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API DEV-First
4.8/5 (30+ reviews)
Bank statement OCR API to extract financial data automatically
Extract structured financial data from bank statements using a production-ready Bank Statement OCR API. Convert PDFs and scans into reliable JSON you can trust for automation, analysis, and decision-making.
Test a bank statement
No credit required
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Les meilleures équipes du monde entier nous font confiance
Everything you need from a production-ready Bank Statement OCR
High-accuracy Bank Statement OCR
Extract text from PDF and scanned bank statements using an OCR engine built for real financial documents. Handles dense tables, multi-page statements, and varied bank formats.
Structured bank statement data extraction
Automatically extract transactions, dates, descriptions, amounts, balances, and statement metadata. Receive clean, consistent JSON ready for financial workflows.
Layout-aware bank statement processing
Handle complex layouts, repeating headers, and multi-page transaction tables without templates. Built to adapt when bank formats change.
Confidence scores for financial fields
Each extracted field includes a confidence score so you can automate safely, flag exceptions, and control financial data quality at scale.
Developer-first Bank Statement OCR API
Simple REST API, clear documentation, SDKs, no -code tools, and predictable pricing. Integrate Bank Statement OCR in minutes — deploy in production with confidence.
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Most advanced AI OCR features getting your document extraction 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.
More than just an API. Refine, test and customize.
Custom your model from scratch or start with a template among 30+ on Mindee interface
Build customizable extraction models with interactive data schemas.
Multi-language support
Parse your document in every languages.
Upload docs in any formats
Add .pdf, .jpg, .png, .docx, .xlsx, ... and more. No time spent to convert.
Integrate Mindee into your worklow in minutes
SDKs and low-code tools supported.
Your data is protected
EU hosting available
GDPR, CCPA Compliant
Exclusive features about Mindee for power‑users
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Add-ON
Confidence scores
Keep an eye on AI work with labels
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Polygons
Highlight your variables for better understanding, before & after extraction
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RAG
Build your own documents library to enrich your model and manage edgecases
FAQ to know more about Mindee
Puis-je combiner des API d'OCR et des LLM pour améliorer le traitement des documents ?
Absolument. De nombreuses entreprises utilisent des architectures hybrides : les API OCR gèrent la couche d'extraction structurée, fournissant des données propres au niveau du champ, tandis que les LLM ajoutent un raisonnement, un enrichissement ou une synthèse par la suite. Cette approche offre une rentabilité, une précision et des fonctionnalités d'IA avancées là où elle apporte le plus de valeur ajoutée.
Quelle est la différence entre l'API OCR et le LLM pour l'extraction de documents ?
Une API OCR est conçue pour extraire des champs de données structurés (tels que les numéros de facture, les dates, les montants) des documents commerciaux avec une grande précision et des résultats prévisibles.
Un modèle de langage large (LLM) tel que GPT-4 peut gérer des raisonnements plus complexes et du texte non structuré, mais peut halluciner les données et entraîner des coûts plus élevés pour les tâches d'extraction. Les API OCR sont généralement mieux adaptées aux documents structurés volumineux, tandis que les LLM sont utiles pour la synthèse, l'analyse de texte libre et le raisonnement.
Are there hidden costs in OCR API pricing models?
Yes, some models may include hidden costs, such as fees for exceeding API call limits, additional charges for advanced features, or costs for data security compliance. It's crucial to evaluate the total price and transparency of the pricing structure before committing.
