Case study

Guide to Handprint Data Extraction and

Digital Transformation


Capturing handprint data has been a source of hardship for most organizations, which is why we are covering the top five factors to consider when working on any digital transformation initiative that touches handwritten data and documents. With that in mind, DataGeometry has some exciting new capabilities that are being rolled out about Intelligent Character Recognition feature.


    Document Source

    First, consider the source of your content. Are documents coming in as faxes, emails, to a centralized location as snail mail, or are pictures of handprinted forms and letters being uploaded to a company portal from a snapshot on a mobile device. These methods of getting formerly paper documents into your organization’s key information systems should be aggregated and routed through a centralized process to ensure uniformity and optimize your document-specific business processes.

    Fortunately, with an application like DataGeometry IDP, we support ingestion of documents from all these sources and even have a mobile application that can
    be embedded in your company’s app via SDK or used natively to allow distributed capture in the field and on-the-fly.



    On the other hand,  DataGeometry IDP’s out-of-the-box ICR engine can be installed on-premises or leveraged in a private cloud.  here is no need to send sensitive information or customer data outside of your organization’s network and firewalls to take advantage of the rich capabilities of ICR.

    Complexity and Variation

    DG IDP utilizes Key-Value (or KV) pairs to identify and extract information from unstructured documents. This means the application looks for a particular pattern of text representing the key, and then finds the corresponding value based on the desired extraction field value’s relationship to the key. This approach eliminates the need to configure document type templates to extract data and can be applied to handprint data.

    This also means that DG IDP has the ability to find a snippet of handprint text on a page using that KV pair logic and send it out to a third party ICR engine in the cloud or otherwise, to pull back that converted value. One note about using a third party ICR engine is that there could be an additional cost associated with that vendor’s tool. Many ICR providers charge on a per  field-basis.

    However, with DG IDP, the ICR engine is embedded in the product, so there is no additional cost to you or  our clients for using handprint extraction, either on a per field or per page basis.

    Signature Detection


    Take the oil & gas industry, for example. The Inspection & Maintenance form is typically a part of a large packet of servicing documents that range in page length and complexity. Validating that any reviewer and approver have signed is crucial. But when a human being enters the mix, they spend time flipping through pages to find that one field and give the packet the green light. Automating this step saves time and therefore money in expediting the approval process.

    OCR, ICR or OMR Extract what you need.

    Lastly, just make sure you understand whether relevant data is machine printed, handwritten, presented with optical marks like checkboxes or radio toggles, or in some combination thereof. We often have project requests where a company or agency wants to have every field on a form or piece of information on a document extracted.

    But when we ask why… when we ask about the purpose of the information downstream, there is no answer. Limiting the scope of your project to include relevant data only whether that data is a signature on a contract, a checkbox on a form, machine or handprinted piece of information and your project timeline and cost of implementation will benefit.

    Agile, Rapid and Proven

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