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Upload an ID card and watch as Affinda instantly predicts the data fields you want to extract, helping you automate ID card data extraction in just a few clicks.
Email, drag and drop or connect via API.
Affinda's AI reads your ID cards with impressive contextual understanding. It splits and classifies documents, extracts and validates data, then transforms the output to match your business needs.
No manual data entry required. Affinda integrates seamlessly into your existing tech stack.
Upload an ID card and watch as Affinda instantly predicts the data fields you want to extract, helping you automate ID card data extraction in just a few clicks.
Affinda automatically converts extracted ID card data into the format your KYC, compliance or HRIS systems recognize, ensuring it's ready for downstream processing. Need something custom? Use natural language to describe how you want the data to appear.
Write validation rules in natural language to apply your business logic to the extracted data. This ensures ID cards meet your verification standards and enables straight-through identity processing.
ID card processing is the workflow organizations use to capture, extract and verify identity data from ID cards and national identity documents. Our AI ID card data extraction software automates this entire process to reduce manual verification, errors and processing times. It ensures that identity information is accurate, compliant and securely integrated into KYC, HRIS and compliance systems.
ID card data extraction is the process of reading an ID card and capturing the critical identity details (such as name, ID number, date of birth, expiry, issuing authority and photo). Our platform uses advanced AI to automate ID card data extraction, turning physical and digital identity documents into structured data ready for your KYC, HRIS, compliance and government systems.
ID card extraction is the automatic capture of key identity data from ID cards using AI. Our ID card extraction software combines reading order models, OCR, LLMs, RAG and more to convert this information with high accuracy and faster processing times.
An ID card parser is a software tool that automatically reads and extracts identity data from ID cards. It converts ID cards into structured, machine-readable formats. Our AI ID card parser learns from every interaction, handling variations in format, layout and language with ease before transforming the output into exactly the format your systems need.
Line extraction captures data within tables on documents, turning it into structured formats whilst preserving the relationships between each row. Our platform interprets tabular data with strong contextual understanding, handling everything from simple grids to complex nested tables with accuracy and flexibility.
Affinda's AI ID card processing platform can extract data from any field on an ID card or national identity document. Standard data fields include:
Need custom fields or working with unique ID card formats? Simply define them in the UI or describe them in natural language and Affinda will extract and structure them automatically.
Our AI agents can process any file type. Supported file types include PDF, JPG/JPEG, PNG, TIFF, DOC/DOCX (Word), XLSX (Excel), HTML and TXT/CSV.
Affinda's AI agents read, extract and validate ID card data. Our platform is intuitive to set up and easily integrates into your systems. Simply:
The result? Faster, more accurate ID card processing with minimal manual input.
Yes. Our AI ID card processing platform combines OCR with retrieval augmented generation (RAG), LLMs, agentic workflows, proprietary reading order algorithms and more, to automatically detect and process data from scanned or photographed invoices (PDF, JPG, PNG). Even low-quality images are automatically enhanced for reliable data capture and processing.
Our AI ID card processing platform can automatically detect and process ID cards in 50+ languages, including multilingual ID cards containing more than one language. Supported languages include: Afrikaans, Albanian, Amharic, Arabic (Standard, Egyptian, Sudanese, Algerian, Moroccan, Levantine), Bahasa Indonesian, Bengali, Bhojpuri, Bulgarian, Burmese, Chinese (Mandarin [PRC/Taiwan], Cantonese, Wu, Min Nan, Jinyu, Xiang, Hakka), Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Greek, Gujarati, Hebrew, Hindi, Hungarian, Italian, Japanese, Javanese, Kannada, Korean, Latvian, Lingala, Lithuanian, Macedonian, Malayalam, Marathi, Nepali, Norwegian, Odia, Persian (Farsi), Polish, Portuguese, Punjabi (Western and Eastern), Romanian, Russian, Slovak, Slovenian, Somali, Spanish, Swahili, Tagalog, Tamil, Telugu, Thai, Turkish, Ukrainian, Urdu, Vietnamese, Yoruba.
Yes. Our ID card processing platform integrates seamlessly with KYC, HRIS, compliance and government systems. You can build no-code integrations using our AI integrations agent or connect via API – whatever suits your workflow best.
AI ID card processing helps automate and streamline identity verification workflows across functions such as:
An ID card optical character recognition (OCR) data extractor scans and accurately captures identity information from ID cards and national identity documents, regardless of format or language. Upload ID cards in PDF, JPG or PNG formats. The OCR technology first converts the documents into a text layer, ensuring all text (even from scans, photos or images) is captured. Affinda's AI models then identify and extract key fields such as name, ID number, date of birth, expiry, issuing authority and photo, transforming them into structured, usable data.
This automation eliminates manual data entry, reduces verification errors and saves time. Once the identity data is captured and structured, our AI ID card processing pipeline can apply machine validation and post-processing to enable seamless integration with KYC, HRIS, compliance and government systems.
Organizations across government, HR, financial services and compliance rely on Affinda's AI for their identity verification, employee onboarding and KYC/AML processes, streamlining workflows and improving overall accuracy.