Best OCR software for AI-powered data extraction

Looking for the right OCR software? Read this in-depth buyer's guide to find the perfect one for your business.

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BUYERS GUIDE OCR Overview

Optical Character Recognition (OCR) software transforms images and scanned documents into machine-readable text. However, traditional OCR tools often struggle with accuracy, especially on varied layouts, low-quality scans, or complex documents like invoices and receipts. This leads to frustrating manual corrections, time-consuming template setups, and persistent data entry errors that hinder business efficiency.

Modern OCR software has evolved significantly, moving beyond simple pattern matching by incorporating AI and ML. These advanced systems don't just see text; they understand document context, structure, and variations, much like a human would. This allows today's best OCR solutions to handle diverse layouts without pre-built templates, achieve significantly higher accuracy on real-world documents, and integrate seamlessly into automated business workflows.

In this buyer’s guide, we compare the leading OCR tools and explore how they’re evolving to meet modern business needs.

Head-to-head comparison of top OCR software


OCR accuracy on open datasets	TBD	87.8	77.7	79.7	N.A.	N.A.	N.A.
Languages supported	40+	200	300	6	200+	276	150+
Pre-trained document extractors	invoices, receipts, POs, bills of lading, bank statements, passports, driver license	bank statements, W-2s, passports, utility bills, identity docs, payslips, driver license, expenses, invoices	bank checks, bank statements, business cards, contracts, credit cards, general documents, health insurance cards, ID docs, invoices, marriage certificates, mortgage docs, oay stubs, receipts, tax docs	invoices, receipts, and ID docs	invoices	tax invoices, profroma invoies, POs, credit notes, debit notes, delivery notes	bank statements, passports, ID cards, finance docs, salary slips
Zero-shot learning	Moderate	Moderate/High	High	Moderate	Low	Moderate	Low/Moderate
Confidence Scoring	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Workflow automation potential	Yes – offers a workflow builder.	No native UI workflow	Yes via Power Automate	Workflow automation is DIY using AWS services.	Yes – but it may require significant configuration	Yes – built-in	Yes – built-in
Table Extraction	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Train with custom dataset	Yes	Yes	Yes	Yes	Yes	Yes	Yes
data export integration options	Multiple ERP and database integrations	No major options apart from google cloud storage	No major options apart from azure offerings	No major options apart from aws offerings	No OOB capability to integrate with other integrations	Multiple ERP and database integrations	No OOB capability to integrate with other integrations
API support	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Asynchronous processing support	Yes	Yes	Yes	Yes	Yes	Yes	Yes
multi page file support	3000 pages without postprocessing limits	Depends on processor	200 pages	JPEG/PNG ⇒ 10mb, pdf,tiff= 500mb upto 3000 pages	optimal number is 100. more pages can cause errors	40 mb	10
File Types supported	PDF, JPEG, PNG, HEIC, TIFF, EXCEL, CSV, WORD, TXT, HTML	PDF, GIF, TIFF, JPEG, PNG, BMP, WebP, HTML	JPEG, PNG, BMP, HEIF, PDF, TIFF, HTML, Word, Excel, Powerpoint	JPEG, PNG, PDF, TIFF	DOC, SPREADSHEET, PPT, PDF, GIF, TIFF, JBIG2, JPEG, PNG, BMP, PCX, etc	PDF, PNG, JPEG, TIFF, XLSX, DOCX	JPEG, PNG, PDF, HEIF, HEIFSequence, HEIC, HEICSequence, AVIF, AVIFSequence, TIFF, WebP, RTF, WORD, EXCEL, ODT, ODS, etc
On Premise Support	Yes	No	Yes	No	Yes	No	Yes
Security and Compliance	ISO 27001, SOC2, GDPR, HIPAA	ISO 27001, ISO 27017, ISO 27018, SOC 2, SOC 3, and PCI DSS, HIPAA, FedRAMP	offers variety of compliances as mentioned here - https://learn.microsoft.com/en-us/azure/compliance/	HIPAA, SOC, ISO, and PCI	SOC2 Type 1	ISO 27001, SOC2, HIPAA	ISO 27001 & 9001, GDPR
Supported document import options	UI, Email, and various integrations such as google drive, sharepoint, onedrive etc	Google console UI, Google cloud storage, API	api/sdk	can upload documents stored in s3, local storage via api/sdk	UI interface, api/sdk	UI, Email and various integrations	api/sdk
Human in loop	Yes	Deprecated now	Yes	Yes	Yes	Yes	Yes
STP stats	Yes	No	No	No	No	No	No

1. Nanonets

Nanonets is an AI-powered document processing platform that automates data extraction from unstructured documents using advanced OCR and machine learning. The solution offers pre-trained models for common document types (invoices, receipts, IDs) while allowing users to create custom models through an intuitive interface requiring minimal technical expertise.

The platform integrates seamlessly with existing workflows through APIs and continues improving through feedback loops. Its cloud-based architecture ensures accessibility, scalability, and enterprise-grade security for organizations of all sizes.

Key Features

Supports a variety of pretrained models.
Instant learning and zero training models
Pre built workflows for end to end automation
Integration with more than 25 external integrations such as quickbooks, salesforce, google drive, netsuite, one drive

Pricing structure

Free Trial: New users receive $200 worth of free credits upon signup to test the platform.
Pay-as-You-Go: Users are charged per workflow block run, meaning you only pay when a block executes a task. There are no platform fees or fixed costs.
Credits Accelerate (Volume-Based Discounts): Businesses with high processing volumes can get discounted pricing based on usage. This includes access to premium AI blocks, analytics, and team-wide credit sharing.
Enterprise Solutions: Custom pricing is available for large organizations with unique requirements, including add-ons such as role-based access and private cloud/on-premise deployments.

PROS

Wide range of options to import documents from variety of sources such as e-mail, google drive, onedrive, dropbox etc.
Upto 20Custom approval flow where files can be assigned to different users on the basis of custom business rules. fields
Reporting and analytics dashboard which helps in analysing the data across files and provide insights.
Can support files with very large number of pages (around 3000) as long as custom post processing is not applied
The platform offers an intuitive, no-code interface that simplifies the creation and training of custom models.
Nanonets allows users to tailor data extraction workflows to specific business needs, enhancing flexibility and efficiency in document processing.
Can interlink different types of models and hence multiple models can be used in a single flow
On premise support is available

CONS

Limited choice of pricing plans for self serve customers
Limited language support for users interacting via UI
Annotation can be time consuming

2. Google Doc AI

Google Document AI is a cloud-based document processing service that leverages Google’s cutting-edge OCR and AI models. It provides specialized processors for invoices, receipts, contracts, and more, alongside a general form parser for flexible extraction. The solution supports over 200 languages and integrates seamlessly with the Google Cloud ecosystem. Continuous updates ensure it remains at the forefront of AI-driven document analysis.

Key Features

15 processors available. Out of these 2 are private and 13 are public. 6 are trainable models.
Supported Regions - EU and US
Support of custom processors which can be trained on sample data is also available

Pricing structure

Usage-Based Pricing:
- Basic OCR: Approximately $1.50 per 1,000 pages (around $0.0015 per page).
- Specialized processors (e.g., invoice parsing): Approximately $30 per 1,000 pages (around $0.03 per page).
Free Credits: New users receive free credits (typically around $300) to test the service.
Scaling: Prices can be lowered with committed use contracts or at very high volumes.

PROS

Seamless integration with other Google Cloud offerings such as BigQuery and Google Workspace
Support of batch processing for bulk processing of documents.
Can extract Intelligent Document Quality (IDQ) scores which helps in assessing which documents must be processed differently based on their quality, making the overall document processing pipeline more efficient

CONS

Processed files can’t be viewed on UI later. However, files uploaded in asynchronous manner can be saved as json in Google cloud storage bucket.
Limited document import options such as API, google cloud storage.
Requires setup on Google Cloud, needs API configuration
Does not support very large files such as 3000 pages files.
Output is primarily in JSON format. No OOB capability to download data in other formats and export it directly to some platform.

3. Azure AI Document Intelligence

Azure AI Document Intelligence (formerly Form Recognizer) provides advanced OCR combined with pre-built and custom model capabilities for form and document processing. It uses deep learning to extract text, key-value pairs, and layout details while integrating naturally with other Azure and Microsoft services. The platform supports both out-of-the-box models and custom training with minimal samples. Its secure, scalable cloud environment is ideal for a variety of document types.

Key Features

Can extract text, key-value pairs, tables and structures from documents
Ability to restrict access to certain networks and endpoints
Can add alerts on metrics such as total calls, total errors, latency
Provides Free tier and Standard tier pricing

Pricing structure

Free Tier: 500 pages per month free for initial testing.
Pay-As-You-Go Rates:
- Basic OCR (Read API): About $1.50 per 1,000 pages (~$0.0015/page).
- Prebuilt models (e.g., invoice processing): Approximately $10 per 1,000 pages (~$0.01/page).
- Custom models: Up to $50 per 1,000 pages, with volume discounts for high usage.
Commitment Options: Discounts are available for large-scale deployments through volume commitment plans.

PROS

Provides multiple pre trained models such as invoices, receipts, identity documents, banks statements, credit cards
Seamless integration with other azure offerings facilitating the development of comprehensive solutions within the Azure ecosystem

CONS

Limited integrations options available. Need to integrate via api/sdk
Requires developer expertise
Max document size can be 4mb for free tier
Does not provide capabilities such as approval flow, export to various integrations.

4. AWS Textract

AWS Textract is a cloud-based OCR service designed to automatically extract text, forms, and tables from documents without manual template configuration. It utilizes advanced machine learning to detect layout elements and structured data, offering both synchronous and asynchronous processing modes. Deeply integrated with the AWS ecosystem, Textract fits well into broader workflows with Lambda, S3, and other AWS services. It is well-suited for scalable, on-demand document processing with zero-shot extraction capabilities.

Key Features

Can Extracts raw text, tables and table cells, document data based, key-value pairs, signature, layout from document
Allows training of model
Synchronous processing capability only for single page files. Multipage documents are processed via asynchronous processing.
Supported in multiple regions where aws service is available

Pricing structure

Free Tier: Up to 1,000 pages of text detection and 100 pages for forms per month for the first three months.
Pay-As-You-Go:
- Basic text detection: Approximately $1.50 per 1,000 pages (~$0.0015/page).
- Form/table extraction: Roughly $15 per 1,000 pages (around $0.015/page), with tiered volume discounts after 1M pages.
- Specialized APIs (e.g., Analyze Expense) may have rates around $0.01 per page.
Scaling: Costs drop with higher usage and very large deployments can often negotiate further discounts.

PROS

No minimum fees or upfront commitments
Leveraging AWS's cloud infrastructure, Textract efficiently processes large volumes of documents, making it suitable for organizations with substantial document processing needs.

CONS

Can process only those documents which are stored in s3 or local. No integration with other storage options such as google drive.
Documents processed via synchronous methods are not stored for retrieval. For asynchronous operations, documents can be retrieved till 7 days.
Developer expertise is required since integration via API/SDK is required. Console is only for testing purpose.
Can be exported
No capability to export document to other platforms.

5. ABBYY FlexiCapture

ABBYY FlexiCapture is an enterprise-grade document capture platform known for its high OCR accuracy and advanced data extraction through configurable FlexiLayouts and machine learning. It processes complex, multi-page documents and supports extensive language recognition. The platform offers robust workflow automation, integrated verification tools, and custom post-processing options. It can be deployed on-premises or in the cloud to meet strict security and compliance requirements

Key Features

Regions supported - USA/Canada, Europe , Australia
Output can be stored in any of the following formats - .xml, .xls, .csv, .dbf, .txt
Mainly supports invoice, application forms, contracts, letters.
Supports approval flow for verifying files. Files are flagged on the basis of default flags

Pricing structure

License-Based Model: Typically sold as an annual or perpetual license with a set page volume per year.
On-Premise vs. Cloud: On-premise deployment involves a significant upfront license cost plus additional page pack purchases; cloud subscription options are available through partners.
Effective Cost: The per-page cost can range from approximately $0.02 to $0.05 at high volumes, with enterprise deals negotiated to reduce marginal costs further.

PROS

Supports basic approval flows
GUI interface. Developer expertise is not needed.
Support to add invoice master data such as list of vendors, business units to improve accuracy

CONS

Limited sets of models
Cannot specify custom fields
No capability to export document to other platforms.
Limited capability on GUI.

6. Rossum

Rossum is a cloud-native, AI-driven document processing platform that minimizes manual template configuration through adaptive learning. Its cognitive engine is optimized for extracting key data—especially from invoices—and continuously improves based on user corrections. Rossum offers an intuitive web-based validation interface and end-to-end workflow automation. It is designed to reduce manual data entry while rapidly deploying across financial processes.

Key Features

Support to add common fields across model.
Doc upload via email is supported

Pricing structure

Subscription-Based: Pricing is quote-driven and typically set on an annual basis.
Cost Factors: Prices scale with document or field count rather than per page, with mid-size deployments often in the $1,000–$1,500 per month range and custom enterprise plans available for larger volumes.

PROS

The platform automates the entire document processing workflow, from data capture and validation to post-processing and reporting, reducing manual intervention and increasing efficiency.
GUI interface makes it easier to use the product without any developer skillset

CONS

Does not support very large files.
Limited extensions in trail version
Costly. Does not support pay as you go model

7. Klippa DocHorizon

Klippa DocHorizon is a SaaS-based OCR and document processing solution that offers robust pre-trained models alongside an intuitive interface. It is designed to handle a variety of documents—including invoices, receipts, IDs, and contracts—with strong multi-language support and additional features like fraud detection and data masking. The service provides both an API for developers and a web portal for non-technical users. It is optimized for fast processing and seamless integration with existing systems.

Key Features

Provides variety of models such as bank statement, financial model, identity model, salary slip model etc.
Does not persist the processed data which can be viewed later.
Data can be uploaded via UI for testing purpose or via api

Pricing structure

Free Trial: Available upon request to test the service.
Subscription & Usage-Based Options: Estimated rates range from roughly $0.01–$0.05 per page, depending on document complexity and volume.
Enterprise Options: Custom quotes are provided for high-volume or on-premise deployments, often including volume discounts and tailored integration support.

PROS

Supports a large variety of image formats.
Pay as you go pricing plan is available

CONS

Limited integrations options available. Need to integrate via api/sdk
Max number of pages in a file can be 10.
User can’t define custom labels.
Output is available only in Json Format

Choosing the Best OCR Software: A Buyer's Guide

Selecting the right OCR solution involves looking beyond basic text conversion. This guide focuses on key factors for choosing modern OCR software designed for business automation.

What are some must-have OCR software features that you need to look for?

Today's best OCR software uses smart technology to automate document processing effectively. Forget basic text scanning; look for these core capabilities:

AI-powered extraction: The software must incorporate AI and ML elements, enabling it to learn, adapt, and understand context beyond simple character matching.
High and verifiable accuracy: Aim for solutions consistently achieving 95% or higher accuracy on diverse documents, with features allowing users to easily verify results and provide feedback for model improvement.
Automated data ingestion: The software should automatically collect documents from various sources without manual uploads. Look for support for email forwarding, API uploads, cloud storage connections (Google Drive, OneDrive, Dropbox, etc.), and SFTP.
Template-free processing: The ability to handle variations in document layouts and formats without requiring manual template setup for each vendor or style is crucial for efficiency and scalability.
Intelligent data extraction: Must accurately extract not just text blocks, but specific key-value pairs, line items (table extraction), and handwriting (if needed), preserving structure and context.
Pre-trained and custom models: Access to pre-trained models for common documents (invoices, receipts, IDs, POs) accelerates deployment, combined with the ability to easily train custom models for unique document types with minimal data (e.g., 10-50 samples).
Configurable workflow builder: Look for tools that let you visually map out your process. This includes setting up data validation rules (Is the total correct? Is the date format right?), post-processing (like formatting dates or looking up vendor details), and routing documents for approval when needed.
Robust integration options: The software must connect to where your data needs to go. Essential options include a comprehensive API, reliable webhooks for instant updates, and ideally, built-in connectors for popular business apps (think Accounting, ERP, CRM, Cloud Storage).
Flexible Deployment & Security: You need options that fit your IT policy and your company's requirements. Look for both a secure Cloud (SaaS) offering and the possibility of On-Premise deployment, backed by strong support by verifiable security standards.

How to choose the right OCR software?

Choosing the right OCR tool requires careful evaluation. You need a solution that effectively handles your specific documents and processes.

Here’s what to prioritize when you're evaluating your options:

Does it actually work on your documents?
Advertising 99% accuracy is easy, but request proof or see it for yourself. Use the free trial and upload samples of your real invoices, receipts, or forms. You could even go ahead and schedule demos to see how it handles the quality and layouts you deal with every day.
Can it handle your specific workflow?
Think about what you need after the data is extracted. Do you just need the text, or do you need a full process with validation checks, approvals, and automatic export? See if the software gives you the tools to build the exact workflow you need without making it overly complicated.
How well does it connect to your other tools?
Your OCR software needs to integrate with your other systems. Check if it easily connects with the software you already use, like your accounting system (QuickBooks, Xero?), ERP, or CRM. Look for ready-made connections and make sure the API or webhooks are well-documented and easy to work with if you need a custom setup.
How well can it process new document layouts?
Look for 'zero-shot' or instant learning capabilities. Some tools offer advanced AI features where it can identify and extract common fields (like dates, totals, names) from new document types immediately, even without specific prior training on that exact layout.
Can it keep up with your volume?
Consider how many documents you process now and how many you might have in the future. The software needs to be fast enough, especially for large batches or long documents. Make sure its performance and scalability match your needs, whether it's running in the cloud or on your own servers.
Is it easy to get started and maintain?
How much effort is involved in the initial setup? Will you need constant IT help? A major point here is templates. Solutions that learn and adapt using AI, without needing manual templates for every document variation, will significantly reduce ongoing maintenance effort.
Does it meet your security and deployment needs?
Where does your data live? Decide if you're comfortable with a cloud service or if you absolutely need an on-premise solution. Always check the vendor's security practices and certifications (SOC 2, GDPR compliance are good signs).
What kind of support can you expect?
When you have questions or run into issues, what help is available? Look into the support options, training resources, and whether you get access to dedicated help, especially if you're signing up for a business-level plan.

How OCR software automates document processing workflows?

Leading OCR platforms automate the entire lifecycle:

Import: Documents arrive automatically via Email, Cloud Drives (Google Drive, OneDrive, etc.), API, or direct upload.
Process: The AI classifies the document and extracts predefined or custom fields and tables – no templates needed. Data Actions automatically format information (like dates) or validate against databases.
Review & Approve: Extracted data is presented in an intuitive interface for quick verification. Custom Approval Rules automatically flag files needing review and route them to the correct team members.
Export: Clean, verified data is automatically sent to integrated systems (QuickBooks, Xero, ERPs, databases) or made available via API/Webhooks, completing the process without manual intervention.

FAQs

How is AI-powered OCR different from traditional OCR?

Traditional OCR often struggles with variations in layout, font, or quality, requiring templates and resulting in lower accuracy. AI-powered OCR, like Nanonets, uses machine learning to understand document context and structure, adapting automatically. This means higher accuracy, no template hassles, and reliable data extraction critical for automation.

What kind of accuracy can I realistically expect?

Leading AI-driven OCR solutions like Nanonets typically achieve over 95% data extraction accuracy on common documents. Importantly, they include tools for user verification and feedback, allowing the AI to learn from corrections and continuously improve its performance on your specific documents.

Do I need to build templates for different document layouts?

No, a major benefit of modern AI-OCR platforms like Nanonets is being template-free. The AI learns to identify fields based on context, meaning you don't need to manually create or update templates for every vendor invoice or form layout, saving significant time.

Can it extract data from tables and handwritten documents?

Yes. Advanced OCR accurately extracts structured data (line items), maintaining row/column relationships. Many AI platforms, including Nanonets, can also achieve high accuracy in reading handwritten text, although performance can vary based on legibility.

How does OCR software automate workflows like AP?

It handles the process end-to-end: 1) Auto-imports invoices (via email, API, etc.). 2) AI extracts key data (vendor, total, line items). 3) System validates data (e.g., checks math, matches POs). 4) Workflow routes for approval if needed. 5) Verified data exports directly to your accounting software (QuickBooks, Xero, etc.). This workflow minimizes manual steps significantly.

What file formats can modern OCR software process?

The best OCR software is versatile. Look for support for common formats like PDF (both native and scanned), JPG, PNG, TIFF, and sometimes others. Nanonets handles these standard formats effectively.

What languages does the OCR support?

High-quality OCR platforms support a wide range of languages. Nanonets, for example, works with most major global languages, including those using Latin, Cyrillic, and other scripts, allowing businesses to process international documents.

Is cloud-based OCR secure for sensitive data?

Reputable vendors use strong security measures. Seek platforms with certifications like SOC 2 Type II, GDPR, and HIPAA compliance, data encryption, and secure infrastructure. Nanonets prioritizes these standards.

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