Credit Note OCR Data Extractor.

Accurately extract over 20+ data fields from multiple Credit Notes all at once, including line items, in 56 languages.




monthly users


documents processed

10+ years

of document IP

Affinda is trusted by some of the world's leading organisations

See our Credit Note parser in action.

Our easy-to-use parser's interface is designed for everyone, with no training required for use.

Want to try the free tool?

Open this web page on a desktop device to upload your documents and see how it works for yourself.

What is a Cover Letter OCR data extractor?

A Cover Letter Optical Character Recognition (OCR) data extractor is an advanced technology that uses Artificial Intelligence (AI) and machine learning to accurately read, understand and extract vital data from cover letters. This innovative OCR technology is capable of accurately identifying key details such as candidate's name, contact information, skills, experience, and specific phrases or statements that match job requirements. This data is then transformed into a structured digital format that can be easily sorted, filed, and analysed.

The infallible accuracy, time efficiency, and improved data management are the chief advantages of a Cover Letter OCR data extractor. By speeding up the initial screening process, recruitment becomes more efficient, allowing for faster, better hiring decisions. Furthermore, a Cover Letter OCR data extractor aids in building a comprehensive digital database of potential candidates for future reference, making talent acquisition a seamless and coherent process.

Automatically process your Credit Notes in four simple steps.

Step 1

Upload your documents to Affinda directly to our app, or by integrating with email or document management platforms

Step 2
Our OCR Credit Note extractor will automatically scan, extract, label and categorise the data on the Credit Notes in seconds
Step 3
Export the data in a structured and usable format. Integrate our Credit Note parser with any downstream system or platform to use your data where you need it most
Step 4

Need an AI data extractor customised to your specific business needs? Our expert team can build a model tailored to your business workflows that integrates seamlessly with existing processes.

Extract data from dozens of fields.

Our AI Credit Note OCR solution automatically extracts data from over 20+ fields.

Personal Details

  • Full name
  • Title
  • Date of Birth
  • Address
  • Email Address
  • Contact Number
  • Gender

Education Details

  • Degree(s) Obtained
  • University/Institution Name
  • Year of Graduation

Work Experience Details

  • Job Title
  • Company Name
  • Employment Duration
  • Responsibilities

Skill Details

  • Technical Skills
  • Soft Skills
  • Language Proficiencies

Achievement Details

  • Certifications
  • Awards
  • Projects
  • Publications

Reference Details

  • Name
  • Company
  • Position
  • Contact Information

Don’t see the fields you need above?

Affinda makes it easy to add custom fields according to your bespoke requirements.
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Innovative features that set us apart from the rest.

Superior accuracy

Over 20+ fields extracted

Supports multiple file formats: PDF, JPG, PNG

Highly flexible and customisable

Supports over 56 languages

Upload and extract in bulk

Self-learning models improve over time

Seamless upstream and downstream integration

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Businesses around the world use our Credit Note OCR Extractor in different industries and use cases.

Recruitment agencies use our Cover Letter OCR data extractor to rapidly process high volumes of job applicant data. This contributes to a more efficient recruitment process and ensures no potential candidate is overlooked.

Human Resources (HR) departments leverage our Cover Letter OCR data extractor to automatically collect key details from job applicants’ cover letters, aiding HR professionals in shortlisting candidates faster for interview rounds.

Hiring managers utilise our cover letter OCR data extractor to effectively evaluate a candidate's skills, experiences, and suitability for a job role. It saves time, enhances the hiring process, and enables a data-driven approach to candidate selection.

Need to automate your Credit Note workflows? Contact us.

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We can build a solution for any document
workflow within weeks.

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