Provider

Affinda

Affinda is best evaluated around OCR, document parsing and structured data extraction rather than as a generic AI tool.

summary

Affinda should first be assessed as a provider for OCR, document parsing and structured data extraction, with tests based on real PDFs, scans, receipts, invoices, IDs, resumes and business documents rather than generic demos.
The strongest use cases are usually linked to back-office automation, onboarding, finance operations, HR workflows and document-heavy products, especially when Affinda matches the expected input quality and output format.
Relevant capabilities to verify for Affinda include id passeport parser, resume parser, financial documents, because feature coverage can influence both implementation effort and production reliability.
Before using Affinda at scale, teams should benchmark field accuracy, document coverage, layout robustness, confidence scores and review effort on representative data instead of choosing a provider only from a feature checklist.
Provider alternatives remain useful when another option performs better on a specific language, media format, document type, latency target or budget constraint.

Affinda efficiently automates information extraction from various documents, including invoices, receipts, resumes, and IDs. The latest Affinda API (v3) adopts a more generalized approach, allowing the document endpoint to handle diverse document types, such as resumes, invoices, and custom documents. This enables seamless processing of different formats and layouts, streamlining workflows for recruitment, accounts payable, compliance, and more. The v3 API also offers enhanced customization, allowing users to define specific fields for extraction.

In 2024, Affinda launched the NextGen Resume Parser, a highly accurate machine learning model for extracting resume data. Key features include improved accuracy with a refreshed ML component, advanced NLP for better context understanding, multilingual support, customizable parsing fields, and seamless integration with HR systems.

They are using Affinda

We use Eden AI because it provides easy switching between different providers, fail-over system, aggregation and normalization of results. Simplified development (5x faster build, at no additional cost).

Jean-Emmanuel Losi

CEO, SuiteOp @SuiteOp

See the case study

When selecting a provider, we prioritized security, the availability of various interfaces, and user-friendly, comprehensive documentation. Eden AI met all these requirements and is also EU-hosted, making it our preferred choice.

Jonathan Ciza

Founder, Ciza Consulting @Ciza Consulting

See the case study