DiscoverCloud Resume Parser vs OpenResumeParser
DiscoverCloud Resume Parser
rchilli.comOpenResumeParser
github.comSide by side
| Figure | DiscoverCloud Resume Parser | OpenResumeParser |
|---|---|---|
| Price from | $6.25/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| Linux | Yes | — |
| iOS | Yes | — |
| Android | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 9 | 1 |
| Spec score · Resume Parsing Software | 9.2 (#1) | 7.4 (#24) |
| Purpose | The resume parser API extracts, enriches, and structures candidate information from resumes for use in hiring workflows. | The project extracts structured data from resumes and matches skills against job descriptions. |
| Support | The pricing page advertises 24x7 customer support for free and Standard offerings and premium customer support for Enterprise. | The README directs users to open a GitHub issue for questions or bugs. |
Plans
DiscoverCloud Resume Parser
- Free creditsFree
- Basic$75 a month
- Standard Plan (Annually)$75 a year
- Standard Plan (Monthly)$75 a month
- Standard Plan (Quarterly)$75 a month
- Incubator Program$150, paid once
- Auto Complete add-on$500 a month
- Standard yearly plan$20,000 a year
- Enterprise PlanPriced on request
In their own words
DiscoverCloud Resume Parser
DiscoverCloud Resume Parser is an API for extracting, enriching, and structuring candidate details from resumes for hiring workflows. It returns structured JSON and supports more than 200 data fields, with automatic language identification across resumes in 40+ languages. Supported formats include DOC, DOCX, PDF, RTF, TXT, ODT, HTM, HTML, DOCM, DOTM, DOT, and DOTX. The parser can redact potentially biased information from 57+ resume or CV fields. Listed uses include application-form autofill, processing scanned resumes and email, bulk parsing, duplicate checks, and taxonomy-based indexing for Solr or Elasticsearch. RChilli lists integrations through Oracle Cloud Marketplace, SAP SuccessFactors, and Salesforce AppExchange, and says it handles implementation and customizations for HR-system integrations. The API can be hosted on a customer's server; enterprise customers can choose cloud or on-premise arrangements. RChilli says its SaaS parsing services do not store submitted data or personally identifiable information. A free plan includes 100 credits. Standard plans are listed at $75 per month billed monthly or quarterly, or $75 per year billed annually.
OpenResumeParser
OpenResumeParser is a free, MIT-licensed project that extracts structured information from resumes and compares skills with job descriptions. It reads PDF and TXT files and extracts names, email addresses, phone numbers, skills, experience, and education. Its matching output includes a score, matched skills, and missing skills. The project offers a command-line interface and a FastAPI REST API, with API access and batch processing listed. A curated database covers more than 120 technical skills and can be customized in extractor.py. Dockerfile and docker-compose files support deployment, while Pydantic models are used in a type-safe design described by the README. The listed platforms are API, self-hosted, and Windows. The MIT license permits personal and commercial use. Important limits include no scanned-PDF or OCR support, heuristic experience and education extraction, a curated rather than machine-learning skills database, and regular-expression date extraction.