OpenResumeParser vs RChilli Resume Parser
OpenResumeParser
github.comRChilli Resume Parser
rchilli.comSide by side
| Figure | OpenResumeParser | RChilli Resume Parser |
|---|---|---|
| Price from | Free | $75/mo |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | — |
| iOS | — | Yes |
| Android | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 9 |
| Spec score · Resume Parsing Software | 7.4 (#24) | 8.9 (#2) |
| Deployment | The project includes a Dockerfile and docker-compose setup. | Enterprise customers can use scalable cloud or on-premise pricing, dedicated cloud servers, and an API hosted on their own server. |
| Support | The README directs users to open a GitHub issue for questions or bugs. | The pricing page lists 24x7 customer support for the free and standard offerings and premium customer support for Enterprise. |
Plans
RChilli Resume Parser
- FreeFree
- Standard Annual$75 a month
- Standard Monthly$75 a month
- Standard Plan$75 a month
- Standard Quarterly$75 a month
- Incubator Program$150, paid once
- Incubator Program$150, paid once
- EnterprisePriced on request
- Enterprise PlanPriced on request
In their own words
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.
RChilli Resume Parser
RChilli Resume Parser has no write-up on Specifiction yet; its figures are above.