A resume parser API lets you automate the process of examining CVs, like PDFs or Word documents, to gather data in structured order, like contact information, work experience, education, and skills.
OCR (Optical Character Recognition) technology is often used in resume parsing APIs to convert scanned or image-based resumes into machine-readable text. This allows the API to extract information from non-editable files by recognizing the text within them.
The OCR Resume Parser is designed to extract information from resumes across different fields and present it in a structured format like a database or spreadsheet. It captures essential details like the candidate's name, contact information, education, work experience, skills, and other pertinent information.
The extracted data is valuable for tasks such as resume screening, candidate tracking, and database management. By employing the OCR Resume Parser, industries such as IT, Healthcare, Banking, and more can streamline their recruitment processes, enhance efficiency, and achieve better results.
While comparing Resume Parser APIs, it is crucial to consider different aspects, among others, cost security and privacy. Resume Parser experts at Eden AI tested, compared, and used many Resume Parser APIs of the market. Here are some actors that perform well (in alphabetical order):
By leveraging advanced NLP to deliver exceptional results, Affinda surpasses other resume parsing APIs by extracting over 100 fields from each resume, allowing for comprehensive and detailed analysis. These fields are then efficiently organized into searchable file formats, providing users with a streamlined and convenient experience. Furthermore, Affinda sets itself apart by supporting an impressive range of languages, enabling the parsing of CVs in 56 different languages.
Ensuring unparalleled accuracy and versatility, DaXtra Parser excels in extracting rich information from CVs and resumes in multiple languages. The API supports various CV, vacancy styles and layouts, including social media profiles, ensuring comprehensive coverage. With its extensive language support, including multiple regions and dialects across Europe and Asia, Daxtra provides a comprehensive and precise resume parsing solutions.
HireAbility offers a robust and reliable Resume Parsing solution for organizations of all sizes. One notable advantage is that HireAbility does not store any of the resume or job data, ensuring data privacy and security for users. Moreover, HireAbility's world-class resume parser and job vacancy parser can seamlessly integrate into existing Oracle Fusion Cloud workflows, enabling a streamlined and efficient process. What makes HireAbility particularly unique is the ability to recognize and parse data from the Matters section, predominantly found in legal and lawyer resumes and CVs. Additionally, HireAbility continually enhances its resume parsing and job parsing online demos, introducing new features and updates for an improved user experience.
With advanced OCR, NLP, and GPT-3 AI technology, Hirize achieves an impressive parsing accuracy of 98%. The provider ensures that organizations can quickly and easily find top talent from resumes in various file formats, including jpg, word, and pdf. Moreover, the seamless API integration provided by Hirize allows for easy implementation with a simple POST call to their RESTFul API.
RChilli is known for its comprehensive solutions, offering parsing, matching, and enrichment capabilities to enhance every recruitment management system. With their resume parser and CV parser, fueled by AI and NLP technologies, RChilli empowers users to effortlessly extract relevant information from resumes of various formats, facilitating seamless analysis and streamlined processes.
Sovren's resume parsing API stands out with pinpoint accuracy and 100% uptime for the past two years. It ensures advanced security, never storing data and encrypting all transactions. With fast processing and 10X fewer errors, it delivers efficient and accurate results. Sovren promotes unbiased hiring by anonymizing resumes and offers extensive language support, insightful summaries, and flexible input options.
SuperParser is a versatile resume parsing API designed for enterprise use. It seamlessly integrates with various Applicant Tracking Systems (ATS), internal recruitment teams, HR technology platforms, and job boards, catering to organizations of all sizes, from startups to large enterprises. The SuperParser API excels at parsing resumes in multiple formats, including Microsoft Word (DOCX), PDF, Text (.txt), Rich Text (RTF), and OpenOffice. With lightning-fast processing, the SuperParser API can swiftly handle documents in a matter of seconds, ensuring efficient and results in no time.
Textkernel's resume parser is renowned for its exceptional accuracy and serves as a valuable tool for recruiting organizations worldwide. It enables these organizations to effectively handle large volumes of candidate documents. With support for over 24 languages and the ability to process documents in various formats such as PDF, DOCX, doc, HTML, ODT, and TXT, the API offers unparalleled flexibility. Textkernel's state-of-the-art AI empowers the parser to extract information from documents regardless of their structure, language, or writing style. The AI is built using native-language documents and speakers, eliminating the need for quality-degrading machine translations and ensuring accurate and reliable results.
For all companies who use Resume Parser in their software: cost and performance are real concerns. The Resume Parser market is quite dense and all those providers have their benefits and weaknesses.
Performances of Resume Parser vary according to the specificity of data used by each AI engine for their model training. This means that some Resume Parser may perform great for some languages but won’t necessarily for others.
When testing multiple OCR Resume APIs, you will find that providers' accuracy can be different according to text quality. In fact, the quality of a resume document, including its layout and formatting, can significantly impact the performance of a Resume Parser. Well-structured and organized resumes are more likely to be parsed accurately, while poorly formatted or disorganized resumes can pose challenges for the parser.
Resume Parsing APIs perform differently depending on the language of the text. Some providers are specialized in specific languages. Different specificities exist:
Companies and developers from a wide range of industries (Social Media, Retail, Health, Finances, Law, etc.) use Eden AI’s unique API to easily integrate OCR Resume tasks in their cloud-based applications, without having to build their own solutions.
Eden AI offers multiple AI APIs on its platform amongst several technologies: Text-to-Speech, Language Detection, Sentiment analysis API, Summarization, Question Answering, Data Anonymization, Speech recognition, and so forth.
We want our users to have access to multiple OCR Resume engines and manage them in one place so they can reach high performance, optimize cost and cover all their needs. There are many reasons for using multiple APIs :
Eden AI has been made for multiple AI APIs use. Eden AI is the future of AI usage in companies. Eden AI allows you to call multiple AI APIs.
You can see Eden AI documentation here.
The Eden AI team can help you with your Resume Parser integration project. This can be done by :