Mindee

Overview

Mindee offers a suite of API-first services designed for intelligent document processing and Optical Character Recognition (OCR). The platform allows businesses and developers to extract structured data from unstructured documents, such as invoices, receipts, passports, and driver's licenses. By leveraging deep learning models, Mindee aims to automate data entry, reduce manual processing errors, and accelerate workflows across various industries.

The core of Mindee's offering lies in its collection of pre-trained APIs, each specialized for a particular document type. For example, the Invoices API can identify and extract vendor names, amounts, dates, and line items from invoices, while the ID Cards API focuses on extracting personal information from identification documents. This specialization allows for high accuracy rates compared to general-purpose OCR solutions, which may require extensive post-processing to structure extracted text.

Beyond its pre-trained models, Mindee provides a Custom Document API, enabling users to train their own models for documents unique to their operations. This flexibility allows organizations to apply AI-powered data extraction to highly specific forms or templates that commercial off-the-shelf solutions might not cover. The platform targets developers and technical buyers looking to integrate document processing capabilities directly into their applications, enterprise resource planning (ERP) systems, or robotic process automation (RPA) workflows. Industries such as finance, retail, logistics, and healthcare can utilize Mindee to streamline operations ranging from expense management and customer onboarding to supply chain automation.

Mindee supports various programming languages through its SDKs, including Python, Node.js, .NET, Java, PHP, Go, and Ruby, facilitating integration into diverse tech stacks. Adherence to compliance standards like SOC 2 Type II, GDPR, and HIPAA is also maintained, addressing data security and privacy concerns critical for handling sensitive document information.

Key features

• Pre-trained Document APIs: Specialized APIs for common document types such as invoices, receipts, passports, ID cards, driving licenses, and financial documents, optimized for high accuracy in data extraction.
• Custom Document API: Tools to define custom document fields and train AI models to extract data from proprietary or unique document layouts. Developers can upload samples and label data to create tailored solutions.
• Multi-language SDKs: Client libraries available for Python, Node.js, .NET, Java, PHP, Go, and Ruby, simplifying API integration and accelerating development cycles.
• Data Security and Compliance: Adherence to industry standards including SOC 2 Type II, GDPR, and HIPAA, addressing requirements for handling sensitive personal and financial information.
• Developer Experience: Comprehensive documentation, consistent API responses, and robust error handling mechanisms designed to provide a straightforward integration experience.
• High Volume Processing: Infrastructure designed to handle large volumes of document processing, with pricing models that scale to enterprise needs and offer volume discounts.

Pricing

Mindee offers a free tier for initial development and testing, with paid plans structured around document volume. As of May 2026, the pricing details are:

Volume discounts become available for higher usage tiers, and custom enterprise pricing is provided for organizations with specific requirements or exceptionally high processing volumes. For the most current pricing information, refer to the official Mindee pricing page.

Common integrations

• Enterprise Resource Planning (ERP) Systems: Integrate with platforms like SAP, Oracle, or Microsoft Dynamics to automate invoice processing and expense reporting by feeding extracted data directly into financial modules.
• Robotic Process Automation (RPA) Platforms: Combine with RPA tools such as UiPath or Automation Anywhere to enhance automation workflows that involve document understanding, replacing manual data entry steps.
• Document Management Systems (DMS): Connect to systems like SharePoint or Google Drive to automatically categorize and index documents based on extracted metadata, improving searchability and organization.
• Customer Relationship Management (CRM) Systems: Use extracted ID information for faster customer onboarding and verification within CRM platforms like Salesforce.
• Financial Software: Integrate with accounting software (e.g., QuickBooks) to streamline expense reconciliation and bookkeeping by automating data entry from receipts and invoices.
• Cloud Storage Services: Direct integration with object storage services like Amazon S3 or Google Cloud Storage to process documents as they are uploaded, enabling real-time data extraction workflows.

Alternatives

• Google Cloud Vision AI: Offers a broad suite of image analysis capabilities, including OCR, handwriting recognition, and object detection, with specialized features for document understanding and form processing.
• Amazon Textract: A machine learning service that automatically extracts text and data from scanned documents, supporting structured data extraction from forms and tables without requiring manual configuration.
• Microsoft Azure Cognitive Services - Form Recognizer: An AI service that extracts text, key-value pairs, and table data from documents, supporting both pre-built and custom models for various document types.

Getting started

To begin using Mindee, you'll typically need to sign up for an account, obtain an API key, and select the specific document API you wish to use. The following Python example demonstrates how to extract data from an invoice using the Mindee Python SDK:

import os
from mindee import Client, product

# Ensure you have your API key set as an environment variable or replace 'YOUR_API_KEY'
mindee_client = Client(api_key=os.getenv("MINDEE_API_KEY", "YOUR_API_KEY"))

# Path to your invoice document
file_path = "./path/to/my/invoice.pdf"

# Call the Invoice API
input_doc = mindee_client.doc_from_path(file_path)
result = input_doc.parse(product.InvoiceV4)

# Print extracted data
print("---------- Invoice Data ----------")
print(f"Supplier Name: {result.document.inference.prediction.supplier_name.value}")
print(f"Invoice Number: {result.document.inference.prediction.invoice_number.value}")
print(f"Total Amount (incl. tax): {result.document.inference.prediction.total_amount.value}")
print(f"Date: {result.document.inference.prediction.date.value}")

# Iterate through line items
print("\nLine Items:")
if result.document.inference.prediction.line_items:
    for item in result.document.inference.prediction.line_items:
        print(f"  Description: {item.description}, Quantity: {item.quantity}, Total: {item.total_amount}")
else:
    print("  No line items found.")

print("----------------------------------")

This example initializes the Mindee client with an API key, loads an invoice document, and then calls the InvoiceV4 product to parse it. The extracted fields, such as supplier name, invoice number, total amount, and individual line items, are then printed to the console. For a complete guide, including error handling and other document types, refer to the Mindee Python SDK documentation.