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.
Accelirate Document Processing Service Deliverables
AI Model for Document
Calssification and Extraction
85% Reduction in Document
Confidence Level Greater
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
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
Loosely organized into categories using meta tags
- Emails by inbox, sent, draft
- Tweets organized by hashtags
- Folders organized by topic
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?
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.
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
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, OCR and Document Processing was integrated within an 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.
- Increase Efficiency
- Increase Invoice Processing Speed
- Improve Customer Service Speed
Invoices Processed Monthly
Monthly Man-Hour Savings
AP Invoice Extraction and Interpretation
A major American Wholesale Retailer was seeking to automate its Accounts Payable Department. The AP Team receives hundreds of gas and freight invoices via email each day from over 80 different vendors and had been processing these invoices manually. This required an employee to open the email containing the invoices, key into the company’s internal system and look up the Supplier ID, then manually extract the data from each invoice and enter it into the internal accounting system that pays the vendors, repeating this process for each incoming invoice. To automate this, Accelirate designed a human-in-the-loop, Document Understanding automation solution. The automation is able to save incoming invoices, digitize and split the invoices, extract the Invoice Number, Invoice Date, Amount, BOL, Due Date, and Vendor Name from the invoice, and enter the data into the accounting system’s required fields; A Machine Learning model was also incorporated to handle over 80 vendor invoice formats. From there, the data is sent to a human for a final validation and the automation is complete with a full report sent to the team lead with what was done.
- Process Invoices as They Come In (24/7)
- Reduce AP Invoice Errors
- Increase Accounts Payable Productivity
Transactions Processed Hourly
Education – Document Approval Process
A major online education company retrieves thousands of student documents daily. A majority of these documents are submitted and then deemed “pending review”. To reduce workload capacity and time from pending to “Reviewed and Accepted” the organization deployed a document processing automated solution. The automation retrieves documents, classifies the type of document and labels it either “acceptable type” or “unacceptable type”. From there, the automation extracts the necessary student information fields needed for the process. If the automation extracts the required fields successfully and the confidence/accuracy of each extraction is above the predetermined threshold, the bot will further process the document into the appropriate applications. The few that are extracted below the accuracy threshold are sent to the student documentation team for human review. The employee is quickly able to breeze through the document and validate the fields, as it has already been classified, separated, and prepared for review. After human validation the automation is given the document back to continue the steps for further processing.
- Reduced Number of Manually Processed Documents
- Implement a Document Solutions that will increase value over time
- Boost ROI from Automation
Documents Processed Monthly