Top 10 Best Text Extraction Software of 2026

Amazon Textract is a fully managed AWS machine learning service that uses advanced OCR to extract printed text, handwriting, forms, tables, and layout elements from scanned documents, PDFs, and images. It excels at understanding document structure without requiring custom templates, enabling automation of data extraction from invoices, receipts, and forms. Supporting multiple languages and integrating seamlessly with other AWS services, it powers scalable document processing workflows for enterprises.

Google Cloud Vision API is a cloud-based machine learning service that excels in image analysis, particularly through its Optical Character Recognition (OCR) features for text extraction. It accurately detects and extracts printed text, handwriting, and dense document content from images, supporting over 100 languages and various formats like PDFs and photos. The API integrates seamlessly with other Google Cloud tools, making it suitable for automating workflows in document processing and data extraction.

ABBYY FineReader PDF is a leading OCR and PDF processing software specializing in high-accuracy text extraction from scanned documents, images, and PDFs. It uses advanced AI-driven technology to convert non-editable files into fully searchable and editable text while preserving complex layouts, tables, and formatting. Ideal for handling multilingual content across 198 languages, it supports batch processing for efficient workflows in document-heavy environments.

Adobe Acrobat Pro DC is a comprehensive PDF management suite that excels in text extraction from digital and scanned PDFs through its advanced OCR technology. It allows users to copy text directly, export to editable formats like Word, Excel, or plain text while preserving layout and structure, and batch process multiple documents. Ideal for handling complex, multi-language PDFs with tables and images, it combines extraction with editing capabilities for a full workflow solution.

Azure AI Document Intelligence is a cloud-based AI service from Microsoft that extracts text, tables, key-value pairs, and structured data from documents like PDFs, images, and forms using advanced OCR and machine learning. It offers prebuilt models for common document types and custom trainable models for specialized needs, preserving layout and reading order accurately. This makes it powerful for automating document-heavy workflows in enterprise environments.

Tesseract OCR is a free, open-source optical character recognition (OCR) engine originally developed by Hewlett-Packard and now maintained by Google, capable of extracting text from images, PDFs, and scanned documents. It excels at recognizing printed text in over 100 languages and scripts using advanced LSTM neural network technology for high accuracy on clean inputs. While primarily a command-line tool, it integrates well with programming languages like Python via wrappers such as pytesseract, making it popular for automated text extraction workflows.

PaddleOCR is a free, open-source multilingual OCR toolkit developed by PaddlePaddle, designed for accurate text detection and recognition in images, supporting over 80 languages and various text types like printed, handwritten, curved, and dense text. It offers pre-trained models such as the PP-OCR series for high-speed inference on CPU/GPU, along with tools for document analysis, table recognition, and key information extraction. The toolkit is highly customizable, with easy Python integration and deployment options for production use.

EasyOCR is a ready-to-use Optical Character Recognition (OCR) library for Python that extracts text from images using deep learning models for both detection and recognition. It supports over 80 languages out-of-the-box, including many non-Latin scripts, and handles various text orientations and scene text effectively. Installation is simple via pip, with support for CPU and GPU inference, making it accessible for developers without requiring model training.

docTR is an open-source OCR library developed by Mindee, specializing in document text recognition through a modular end-to-end pipeline that combines text detection and recognition using deep learning models. It excels at extracting text from complex layouts in scanned documents, receipts, invoices, and forms, supporting multiple languages and architectures like DBNet for detection and CRNN/MASTER for recognition. Users can leverage pre-trained models or fine-tune them for custom needs, making it ideal for integration into Python-based document processing workflows.

Nanonets OCR API is an AI-powered platform specializing in text extraction and data capture from documents like invoices, receipts, and forms using machine learning models. It allows users to train custom extraction models with minimal labeled data, achieving high accuracy on structured and semi-structured content. The API integrates seamlessly into workflows for automating data entry and processing at scale.