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Use the MRZ scanner SDK to onboard and verify users in your app
Our machine-readable zone (MRZ) recognition module enables you to quickly integrate passport-, ID document scanning, and data extraction features into your apps. Read data from identity documents of more than 150 countries to verify the identity or age of your customers instantly.
Our MRZ Scanner SDK can be easily integrated within your existing mobile app and used with regular smartphones and tablets. Cutting-edge data extraction does not require costly investments in specialized reading devices. Simplicity and speed matter and therefore, our MRZ Scanner SDK is designed for ease-of-use and saves a lot of costs by speeding up the existing workflow significantly. Also, privacy is one of our concerns. For this reason, our MRZ Scanner SDK is a 100% offline solution which complies to high-class privacy standards.
How does the scanner SDK work?
- Launch the MRZ scanner inside your app and hold the device over the document
- Our algorithm automatically extracts data from the machine-readable zone on your passport, visa or id document
- The extracted values are checked and passed to your code
Our MRZ scanner SDK is able to capture the identification document as PDF or image along with the MRZ. It’s the perfect way to capture all required data and being able to automate processes (i.e. performing background checks) with the verified data from the MRZ. Combine it with other documents or certificates you need and let the text extraction speed up manual data entry.
What are the advantages?
- Highest data extraction precision. Checksums automatically verify the data.
- Wide range of supported documents and countries with the two-line (td-3, td-2) as well as the three-line (td-1, MRV-A, MRV-B) standards.
- Highest data privacy, because everything happens on the device. There’s no requirement for a network connection or external servers
- Customize the user interface by easily adapting the MRZ scanner SDK to your CI
- Save costs with a fast integration and automated workflows while avoiding investments in specialized and inflexible reading devices
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