Mindee: automate document processing with an AI-powered API

Summary

The Mindee home page is headed “Automate document processing with AI-powered API” and says the API turns document data into structured JSON, with zero model training required. It describes splitting multi-page uploads, sorting incoming documents by type, cropping several documents scanned on one page and chaining models in a single API call. Document types listed are invoices, receipts, passports, resumes, bank statements and driver’s licenses, and customers named include Spendesk, Lucca and Indy. The FAQ says files can be up to 100MB and 200 pages, plans are Starter, Pro, Business and Enterprise with 500 to 10,000 monthly credits, and extra credits start from $0.05.

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Automate document processing with AI-powered API

From simple photos to complex PDFs or handwritten files, our API turn your document data into structured JSON with high‑reliability. Zero model training required. Any alphabets, any languages supported.

Trusted by top-tier teams worldwide

Most advanced AI OCR features Getting your document processing to the next level

Our AI-driven OCR API provides high-precision data extraction for all document formats, enabling businesses to automate workflows with speed and total reliability.

Accelerate processing by automatically breaking multi-page uploads into separate documents. Our solution detects document boundaries to split batches into distinct records ready for extraction.

Automate your workflow by sorting incoming documents instantly. Mindee OCR API distinguishes between document types, routing each file to its specific category for streamlined data management.

Digitize multiple documents scanned on a single page with automated detection. Mindee OCR API isolates and crops each item into a standalone file, ensuring every record is processed individually.

Platform overview

Chaining

Chain your pre-processing & extraction models in a single API call

A single API call to manage, manipulate, detect, and isolate the elements to be processed, then extract each one according to your specific needs. At no additional cost.

Companies around the world use Mindee’s API

Spendesk

Lucca

Indy

Learn more

Maxime Rihouey

Lead ML Engineer @ Spendesk

Documents processed

Invoices

Receipts

Features most used

Extract

Learn more

Antoine Diekmann

Head of the Finance BU @ Lucca

Documents processed

Invoices

Receipts

Features most used

Extract

Learn more

Boris Chabilan

Lead Product Manager @ Indy

Documents processed

Receipts

Features most used

Extract

Auto-crop

All customer stories

continuous learning model

Train and custom your extraction model to deal with every edge-case

Master the complexity of non-standard documents with an architecture built for total adaptability. Our platform moves beyond static extraction by leveraging continuous learning to refine performance. By integrating RAG (Retrieval-Augmented Generation), you can upload documents to create a dynamic knowledge base of past corrections and specific business contexts. This ensures that even the most unique edge‑cases are handled with precision, turning rare exceptions into standard automated successes through a self-improving feedback loop.

one platform, total control

Advanced OCR features and more to give you full control about your extraction workflow

Our platform provides granular confidence scores and precise bounding boxes to ensure that every extraction is both verifiable and structurally accurate, and moving beyond simple "black-box" processing. Empower your compliance strategy with localized processing zones and a strict "don't store my data" retention policy. Integrated with seamless team collaboration tools, these features offer the architectural control required to turn complex document workflows into secure, high-precision automated assets tailored to your specific needs.

Types of documents most commonly processed by our clients

See all document types

Invoice OCR

Extract line items and totals from global invoices in any language or format

Receipt OCR

Extract itemized totals, taxes, and merchant details from receipts in any format

Passport OCR

Capture identity data, MRZ, and expiry dates from any international passport

Resume OCR

Parse skills, work history, and contact info from diverse resumes and CV styles

Bank statement OCR

Digitize transactions, balances, and account details from multi-page statements

Driver's License OCR

Extract license numbers, classes, and addresses from diverse regional formats

Get started with Mindee’s platform

Reliable infra for any stack. Deploy via SDKs, no-code tools, or manual API calls to fit your unique business needs.

Learn more about document processing

See all resources

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FAQ about Mindee's OCR API

How much technical knowledge experience do I need to create a model ?

Mindee is designed with a "developer-first" philosophy , offering an intuitive interface that replaces complex manual programming with visual training tools. No training is required before using a model , while expecting high-accuracy for any document types.

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This democratization of AI allows product teams to deploy custom classification skills in a fraction of the time it would take to build a traditional OCR pipeline from scratch on GitHub.

What are some real-world examples of automated document data extraction ?

When it comes to automated document data extraction, Here are the most impactful real-world examples of how automated data extraction is used to eliminate manual entry:

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In the accounts payable world, data extraction is the engine behind "touchless invoicing."When a vendor sends an invoice, the API doesn't just read the text; it extracts specific fields like the invoice number, tax ID, net amount, and total. Most importantly, it parses complex line-item tables, capturing every individual product, quantity, and unit price.

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This allows the system to process payments automatically while ensuring that credit notes and statements are recorded with 100% accuracy.

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It is a core component of two-way matching and reconciliation for supply chain management. By extracting the PO number from a purchase order and the SKU list from a corresponding delivery note, businesses can automatically verify that the items received match the items ordered. This automated extraction ensures that auditors have a clean, digital trail of exactly what was delivered versus what was requested, without a human ever having to cross-reference paper sheets.

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For customer onboarding , automated extraction turns a slow, manual verification process into an instant check. When a user uploads their ID or a utility bill, the API extracts the full name, date of birth, and document expiration date. It also pulls the address and account number from utility bills to provide instant proof of residence. This allows companies to verify a customer’s identity in seconds, significantly reducing drop-off rates during the sign-up flow.

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You can check more real-life examples of how companies leverage this technology by visiting customer stories .

Can I extract complex tables from scanned PDFs with Mindee ?

Yes,with Mindee,you can test this feature by signing up for free here and uploading a sample file. Line items and complex tables recognition will be fully supported from PDFs or any image formats.

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This is where generalist APIs often fail. Standard OCR might give you a "word soup."

For complex tables (multi-line rows, merged cells, or nested headers), you need a vision-aware pipeline .

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Pro tip : Generalist LLMs often hallucinate table structures. For "messy" financial documents, look for APIs that use specific vision models rather than just generic text-to-text models

How do I extract 10MB+ PDFs or long documents ?

With Mindee, you can handle up to 100MB size per file and up to 200 pages .

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Large files (e.g., 100-page mortgage) should never be processed in a "request-response" (synchronous) loop. We can talk about two API methods :

- Asynchronous processing (Polling) : You submit the file, receive a job_id, and the API processes it in the background.
- Webhooks : Once complete, the API "pings" your server with the structured JSON. This is the gold standard for any Automated data extraction API setup for every language (Python, Node JS, Java, etc.)

How do I guarantee valid JSON structured format ?

Getting JSON is step one; getting valid JSON is step two. Most modern APIs, like Mindee allows you to define a data schema. To ensure your database doesn't crash:

- Use Pydantic (Python) or Zod (TypeScript) to validate the API output.
- If the extraction doesn't meet the schema (e.g., a missing mandatory invoice_id), flag it for human review.

Is integration complex, or does it require training time ?

No. Unlike traditional "On-Premise" solutions that take months to deploy, Mindee’s API-first approach allows you to go live in minutes . The complexity of document processing usually depends on whether you choose to build an infrastructure or consume an intelligent service.

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Mindee simplifies the experience by two ways :

- Zero-training time : Mindee models are pre-trained on millions of data points. Whether it’s an invoice, a receipt, or an ID card, the API already "knows" what it’s looking at. You don't need a Data Science team; you just need an API key.
- Plug-and-play : Mindee is a plug-and-play REST API. With our dedicated SDKs (Python, Java, PHP, and more), a developer can integrate full document automation into your existing software with just a few lines of code.

Can I integrate Mindee API with a business tool (ERP, CRM, etc.)?

Mindee’s API is RESTful and returns data in JSON format . XML is not returned.

To connect Mindee to your business tool you can use Mindee’s REST + JSON API via an ERP/CRM connector , HTTP steps, or webhooks. Most ERP/CRM tools integrate either through HTTP actions/nodes (low-code) or an automation platform.

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If your ERP/CRM supports inbound webhooks, you can also use Mindee webhooks to receive results on your server endpoint (recommended for heavy production usage).

How does Mindee's API pricing work ?

Mindee’s pricing is structured to support businesses at every stage, from early testing to high-scale production. We offer four main subscription plans—Starter, Pro, Business, and Enterprise—each with a fixed monthly credit volume and access to different features.

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- Starter, Pro, and Business plans include a monthly credits allowance (ranging from 500 to 10,000 credits), with additional credits charged at a per-credit starting from $0.05.
- Enterprise plans are fully customizable and designed for organizations with specific volume, SLA, or integration needs.

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Advanced features such as RAG capabilities, automation tools, and premium support are included progressively across the plans.

This model allows you to choose the plan that best fits your current needs while retaining the flexibility to scale as your usage grows.

Is it cheaper to build or buy a document processing API ?

You can calculate your specific breakeven point, but in short :

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BUY if :

- You are processing standard documents (Invoices, IDs, Receipts, Tax forms)
- You need speed-to-market and high accuracy immediately
- Document processing is a utility/commodity for your business, not the product
- You want predictable monthly spending without managing GPU hardware

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BUILD if :

- Your documents are highly proprietary (e.g., secret blueprints, unique internal forms)
- You have strict data sovereignty requirements (Data cannot leave your private cloud)
- You want to own the Intellectual Property for a core business differentiator
- You process >30M pages/year , making the "API tax" higher than a 5-person engineering team

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