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GUIDES 6 min read

Document Processing Guides

100+ hands-on guides covering the full document processing stack — OCR engines, LLM-based extraction, table parsing, pipeline architecture, and industry-specific automation. Written for developers, technical evaluators, and architects who need implementation detail, not marketing overviews.

Each guide covers real-world trade-offs, includes benchmark data where available, and links to relevant vendor profiles for commercial alternatives.

Getting Started

Guide Who It's For
OCR vs LLMs for Document Processing Teams deciding between traditional OCR and LLM-based extraction
Open-Source OCR Engines Compared Developers choosing between Tesseract, PaddleOCR, Surya, and EasyOCR
OCR API Comparison Developers evaluating cloud OCR services (Azure, Google, AWS, ABBYY)
Tesseract OCR Guide Developers getting started with the most widely-used open-source OCR engine
OCR Accuracy: Measuring and Improving Quality Teams benchmarking and optimizing OCR output quality
Multi-Language OCR Teams processing documents in multiple languages and scripts
Document Digitization Organizations planning large-scale paper-to-digital conversion projects
Document Scanning Best Practices Teams preparing physical documents for digitization and OCR
OCR for Developers Developers integrating OCR into applications and pipelines
Document Conversion Tools Teams converting between document formats (PDF, Word, images, HTML)
Apache Tika Guide Java developers using Apache Tika for document content detection and extraction
Docling Guide Developers using IBM's open-source document parser for structured extraction
Unstructured.io Guide AI engineers using Unstructured for document ETL and RAG pipelines
Document Capture Solutions Teams evaluating document capture hardware and software solutions
Document Indexing Automation Teams automating document classification and metadata tagging
Intelligent Character Recognition Teams processing handwritten and cursive text with ICR technology
PDF to Markdown Tools Developers converting PDFs to clean markdown for RAG and LLM pipelines
Vision Language Models for OCR Teams evaluating VLM-based OCR models like GOT-OCR, Qwen2-VL, and olmOCR
Image Preprocessing for OCR Developers improving OCR accuracy with deskew, denoise, and binarization
Marker Guide Developers using Marker for high-accuracy PDF to markdown conversion
LlamaParse Guide Developers using LlamaParse for GenAI-native document parsing
Document Parsing Benchmarks Teams benchmarking and comparing document parsing tools
AWS Textract Guide Developers using Amazon Textract for cloud-based document extraction
Google Document AI Guide Developers using Google Cloud Document AI for document processing
Azure Document Intelligence Guide Developers using Microsoft Azure AI Document Intelligence
OCR Benchmarks Teams evaluating OCR accuracy across engines, languages, and document types
Document Layout Analysis Developers detecting document structure, regions, and reading order
OCR Post-Processing Teams improving OCR output with error correction and confidence scoring
Document AI Model Evaluation Teams benchmarking and comparing document processing model accuracy

Data Extraction

Guide Who It's For
Extracting Tables from PDFs Developers building table extraction pipelines
Python PDF Libraries Compared Python developers choosing a PDF parsing library
Document Processing with Python Python developers building end-to-end document pipelines
Handwriting Recognition Tools Teams processing handwritten forms, medical records, and historical documents
Receipt OCR Developers building receipt scanning and expense automation
ID Document OCR Developers building passport, driver's license, and ID card scanning
Bank Statement Processing Fintech teams automating financial document extraction
Form Recognition Developers automating structured form data capture and extraction
PDF Data Extraction Developers extracting structured data from PDF documents at scale
Email Document Extraction Teams automating extraction from email attachments and inboxes
AI Data Extraction Teams using AI/ML for intelligent data extraction from documents
Document Processing with Node.js Node.js developers building document extraction pipelines
Document Processing with Java Java developers building enterprise document extraction pipelines
PDF to Structured Data Developers extracting tables, forms, and key-value pairs from PDFs into JSON/CSV
Document Processing with C# .NET developers building document extraction pipelines
Document Processing with Go Go developers building high-performance document processing
PDF Accessibility Guide Teams making PDFs accessible and Section 508/WCAG compliant
Document Processing with Rust Rust developers building high-performance document processing
Document Processing with React Frontend developers building document upload, viewing, and extraction UIs
Document Processing with Angular Angular developers building document processing UIs and pipelines

Classification & Understanding

Guide Who It's For
Document Classification with ML ML engineers building automated document routing and classification
Document Processing for RAG Pipelines AI engineers building retrieval-augmented generation systems
Contract Analysis Legal teams automating contract review and clause extraction
Document AI with LLMs AI engineers using GPT-4, Claude, and Gemini for document understanding
AI Document Summarization Teams using AI to summarize and extract insights from long documents
Structured vs Unstructured Data Teams understanding document data types and processing approaches
Agentic Document Processing AI engineers building LLM agent workflows for document extraction
Fine-Tuning Document Models ML engineers fine-tuning LayoutLM, Donut, and custom VLMs for documents
Prompt Engineering for Document Extraction Developers designing reliable prompts for structured data extraction
LangChain for Document Processing Developers building LLM document pipelines with LangChain
OCR to LLM Migration Guide Teams migrating from legacy OCR to modern LLM-based extraction
Document Classification with Transformers ML engineers training BERT, LayoutLM, and Donut for document classification
Claude API for Document Processing Developers using Claude's vision API for document extraction
Document Processing Performance Tuning Teams optimizing latency, throughput, and cost of document pipelines

Industry Solutions

Guide Who It's For
Medical Document Processing Healthcare teams automating clinical records and HIPAA-compliant workflows
Invoice Processing Automation Finance teams automating AP workflows with IDP
Accounts Payable Automation Finance teams automating the full AP cycle from invoice receipt to payment
Insurance Claims Processing Insurance teams automating claims intake, extraction, and adjudication
Mortgage Document Automation Mortgage lenders automating loan document processing and compliance
Tax Document Processing Accounting teams automating W-2, 1099, and tax form extraction
Purchase Order Processing Procurement teams automating PO extraction and matching
Digital Mailroom Enterprise teams automating inbound mail classification and routing
Logistics Document Processing Supply chain teams automating BOL, customs, and freight documents
HR Document Processing HR teams automating employee records, onboarding, and compliance docs
Real Estate Document Processing Real estate teams automating title, closing, and property documents
Government Document Processing Government agencies automating citizen services and records management
Legal Document Automation Legal teams automating document assembly, review, and compliance
Supply Chain Document Automation Supply chain teams automating procurement, shipping, and trade docs
Construction Document Management Construction teams managing blueprints, permits, and project documents
Education Document Processing Educational institutions automating student records and admissions
Freight Document Processing Logistics teams automating BOL, customs, and shipping documents
Healthcare Claims Automation Healthcare organizations automating claims processing and adjudication

Compliance & Security

Guide Who It's For
Document Redaction Compliance teams automating PII removal from documents
KYC Document Verification Fintech and banking teams automating identity document verification
Document Verification Teams automating document authenticity and fraud detection
Document Processing Compliance Compliance teams ensuring regulatory document processing requirements

Implementation & Strategy

Guide Who It's For
IDP Vendor Evaluation Guide Procurement teams evaluating and selecting IDP software vendors
IDP Implementation Guide Project leads planning intelligent document processing deployments
Self-Hosted Document Processing Organizations needing on-premise document processing solutions
Batch Document Processing Teams processing thousands of documents at scale with OCR and AI
Document Workflow Automation Operations teams automating end-to-end document workflows
Automate Data Entry Teams eliminating manual data entry with AI-powered automation
Document Management Best Practices Organizations implementing document management systems and workflows
Document Data Validation Teams implementing extraction quality assurance and validation rules
Document Automation ROI Leaders building the business case for document processing automation
Document Archiving Solutions Organizations implementing long-term document storage and retrieval
Document Processing Pipeline Architecture Architects designing end-to-end document processing pipelines
Serverless Document Processing Teams deploying document processing on AWS Lambda, Azure Functions, and GCP
Document Processing Cost Optimization Teams reducing IDP costs through architecture, batching, and vendor strategies
Document Processing Monitoring Teams building observability for production document processing pipelines
Human-in-the-Loop Document Processing Teams designing review workflows for AI-assisted document extraction
Document Processing Testing Teams building test suites for document extraction pipelines
Document Processing Security Teams securing document processing workflows and data pipelines
On-Premise Document Processing Organizations deploying document processing on-premise for compliance and security
Real-Time Document Processing Teams building low-latency document processing for streaming and event-driven architectures
Document Enrichment & Entity Resolution Teams enriching extracted document data with entity linking and knowledge graphs
Building a Document Processing API Developers designing REST/GraphQL APIs for document extraction services
Streaming Document Processing with Kafka Teams building event-driven document processing with message queues

Looking for a production-grade solution? Browse the vendor directory or use the Vendor Finder to match your requirements. For head-to-head competitive analysis, see Vendor Evaluations.