP), and machine learning (ML) algorithms.

The role of GenAI in Intelligent Document Processing (IDP)

Improved Data Extraction
GenAI algorithms can extract text and relevant information from unstructured documents with higher accuracy, even when dealing with complex layouts, fonts, and languages.

Enhanced Understanding and Interpretation
GenAI models can better understand the context and meaning of the extracted data, enabling more accurate interpretation and analysis of documents.

Automated Document Generation
GenAI can generate human-like text, enabling the automation of document creation tasks such as generating responses to requests for proposals (RFPs), populating forms, and summarizing documents.

Reduced Model Training Time
GenAI has dramatically reduced the time and effort required to train models for specific document types and domains.

How IDP Worked Before GenAI

Before the introduction of GenAI, IDP relied heavily on traditional techniques like OCR, NLP, and ML algorithms. Here’s how the process worked:

  • Document Ingestion: Documents were scanned or uploaded into the IDP system.
  • Pre-Processing: Documents underwent pre-processing steps like image enhancement and OCR to improve readability.
  • Data Extraction: Traditional OCR and NLP algorithms were used to extract text and relevant information from the documents. However, these techniques often struggled with complex layouts, fonts, and languages, leading to lower accuracy.
  • Validation and Verification: The extracted data was validated against predefined rules and verified manually, which was time-consuming and prone to errors.
  • Integration: The processed data was integrated into the organization’s workflows for further analysis and decision-making.

Gen AI-driven Intelligent Document Processing (IDP) can be used across industries

Several industries can significantly benefit from the integration of Generative AI (GenAI) in Intelligent Document Processing (IDP)

Legal Industry

IDP can automate tasks like contract review, clause identification, and legal research, saving substantial time and effort for law firms and legal departments.

Healthcare Industry

IDP extracts relevant data from these unstructured documents, improving efficiency and reducing costs. It can also assist in summarizing medical reports and generating clinical documentation.

Financial Services

With IDP data extraction from financial statements, invoices, and other financial documents, improving operational efficiency can be improved.

Insurance Industry

IDP automates the processing of insurance claims, policy documents, and underwriting files, extracting relevant information with high accuracy.

Manufacturing and Supply Chain

IDP processes various documents like purchase orders, invoices, shipping manifests, and inventory reports, enabling better supply chain visibility and optimization.

Gen AI Intelligent Document Processing (IDP).
Step by step

Document Ingestion

Documents in various formats (PDF, Word, images, etc.) are ingested into the system through scanning, uploading, or other means.


The ingested documents undergo pre-processing steps like image enhancement, layout detection, and optical character recognition (OCR) to improve readability and extract text data.

Data Extraction

GenAI models, powered by large language models (LLMs) and natural language processing (NLP), are used to accurately extract relevant information from the documents, such as entities, dates, amounts, and key phrases. This step leverages the models’ ability to understand context and meaning.

Document Understanding and Analysis

GenAI models can comprehend the context and meaning of the extracted data, enabling deeper analysis, summarization, and generation of insights from the documents.”

Document Generation

Leveraging the understanding gained from the previous steps, GenAI models can generate human-like text, such as summaries, reports, responses to requests for proposals (RFPs), or populated forms. This automation reduces manual effort and increases efficiency.

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Document Processing in Logistics

Generative AI Intelligent Document Processing (IDP) offers practical solutions such as automating the handling of shipping documents, customs forms, and invoices.

For example, IDP can swiftly process bills of lading, extracting crucial data like shipment details and destinations.

By automating these tasks, logistics companies can accelerate the movement of goods, ensure compliance with regulations, and reduce costly errors.

Document Processing in Retail

The integration of GenAI and IDP technologies streamlines order processing and returns management, improves inventory accuracy, and enhances customer service.

By automating the extraction of data from order forms, invoices, and receipts, these solutions help retailers handle orders and returns more efficiently, leading to quicker resolutions and higher customer satisfaction. Real-time data extraction from stock management documents provides accurate updates on inventory levels, demand trends, and supplier performance, preventing stock-outs and reducing carrying costs.

Furthermore, automating customer data extraction accelerates response times and improves the overall customer experience.

Document Processing in Healthcare

Generative AI IDP helps healthcare providers work smarter by automating tasks like managing medical records, insurance claims, and paperwork. It saves time and resources by quickly and accurately extracting data from different documents, reducing errors, and ensuring patient information security.

With this technology, staff can spend more time caring for patients instead of doing repetitive administrative work. Overall, Generative AI IDP makes healthcare operations more efficient and helps providers focus on what matters most: patient care.

Document Processing in Finance

Generative AI Intelligent Document Processing (IDP) can be a game-changer for the finance industry, which is often overloaded with tons of paperwork. With this technology, financial institutions can automate tasks like handling invoices and contracts, saving time and resources.

For instance, Generative AI IDP can swiftly process loan applications, extracting relevant data from various documents to speed up the approval process. This not only improves efficiency but also enhances customer satisfaction.

Additionally, Generative AI IDP accurately sorts through documents, reducing errors and ensuring data security. By streamlining document management processes, financial institutions can focus more on strategic initiatives and providing superior service to clients.

Finance & Insurance

Check ContextClue for Documents Processing


ContextClue for IDP

ContextClue for IDP – ContextClue is a comprehensive AI-driven solution crafted for modern document research, code migration, and proposal creation. With its robust API-first design and Intelligent Document Processing (IDP) capabilities, ContextClue simplifies complex topics, extracts vital information, and enhances productivity across various domains. From technical documentation to legal contracts and beyond, ContextClue empowers teams to unlock insights, streamline workflows, and drive innovation.

-> Visit ContextClue page

Key benefits

What you will gain with
Gen AI Intelligent Document Processing?

Increased Accuracy

IDP leverages technologies like machine learning, natural language processing, computer vision and – recently – Gen AI to accurately extract data from unstructured and semi-structured documents, reducing errors compared to manual processing.

Improved Efficiency

IDP can process large volumes of complex documents rapidly, improving efficiency compared to manual efforts. This enables faster turnaround times and streamlined workflows.

Cost Savings

By automating document processing tasks, IDP significantly reduces the need for manual labor, lowering operational costs. The per-document cost is considerably lower than manual processing.

Data-Driven Decision Making

IDP enables organizations to extract valuable insights and patterns from unstructured data, facilitating data-driven decision-making and gaining a competitive advantage.

Intelligent Document Processing - FAQ

What is Gen AI IDP?
How does Gen AI IDP work?
What types of documents can Gen AI IDP process?
How secure is using GenAI for processing sensitive documents?
What are some key use cases of GenAI in IDP?

What is Gen AI IDP?

Gen AI IDP (Intelligent Document Processing) refers to the use of advanced AI technologies to automate the extraction, processing, and analysis of data from various document types. It combines natural language processing (NLP), machine learning, and computer vision to streamline document handling tasks.

How does Gen AI IDP work?

Gen AI IDP works by scanning and digitizing documents, then using AI algorithms to recognize and extract key information. The extracted data is then processed and categorized according to predefined rules, enabling efficient data management and retrieval.

What types of documents can Gen AI IDP process?

  • Invoices
  • Purchase orders
  • Receipts
  • Contracts
  • Forms
  • Emails
  • Reports
  • Any other structured or unstructured documents

How secure is using GenAI for processing sensitive documents?

Leading GenAI IDP solutions employ robust security controls like encryption, access management, auditing to protect sensitive data. However, it’s crucial to assess risks and implement proper governance when using GenAI with confidential documents

What are some key use cases of GenAI in IDP?

  • Summarizing lengthy documents and contracts
  • Extracting data from invoices, forms, legal agreements etc.
  • Generating responses to requests for proposals (RFPs)
  • Automating document creation like reports, letters etc.
  • Answering questions based on document content

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