Intelligent Document Processing

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 Emerging Technology 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.

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.

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Accelirate Document Processing Service Deliverables

Pre-Processing
Automation

AI Model for Document
Calssification and Extraction

Post Processing
Automation

Human Validation
Station

85% Reduction in Document
Processing Time

Confidence Level Greater
that 90%

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.

Different Types of Documents

Structured Data

Often numbers or labels, stored in a structured framework of columns and rows relating to per-set parameters.

  • ID codes in databases
  • Numerical data google sheets
  • Star ratings

Semi-unstructured Data

Loosely organized into categories using meta tags

  • Emails by inbox, sent, draft
  • Tweets organized by hashtags
  • Folders organized by topic

Unstructured Data

Text-heavy information that’s not organized in a clearly defined framework or model.

  • Media posts, emails, online reviews
  • Videos, images
  • Speech, sounds

Why Implement IDP?

01

Flexible

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.

02

Smart

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”.

03

Accurate

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.

04

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.

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RPA Success Stories