Driver's License Parser

Extract identification details from driver's licenses

Verify your client’s identity in seconds with automatic data extraction from driver's licenses. Whether you’re complying with KYC or onboarding customers, eliminate manual data entry and automatically extract accurate information into your system of record.

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Start with 100 documents free

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Up-to-date & accurate documentation

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Fast, technical customer support

Driver's License Parser with structured data extracted from it
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Extract the data you need from driver's licenses with Sensible

Identity validation is an important checkpoint for insurance companies and financial institutions. Extracting data from driver's licenses is a tedious and time-consuming process, especially when done manually. Automating this data extraction saves your team’s time and effort, and ensures that the information is accurate and up to date.

Sensible automates driver’s license extraction across all US states and territories. Teams using Sensible for identity verification benefit from increased efficiency and reduced manual errors.

Common driver's license extraction use cases

No matter where identification extraction falls in your verification workflow, trust Sensible to accurately extract the data you need in real time.

Know Your Customer (KYC)

Automate identification document extraction to guarantee consistent and accurate customer verification to reduce fraud risk and comply with regulatory requirements.

Customer onboarding

Ingest users’ driver's licenses and other identification documents to reduce manual entry time for quicker onboarding.

Identity verification

Streamline identity verification with automatic extraction of key data points, such as date of birth, address, and license number, from identification documents.

What data can Sensible extract from driver's licenses?

Some of the key data that Sensible can extract from your driver's licenses include:

Personal information

  • First name
  • Last name
  • Address
  • Date of birth
  • Endorsement
  • + more

Physical description

  • Height
  • Hair color
  • Eye color
  • Weight
  • + more

Issuing state information

  • State
  • License number
  • Expiry date
  • Issue date
  • Restrictions
  • + more
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The Document Automation Platform for Developers

Sensible is the developer-first platform that makes accessing the data in documents as easy as calling an API. Avoid PDF parsing headaches with Sensible Instruct – just describe the data you want to extract, and integrate it into your workflow or system. Augment Sensible Instruct with SenseML to maintain full control and visibility over your data extraction.

Extract data in seconds, not minutes or hours. Perfect for real-time workflows.
Extract structured forms, unstructured text documents, and everything in between.
Leverage LLMs to reliably extract data from your documents. Flag outliers with built-in validations.
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“We have a very high confidence that whatever data Sensible gives back to us, it will work with a high level of certainty.”

Danil Kolesnikov

Lead Engineer, Shepherd


Focus on building apps, not document extraction

Sensible gives you customizable control over your entire extraction process. Combine LLM and layout-based extraction methods to accurately extract data. There are no models to train (or retrain), and no onerous data requirements. Onboard using a single sample document, and publish production API endpoints in seconds.

Product Managers

Scale your business without reinventing the wheel

Sensible provides embeddable document extraction infrastructure so that your team can focus on building a great product, not wrangling OCR and AI services. Integrate with your product in just a few lines of code, saving hundreds of hours of development and ongoing maintenance.

Extract driver's licenses with just a few lines of code

Stop relying on manual data entry. With Sensible, you can claim back valuable time. Your ops team will thank you and you can deliver a superior user experience. It’s a win-win.

Stop relying on manual data entry to parse driver's licenses. With Sensible, claim back valuable time while ensuring mission-critical accuracy in onboarding or KYC workflows. Your engineering team will thank you and you can deliver an expedited user experience. It’s a win-win.

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Start with 100 documents free per month

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Up-to-date & accurate documentation

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Fast, technical customer support

Drivers License Parsing FAQs

We’d be happy to answer any additional questions. Please book a demo with our team to get more information.

What is driver's license parsing?

Drivers license parsing, also known as driver's license extraction, is a technological process that extracts and organizes data from driver's licenses in a structured format. The goal of driver's license parsing is to save time, reduce human error, increase processing efficiency, and improve data accuracy in KYC, onboarding, and identification verification workflows.

This process involves utilizing natural language processing (NLP) and machine learning algorithms to identify crucial information such as service information, account details, monthly usage, meter readings, fees, due dates, customer information, and more. The extracted data is then categorized and stored in a systematic manner, allowing for efficient searching, analysis, and management.

At Sensible, our AI-powered platform provides robust utility bill parsing capabilities that are customizable, accurate, and fast.

How does driver’s license parsing work?

Drivers license parsing, also known as driver's license extraction, is the process of converting unstructured driver's license data into a structured format. Here's how it generally works:

Document Input: A driver's license in various formats - such as .pdf, or a scanned image - is uploaded into the driver's license parser.

Pre-processing: The parser software performs preprocessing steps to prepare the document for extraction. This can include Optical Character Recognition (OCR) for scanned images or PDFs, removing special characters, and converting the entire text to a standard format.

Parsing: The parser then analyzes the standardized text to identify and tag different sections such as personal information, physical description, issuing state information, and so on. Advanced parsers, like Sensible, can even handle complex structures such as tables, checkboxes, and handwriting.

Data Extraction: After tagging, the parser extracts relevant data points based on predefined categories or tags. The parser converts these data points into a structured format, making it easy to store, manage, and analyze.

Output: The parser generates an output usually in a structured format like JSON or XML that can easily be incorporated into various applications and systems.

It's important to note that the quality and accuracy of driver's license parsing can significantly vary based on the parsing software used. Sensible’s advanced AI-driven approach to driver's license parsing ensures high accuracy and versatility, capable of handling various license types and layouts, even ones it has not encountered before. This provides users with reliable and efficient extraction of data from driver's licenses.

What is OCR for driver's licenses?

OCR, or Optical Character Recognition, is used to convert different types of documents, including driver's licenses, into editable and searchable data.

For driver's licenses specifically, OCR works by scanning the license, whether it's a physical paper, a PDF, or an image file, and recognizing the characters within it. This technology is capable of identifying text within the document and converting it into a format that can be edited, searched, or digitally stored.

However, traditional OCR has its limitations. While it can effectively 'read' the text in a document, it may struggle with understanding the context or structure of an invoice, especially if the document's layout is complex or inconsistent.

That's where advanced document extraction platforms, like Sensible, come in. These platforms go beyond simple character recognition. They can understand the structure and context of the data in a driver's license, which allows for more accurate and efficient extraction of key information such as address, date of birth, license number, expiry date, and more.

OCR for driver's licenses is a crucial technology for onboarding and identification verification, enabling businesses to save time, reduce manual errors, and improve operational efficiency.