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Motor Vehicle Repairers Industry Certificate (MVRIC) OCR Data Extractor.


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

500+
global customers
250M+
documents processed
10+
years experience

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

See our Motor Vehicle Repairers Industry Certificate (MVRIC) parser in action.


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

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

What is a Motor Vehicle Repairers Industry Certificate (MVRIC) OCR Data Extractor?

A Motor Vehicle Repairers Industry Certificate (MVRIC) OCR Data Extractor employs Optical Character Recognition (OCR) and Artificial Intelligence (AI) to automate the extraction of data from industry certificates for motor vehicle repairers. This technology captures and digitises key details using a cutting-edge OCR parser, such as certification numbers, expiry dates, and qualification criteria. By automating this process, businesses can reduce manual data entry efforts, ensure compliance with industry regulations, and maintain accurate certification records for repair technicians.

Using a Motor Vehicle Repairers Industry Certificate (MVRIC) OCR data extractor supports businesses in the automotive sector by automating the capture of certification numbers, expiry dates, and qualification criteria. This reduces manual data entry tasks, ensures compliance with industry regulations, and maintains accurate certification records for repair technicians.

Automatically process your MVRIC Certificates 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 Motor Vehicle Repairers Industry Certificate (MVRIC) extractor will automatically scan, extract, label and categorise the data on the MVRIC Certificates in seconds
Step 3
Export the data in a structured and usable format. Integrate our Motor Vehicle Repairers Industry Certificate (MVRIC) 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 Motor Vehicle Repairers Industry Certificate (MVRIC) OCR solution automatically extracts data from over 20+ fields.

Motor Vehicle Repairers Industry Certificate (MVRIC) Details

     
  • Certificate Number
    •  
  • Technician Name
    •  
  • Issue Date
    •  
  • Expiration Date
    •  
  • Qualification Criteria

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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

AI-Powered Motor Vehicle Repairers Industry Certificate Data Extraction | Affinda

Businesses around the world use our Motor Vehicle Repairers Industry Certificate (MVRIC) OCR Extractor in different industries and use cases.

Auto repair shop owners utilise our MVRIC OCR to quickly verify the credentials of potential hires, ensuring they employ only qualified and certified mechanics.

Regulatory bodies in the automotive industry benefit from our OCR technology to efficiently process and maintain records of certified repairers, improving oversight and compliance monitoring.

Consumer protection agencies use our MVRIC OCR to quickly verify the credentials of repair shops during investigations, ensuring consumers are protected from unauthorised or unqualified repairers.

Need to automate your Motor Vehicle Repairers Industry Certificate (MVRIC) workflows? Contact us.

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

All Document Types

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