cvparser.io

What It Is

cvparser.io is a “CV → JSON” resume parsing API built for ATS platforms, recruitment agencies, and HR-tech teams. It can convert PDF, DOCX, DOC, HTML, plain text, as well as images/scanned documents mentioned on the site, into standardized candidate objects. Typical returned fields include name, title, email, phone, location, LinkedIn, work experience, education, skills, certifications, languages, projects, and more, with validation via a Zod schema.

Core Capabilities

The product centers on a single synchronous endpoint: upload a file to /parse, or send existing text to /parse/text, with most CVs returned inline within 1–2 seconds. Its AI stack uses a multi-provider approach; the site lists Claude, GPT-4, and local spaCy NER, which can be switched while keeping the same response structure. Notable design choices include “missing fields are returned as null, not fabricated,” and confidence scores for each candidate and some fields. It also supports a sections parameter to extract only required sections such as work experience or skills, reducing prompt usage and cost; GraphQL allows more granular selection of list fields.

Pricing and Trial

Pricing is based on prepaid credits with no auto-renewal. New users get 5 free parses without a credit card. Starter costs $50 for 100 parses, Pro costs $225 for 500 parses and includes priority support, while Business costs $800 for 2,000 parses and is marked as having no credit expiry. File parsing usually consumes 1 credit only on a successful 2xx response. For more than 100k parses per month, users need to contact the company for an enterprise plan. The free allowance is small, so it is better suited to testing accuracy and integration flow.

Pros and Cons

The advantages are a simple API, broad format coverage, clear documentation for error codes and rate limits, plus sandbox/live keys and a public demo endpoint. On privacy, the site states GDPR compliance, EU/UK residency, files being cleared from disk after 60 seconds, and no use of uploaded data for training. Limitations include a claimed 99% accuracy without independent benchmarks; Chinese is not explicitly listed among supported languages, with the page only saying English, Spanish, French, German and more; and payment methods are not disclosed. It feels more like a developer API than a full front-end tool for recruiters to use manually.

Who It’s For and Access from China

cvparser.io is suitable for teams that already have an ATS, candidate database, or recruitment SaaS and need to structure resumes in bulk. It can also serve as the parsing layer for a self-built recruitment system. The site does not state how well it works from China, so users still need to test network connectivity, latency, overseas payment, and data export compliance in practice. If Chinese resume recognition, mainland deployment, or local compliance is a high priority, it is worth evaluating RChilli, Affinda, Textkernel, or a local OCR + LLM/NER solution in parallel.