Online Resume Parser

Overview

Online Resume Parser is an API and web service for structuring resumes and job descriptions, then matching and ranking candidates. It is best suited to recruitment software teams and agencies that want to build those functions into an existing workflow. The broad file support and adjustable retention are useful, but French-only generated text and firm request limits make it a poor fit for some global or document-heavy pipelines.

Key features

Five APIs cover CV extraction, job-criteria extraction, skills matching, candidate matching and ranking. Resume extraction can return contact details, work experience, education, languages, skills, certifications and interests, giving ATS, job-board and sourcing products a broad set of candidate fields to work with. The matching and ranking APIs extend the suite beyond intake, though ranking is limited to 10 candidates against one job.

The API accepts PDFs, office documents, spreadsheets, presentations, text files and common image formats, including PDF, DOC, DOCX, ODT, PPT, PPTX, ODP, XLS, RTF, TXT, JPG/JPEG, PNG and BMP. HTTPS requests authenticated with an X-API-Key, optional webhook callbacks and batch processing give implementation teams several useful integration patterns. But encoded requests must stay under 6 MiB, and documents with more than 100,000 extracted characters return HTTP 422. Teams handling unusually large or dense files will need a fallback path.

Job Extract criteria, Match explanations and Rank rationales are generated in French regardless of the input language. That may be acceptable for teams whose users can work with French output, but it is a significant limitation for products expecting localized explanations in other languages.

Data handling

Resume parsing and extracted photos are stored in Paris, and AI processing stays in the EU through an in-house pipeline. API callers can set do_not_store_data to true when parsed data must not be retained; it defaults to false, so teams with stricter retention requirements need to set it deliberately. The privacy policy describes technical and organizational safeguards and says submitted resume and job content is not used for advertising. It also identifies AWS Lambda and Amazon Bedrock for resume parsing, and a provider-operated service with Amazon Bedrock for job parsing, matching, skills matching and ranking.

Pricing

The free plan provides 50 credits per month, all APIs and supported formats, and API key management, with no card required. It is a sensible way to evaluate the full API surface, but the monthly allowance is limited for sustained processing.

Starter costs €24 a month for 500 credits, or €48 per 1,000 credits. It includes all APIs, supported formats and API key management, making it the lower-commitment recurring option for modest workloads. Scale costs €89 a month for 2,000 credits, or €44.50 per 1,000 credits, and suits teams with higher regular volume; the lower unit cost comes with a larger monthly commitment.

One-time credit packs do not reset each month: 500 credits cost €29, paid once (€58 per 1,000 credits), 2,000 cost €99, paid once (€49.50 per 1,000), and 10,000 cost €449, paid once (€44.90 per 1,000). They suit irregular workloads that do not justify a monthly plan, while the smaller packs cost more per credit than the recurring tiers. Enterprise has custom monthly volume and integrations, plus dedicated support, for organizations needing a tailored arrangement.

Platforms

Online Resume Parser is offered on the web and through an API. This is a backend-oriented choice rather than a standalone recruitment desktop or mobile app; its value depends on integrating the APIs into a product or process.

Who it's for

The strongest fit is ATS and HR software platforms, job boards, sourcing tools, staffing and recruitment agencies, and RPO providers that need structured candidate data plus matching or ranking. It is less suitable where generated criteria and explanations must be in a language other than French, or where requests commonly exceed the size and character thresholds.

Pros and cons

Pros

• Broad extraction and workflow coverage: five APIs span resume and job extraction, skills matching, candidate matching and ranking.
• Wide document acceptance: support for office, text, spreadsheet, presentation and image formats can reduce conversion work at intake.
• Retention control: callers can opt out of data storage with a request parameter, and processing is described as EU-based.
• Low-risk evaluation: the free plan includes all APIs and supported formats with no card required.

Cons

• French-only generated text: criteria, match explanations and ranking rationales are not generated in the input language.
• Strict document ceilings: the 6 MiB encoded-request cap and 100,000-character rejection can interrupt processing of large files.
• Small ranking batch: the Rank API handles no more than 10 candidates per job.
• Retention needs attention: do_not_store_data defaults to false, so privacy-sensitive integrations must actively change the setting.

Alternatives

Resume Parsing Software is the broader category directory for comparing options. Doxis AI.dp is worth considering for teams that want a paid service with a free trial and support across mobile, web and API platforms. DiscoverCloud Resume Parser may suit buyers seeking self-hosted deployment, 40+ language parsing and 24x7 support. DocuShell Resume Parsing API is an alternative for those comparing a freemium API with a 500-credit monthly free tier and larger per-file and PDF limits.

RChilli Resume Parser is another option for teams prioritizing 40+ resume languages, OCR and 200+ resume fields. Rezmatch.ai may fit smaller screening workloads where a one-time credit pack and a stated requests-per-minute allowance are useful. Parseur offers a free tier centered on pages, users and email mailboxes, which may better suit document and email extraction needs. Eden AI is an API gateway alternative for buyers comfortable with provider-priced calls plus a platform fee rather than a free plan. OpenResumeParser is the alternative to consider when an MIT-licensed project and self-hosting are priorities.

Verdict

Choose Online Resume Parser if you are building recruitment software or running an agency workflow that needs broad resume extraction alongside matching and ranking, and can work within its request limits and French-generated text. Its API breadth and retention control are the strongest reasons to adopt it. Look elsewhere if localized explanations, larger ranking batches or larger document requests are essential to your workflow.