Here is our selection of the best OCR Resume Parser, to help you choose and access the right engine according to your data.
Optical Character Recognition, also called OCR, is a technology that recognizes text within a digital image. The basic process of OCR involves examining the text of a document and translating the characters into code that can be used for data processing. OCR engines are made up of a combination of hardware and software that is used to convert physical documents into machine-readable text. Hardware to copy or read text while software typically handles the advanced processing.
Resume Parsing is the conversion of a free-form resume document into a structured set of information that can be stored, reported and manipulated by software. Resume Parsing helps recruiters efficiently manage electronically submitted resume documents.
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OCR traces its roots back to telegraphy. On the eve of the First World War, physicist Emanuel Goldberg invented a machine that could read characters and convert them into telegraph code. In the 1920s, he went a step further and created the first electronic document retrieval system.
Early versions of OCR had to be trained with images of each character and were limited to recognising one font at a time. In the 1970s, inventor Ray Kurzweil commercialised “omni-font OCR”, which could process text printed in almost any font.
OCR Technology became popular in the early 1990s while attempting to digitize historic newspapers. In the early 2000s, OCR became available online as a cloud-based service, accessible via desktop and mobile applications.
Today, there’s a host of OCR service providers offering technology (often accessible via APIs) capable of recognising most characters and fonts to a high level of accuracy.
Affinda provides artificial intelligence technologies for the automation of high volume document workflows. They help companies process unstructured data, removing the need for high-cost and error-prone manual processes. Affinda's approach is deliberately designed to overcome the typical issues associated with AI investment. Underpinning our approach is our proprietary technology in combination with the latest advancements in natural language processing, image recognition, and transfer learning. Affinda's technology is industry agnostic, and applies to any document type, including emails, contracts, invoices, forms, financial statements and more.
Daxtra Technologies is a world-leading specialist in high-accuracy, multilingual resume and job parsing, semantic search, matching and recruitment automation. Daxtra offers a competitive edge in finding the best available talent, while keeping the cost-per-hire to a minimum. Their products seamlessly integrate with our clients’ existing systems and processes, helping to find relevant information quickly and intuitively, across multiple internal and external databases.
Daxtra is an innovative technology that automatizes every step of the way, with Capture, Search, Parser amongst others. It automates different parts of the recruiting process – and seamlessly integrates with your existing recruitment or resume management software.
Docparser is a cloud-based OCR service that can extract data from resumes and CVs. With Docparser, you can extract data from resumes and CVs such as name, address, phone number, email, skills, education, and work experience, and then export it to various formats such as CSV, Excel, Google Sheets, and more. This can be useful in many cases such as recruitment, HR, and other use cases where resumes and CVs are important, as it allows you to easily extract data and process it in a format that suits your needs.
HireAbility uses a software called ALEX to process all your data. HireAbility’s parsing software supports any resume, CV and job posting layouts, including social media profiles. ALEX can parse resumes in over 40 languages and dialects, including multiple languages and multiple locations in one resume or CV. ALEX (Automated Linguistic EXpert), HireAbility’s CV / Resume parser and Job Order parser, employs several AI strategies including natural language processing techniques and pattern recognition in order to parse relevant information from resumes written in a free-text format.
hireEZ (previously Hiretual) is an AI-powered outbound recruitment platform to help you break free from outdated recruiting systems and help jobs find people. With hireEZ, you can execute a strategically scalable approach to build your workforce of the future. hireEZ's Resume Parsing API autofills application forms with information from uploaded resumes to substantially simplify the application process for candidates. You can also use that structured data to apply analytics and extract insights about your talent pool.
HrFlow.ai is an AI powered API that brings intelligence to your HR Data and gives you the freedom as a developer or an HR architect to build an infinite number of scenarios that meet your business logic.It comes with a complete and a fully integrated suite of HR data processing products -- such as Parsing API, Revealing API, Embedding API, Scoring API and Reasoning API. You just have to connect your existing tools and start automating workflows.
RChilli is known for providing parsing, matching, and enrichment to every recruitment management system. They offer resume parser / CV parser powered by AI and NLP, enabling users to extract the relevant information from resumes of different formats and easy analysis.
Sovren is a privately held software-components-only firm established in 1996. Sovren develops and licenses Resume / CV Parsing and Semantic Matching / Artificial Intelligence Matching (AIM) components. The Sovren Resume Parser is used within human resource software, and on recruitment websites and portals, to simplify and accelerate the application process, to extract and classify thousands of attributes about the candidate, and to provide a foundation for the semantic searching of candidate data. The Parser identifies hundreds of different kinds of information within a resume or CV, and clearly tags each data point (for example: first name, last name, street address, city, educational degrees, employers, skill, etc.). The output may be used in HR-XML or JSON format.
SuperParser is an enterprise grade resume parsing API deployed in a number of Applicant Tracking Systems (ATS), internal recruitment teams, HR technology platforms and job boards – ranging from tiny start-ups all the way through to large enterprises. SuperParser API can parse resume of all formats: Microsoft Word (all versions including DOCX), PDF, Text (.txt), Rich Text (RTF), OpenOffice 2. SuperParser API will process documents in a matter of seconds.
Textkernel’s highly accurate resume parser supports recruiting organizations around the world to effectively and efficiently process large volumes of candidate documents. Textkernel offers parsing in 24 languages and can process documents in any format, such as PDF, DOCX, doc, HTML, ODT, TXT, etc. It can also process scanned documents by applying OCR (Optical Character Recognition). Texternel uses state-of-the-art AI to extract information regardless of the document structure, language or writing style. The AI is built using documents and speakers in the native language, without using quality-degrading machine translations.
OCR Resume Parser can extract information from resumes in various fields and organize it in a structured format, like a database or spreadsheet. This can include information such as the candidate's name, contact information, education, work experience, skills, and other relevant details.
The extracted information can then be used for tasks such as resume screening, candidate tracking, and database management. This can help streamline the recruitment process and make it more efficient for various industries such as IT, Healthcare, Banking and many more.
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 Parser 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 Parser 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:
You need to set up a provider API that is requested if and only if the main OCR Resume Parser API does not perform well (or is down). You can use confidence score returned or other methods to check provider accuracy.
After the testing phase, you will be able to build a mapping of providers performance based on the criteria you have chosen (languages, fields, etc.). Each data that you need to process will then be sent to the best OCR Resume Parser API.
You can choose the cheapest OCR Resume Parser provider that performs well for your data.
This approach is required if you look for extremely high accuracy. The combination leads to higher costs but allows your AI service to be safe and accurate because OCR Resume Parser APIs will validate and invalidate each other for each piece of data.
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.
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You can see Eden AI documentation here.
The Eden AI team can help you with your OCR Resume Parser integration project. This can be done by :
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