Why is Data Extraction a Key Component of Intelligent Automation?

When processes are evaluated for Robotic Process Automation (RPA), one key factor to be considered is the nature of data used in the process. RPA can only work with structured, digital data. However, in the workplace, that is not often the case. Examples of unstructured data you may come across in the workplace include:


Unstructured emails or chats


Scanned PDF images of forms or other documents like invoices or lease agreements in PDF, TIFF, MS WORD or any other format

The data must be extracted from structured, semi-structured or unstructured sources. Lateetud has recognized the need for a holistic solution and has developed expertise to tackle the data-intake challenges.

Reduce time to automate by pic1
Increase scope of RPA by at least pic2

What are the Use Cases for Data Extraction?

A process always starts with some form of data - structured or unstructured and digital or scanned. RPA can automate processes as long as the data is structured and available in a digital format. Many RPA tools also provide data extraction capabilities.

The uses cases are indicated below:

  1. Extracting information from templates - structured or semi-structured
    • Invoices
    • Driver's License
    • ACCORD Forms
    • Flood Determination
    • W2
    • Tax Returns
  2. Data Extraction from unstructured formats
    • Bank Statements
    • Medical Records
    • Legal Documents
    • Payroll Documents
  3. Understanding language and context
    • Speech Analytics
    • NLP Based Chat
    • Email Based Work Items
    • Sentiment Analysis
    • Intelligent IVR

How to Get Started?

Data Extraction has yet to be boiled down to a science. Unstructured data requires more time to increase the efficiency of the process; solving data intake challenges must be addressed with multiple tools or technologies. Yet, successfully solving for data extraction is an evolutionary process that requires continuous improvement over time to optimize the extraction via building more rules or using machine learning models.

The below diagram provides a structured approach to get started with the initiative:

How Lateetud Can Help?

Through its service offerings – Envision, Accelerate and Cruise – Lateetud helps enterprises embark on the journey to solve data intake challenges. With multi-industry (banking, mortgage and insurance) expertise in automating processes, Lateetud has certified data extraction specialists who can help enterprise setup capability to extract and input data.

Lateetud can also help enterprises automate the upstream and downstream processes to extend the gains of data extraction.

Learn more about Advanced Data Intake

Request additional information on how Advanced Data Intake can help with data extraction from documents within your organization.