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Intelligent Document Processing

Utilize AI to Automate Processes involving Un/Semi-structured Documents

Accelirate’s Intelligent Document Processing Solution

Accelirate has implemented Document Processing and Automation Solutions for clients in all industries. Leveraging IDP tools and Process Automation platforms, Accelirate helps organizations implement end-to-end automation solutions for processes involving all kinds of documents. Whether its unstructured, semi-structured, or structured, Accelirate’s Delivery Pods are equipped to design, deploy, and maintain ROI-focused automations.

Document Processing Solutions vary depending on need and document type, however, they all follow the same IDP design framework.

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What is Document Processing?

Document Processing is an emerging technology business solution built around all-in-one OCR, AI, and Machine Learning tools.

These solutions, often coupled with automation, are able to process unstructured, semi-structured, and structured data of all kinds including, handwriting, emails, forms, and more. Intelligent Document Processing (IDP) is useful not only for extracting data, but also for understanding it. In the same way humans read and understand documents, IDP can create insight, and detect context and sentiment from complex unstructured documents, and then turn it into machine-readable data to be leveraged in downstream systems.

Where organizations truly stand to benefit from IDP is when it is coupled with process automation software. Using RPA bots to collect and load the documents into the IDP solution and then collect the exported information automation can be leveraged to complete a full business process and not just the digitization of documents.


Document Classification

Structured Data

Structured Documents

  • Like forms, passports, licenses, time sheets
  • Fixed in format and can contain handwritten text, signatures, checkboxes
Semi Unstructured Data

Semi Structured Documents

  • Like invoices, receipts, purchase orders, medical bills, bank statements, utility bills
  • Containing fixed and variable parts like tables
Unstructured Data

Unstructured Documents

  • Like contracts, agreements, emails, disease descriptions, drug prescriptions, news, voice scripts
  • No fixed format

Why Implement IDP?


Any kind of document can be processed. Training models is a thorough process that can be customized for all kinds of industry needs. Various document formats and data types can be analyzed and extracted.


Models are adaptable and continously learning. Slight skews in documents, changes in formats, and more are all learning experiences as they can adapt and remember corrections made over time to become “smarter”.


The more a model is used the more it learns. With each new correction and types of document processed the model becomes more accurate; eliminating errors and rework and ensuring compliance.

Unstructured Data Proficient

Models are often quick to build and depending on document type some models are pre-built and pre-trained with only small modifications necessary for deployment. High-volume document processes can be entirely automated and deployed in short timeframes.

RPA Success Stories

Claims Correction and Resubmission in Healthcare

The objective of this project was to automate the processing, correction, and resubmission of insurance claims. Prior to automation, claims were being processed on demand as an email containing claim information was received. These emailed lists can contain thousands of claims that require correction; with such a high number of claims it required SME’s to devote most of their time to correcting claims. To best automate this process the team found it best to split the process into two separate automations, one to manage ITS Claims and a second automation to manage local claims. To automate the claim correction process for local claims, the bot extracts information from the email containing claims with errors in them. The bot then logs into the record system. locates the claim list, and searches for each individual claim that needs correction. Once the errors have been corrected, the bot attaches a note and an EOB code to the claim, then notifies the SME of completed claim correction.

Business Goals

  • Improve Employee Utilization
  • Improve Employee Productivity
  • Reduced Errors
  • Minimize SME Claim Interaction

2.5 Minutes

Automated Claim Processing Time


Monthly Man-Hour Savings

OCR Invoice Processing in Manufacturing

The Accounts Payable Department at a major manufacturing company is responsible for locating and uploading all incoming invoices into the company’s SAP system. This process was originally extremely manual and consumed up to 75% of the AP team’s day during peak times. The Accounts Payable Department is held responsible for the accuracy and efficiency of locating invoice emails and uploading more than 200 received invoices into SAP daily. At this volume, the AP team was struggling to keep up with the fluctuating number of invoices, especially as vendors order more items during certain months of the year and often place orders that need to be completed quickly. To automate this process in its entirety and fully optimize the results, Optical Character Recognition (OCR) was integrated within the automation to read PDF invoices and enter the data accurately into SAP. The Bot Sorts through emails, locates invoices, reads them to find PO numbers and other critical information, sorts the invoices into 4 specific categories based on the type of invoice, logs the work, and emails a report to the Accounts Payable Department for approval and auditing purposes.

Business Goals

  • Increase Efficiency
  • Increase Invoice Processing
  • Improve Customer Service


Invoices Processed Monthly After Automation


Monthly Man-Hour Savings

Customer Service Center Desktop Automation in Global Financial Services

A major Financial Services Firm receives over 2 million participant calls each year through their Customer Service Centers. The ability to quickly pull up information about a customer’s account and plan number is critical to the department’s effectiveness within the company. The RDA Bot functions as a high-impact digital assistant on the CSR’s desktop that works in tandem with the user to, when triggered by specific commands or actions, pull up relevant customer and plan information and update it in real time. This enables the CSR to focus on the customer while avoiding post-call data accuracy errors, leading to a higher customer satisfaction rate and a tremendous decrease in both call time and hold time.

Business Goals

  • Update Internal Systems in Real-Time
  • Improve Data Accuracy
  • Reduce Repeat Customer Calls
  • Reduce Cycle Time
  • Increase Customer Satisfaction Rate


Annualized Savings


Call Time Reduction

Suspense Processing Automation in Mortgage Loan Servicing

A Major Loan Servicing Company is responsible for managing their borrower’s suspense accounts. The suspense account is a catch-all account in which the borrower’s money is stored until the loan servicing firm decides where to allocate the funds. The loan servicing company has a team in their administrative department dedicated to looking through loans daily and moving money from the suspense account to make loan payments to the appropriate area on behalf of their clients. Each person on the team is responsible for completing 160 loans a day, which consumes 4 hours of every workday. Accelirate created an automation that processes the daily list of loans and based on priority, pays as many fees and advance payments as possible with the money in each borrower’s suspense account. After the Accelirate Solution was implemented the client was able to double the amount of time their full-time employees have each week to work on other tasks and eliminate all errors in the suspense process, making for happier customers as all their payments and extra fees are now accurately paid on time.

Business Goals

  • Give Employees More Time to Work on Other Tasks
  • Increase Customer Satisfaction
  • Eliminate Errors


Monthly ROI


Monthly Man-Hour Savings

RPA Transforms Operation at Major Oil and Gas Corporation

For this Large Oil and Gas Client, Accelirate’s automation implementation services helped them fully understand RPA and the business value it delivers beyond just time and monetary savings. When the client approached us, they were new to automation technology. Within three months, Accelirate delivered two complete processes deployed into production, resulting in over $15,000 returned to the business monthly. The success from the program and the relationship built with Accelirate during the creation of this first wave of processes ignited a passion to implement automation throughout their entire organization. The client now has 75+ automations in production, a pipeline for the next 2 years of processes built out, and has furthered their digital transformation by building automations with integrated OCR and Machine Learning technology.

Processes Created

  • Accounts Payable
  • Electronic Ticketing Support


Monthly ROI


Hours of Manual Labor Saved Monthly