Affinda

What is Affinda?

Affinda is an intelligent document processing platform that extracts, validates, and converts unstructured business documents into structured, decision-ready data for automated workflows. It belongs to the IDP category, combining document parsing, data validation, matching, and transformation to reduce manual review and support straight-through processing.

Affinda’s own platform handles documents such as invoices, financial statements, bank statements, forms, resumes, tables, and handwritten content. Users can also describe workflows in natural language, allowing the system to manage extraction, validation, and integration steps across document-heavy processes. Its parsing capabilities support multiple languages, although Affinda does not publish an exact language count.

The platform is used across banking and finance, insurance, logistics, healthcare, government, manufacturing, real estate, and recruitment technology. Typical applications include accounts payable automation, loan processing, claims handling, customer onboarding, compliance checks, and candidate screening. Affinda is available through Eden AI’s unified API, where exactly three parsers are exposed: Identity Parser, Financial Parser, and Resume Parser.

Affinda at a glance

Affinda main AI capabilities

Affinda combines document-specific parsing with broader intelligent document processing workflows.

• Identity document parsing: Extract structured data from identity documents through the ocr/identity_parser/affinda feature.
• Financial document parsing: Convert financial documents into structured data through the ocr/financial_parser/affinda feature, priced per page.
• Resume parsing: Extract candidate and employment information from resumes through the ocr/resume_parser/affinda feature.

When should you choose Affinda?

Choose Affinda if you are building a recruitment or HR technology workflow that needs to convert resumes into structured candidate data. Its Resume Parser can support applicant tracking, candidate screening, profile normalization, and downstream matching through Eden AI.

Choose Affinda for accounts payable or financial document automation when you need structured extraction from financial documents on a per-page basis. This can fit invoice processing, financial review, loan operations, and other workflows that depend on consistent financial fields.

Choose Affinda for KYC or identity onboarding when your application needs to extract structured information from identity documents. Its Identity Parser can support onboarding, verification, and compliance workflows that require document data before additional checks are performed.

A different provider may be a better fit if you need generic OCR across arbitrary layouts, support for custom document types outside identity, financial, and resume parsing, or EU or US data residency. Affinda is available in the AP region on Eden AI. You should also compare alternatives when you specifically need token-priced, LLM-based document extraction rather than file- or page-priced parsers.

Affinda pros and cons

Affinda models, features and capabilities on Eden AI

Relevant selected features for Affinda

Affinda is available through three Eden AI features, all within the OCR & Documents category: Identity Parser, Financial Parser, and Resume Parser. These features let you extract structured data from identity documents, financial documents, and resumes through Eden AI’s unified API.

Available Affinda models

Identity Parser and Resume Parser are priced per file, while Financial Parser is priced per page.

Supported Affinda capabilities

Supported AI categories

• OCR & Documents: Affinda is available only in this category on Eden AI.
• It does not provide chat, generation, embeddings, speech, or image-generation features through Eden AI.

Affinda API output: what data can be extracted?

Affinda’s parsers return structured fields that you can use in identity, financial, and recruitment workflows.

Eden AI normalizes provider responses into a standardized JSON schema, so you can swap providers without rewriting your parsing logic, while retaining access to the raw provider response. Check the Eden AI documentation for the exact schema and field names.

What can you build with Affinda?

Use case 1: Recruitment and candidate screening automation

You can build a recruitment workflow that receives resumes from job portals, email applications, or candidate upload forms and sends each file to Affinda’s Resume Parser through Eden AI. The parser converts the document into structured candidate information such as contact details, employment history, education, skills, certifications, and languages.

That structured output can feed an applicant tracking system, candidate database, or matching engine without requiring manual data entry. You can use it to standardize profiles, route candidates to relevant roles, or identify missing information before review. A recruiter should remain involved when fields are incomplete, experience is ambiguous, or automated screening could affect a hiring decision.

Use case 2: Accounts payable and financial document processing

You can build an accounts payable workflow that receives invoices and other supported financial documents from suppliers, shared inboxes, or upload portals. Affinda’s Financial Parser processes each page and returns structured information such as vendor details, invoice numbers, dates, line items, totals, taxes, currency, and payment information.

The extracted data can be sent to an ERP, accounting platform, approval workflow, or reconciliation system. Validation rules can flag duplicate invoices, inconsistent totals, missing purchase orders, or unexpected currencies before payment. Human review should be required for low-confidence fields, unusual layouts, handwritten corrections, or discrepancies between the document and existing supplier records.

Use case 3: KYC and identity verification onboarding

You can build an onboarding workflow that collects identity documents from customers, employees, or business representatives and processes them with Affinda’s Identity Parser through Eden AI. The parser extracts structured fields such as document type, full name, date of birth, document number, issuing country, nationality, and expiry date.

This output can populate a CRM, onboarding platform, or compliance system and reduce manual transcription. You can then pass the extracted information to separate verification, sanctions-screening, or identity-checking tools. Affinda’s parser extracts document data; it should not be treated as a complete identity-verification decision. A human reviewer should handle unreadable documents, mismatched details, expired documents, and higher-risk onboarding cases.

Affinda use cases by industry

Best Affinda alternatives and comparisons on Eden AI

Affinda vs Klippa

Affinda and Klippa both provide purpose-built document parsers rather than limiting their output to raw OCR text. On Eden AI, they overlap across resume, identity, and financial document processing, making Klippa a relevant provider to test against Affinda on the same files. Klippa’s broader platform also processes invoices, receipts, contracts, passports, identity cards, and driving licenses.

Choose Affinda when you need one of its three clearly defined parsers, predictable pricing, and structured output for HR, finance, or identity workflows. Choose Klippa when its document coverage better matches a broader or more specialized intake pipeline. Klippa’s Resume Parser was listed at $0.10 per file in Eden AI’s previous API documentation, but current pricing and regional availability should be confirmed in the model catalog.

Affinda vs Mindee

Affinda and Mindee both turn documents into structured data, but their available document coverage differs. Affinda exposes exactly three parsers through Eden AI: Identity Parser, Financial Parser, and Resume Parser. Mindee’s platform publicly documents parsers for invoices, receipts, passports, resumes, bank statements, and driving licenses, as well as tools for building custom document parsers.

Choose Affinda when its predefined parsers match your workflow and you want flat $0.070 file- or page-based pricing. Mindee may fit better when you need a wider selection of standard document types or custom extraction workflows. On Eden AI, Mindee’s Financial Parser is documented at $0.10 per page. Its pricing for other features and its processing regions should be checked in the current catalog before making a cost or residency decision.

Similar providers available on Eden AI

• Klippa: Structured extraction for resumes, identity documents, financial documents, and other recurring business-document workflows.
• Mindee: Document parsing for financial documents, identity records, resumes, and a broader range of predefined document types.
• Base64.ai: Document AI for structured extraction across identity documents, forms, financial files, and mixed business documents.
• Amazon: Generic OCR for extracting printed or handwritten text from documents, with pricing based on processed pages.
• Google: General text detection for PDFs and images when you need OCR output rather than a document-specific schema.
• Microsoft: General-purpose OCR for extracting text and bounding-box information from document files.
• Mistral: OCR for document text extraction through Eden AI’s standardized OCR feature.

Frequently asked questions about Affinda on Eden AI