Button Text
Home
arrow
Blog
arrow
Invoice Processing
Sep 29, 2022
Min Read

Automating Invoice Processing: Super.AI vs. Microsoft Azure

Share on TwitterShare on Twitter
Share on TwitterShare on Twitter
Share on TwitterShare on Twitter
Share on TwitterShare on Twitter
super.AI
Chief AI for Everyone Officer
SUMMARY

Software that helps companies capture, process, and record invoices for transactions and services often falls beneath the expansive accounts payable (AP) software category. However, when it comes to invoice processing automation, the most performant solutions may not be the ones that were built for AP automation specifically. Many of the best tools for extracting invoice data and inputting it into a centralized repository are general document processing solutions that leverage the latest artificial intelligence and machine learning models to accurately extract information from any invoice. These solutions typically include specialized parsers built to handle different document types.

This article is the first in a series of comparisons that will pit super.AI’s Intelligent Document Processing (IDP) technology against alternative options. To start, we will compare the super.AI Invoice Parser to the Microsoft Azure Form Recognizer invoice model (FRIM). This is a comparison, not a competition, in part because these solutions are fundamentally different:

  • Microsoft Azure FRIM is an AI optical character recognition (OCR) tool that can be used as a building block to create custom invoice processing applications
  • Super.AI Invoice Parser is a packaged solution that is ready to deploy and automate invoice processing immediately

Let’s explore what these applications do, including the pros and cons of each, as well as the situations they are best suited for.

What is super.AI Invoice Parser?

The super.AI Invoice Parser is an Intelligent Document Processing (IDP) application built on top of our unified AI platform for unstructured data processing (UDP). Our solution is capable of processing 100% of complex invoices with guaranteed quality thanks a few unique features:

  1. Users define processing priorities for quality, cost, and speed. The platform then automatically routes tasks to any the best combination of AI, human, and software workers to achieve the desired outcome.
  2. Processing is broken down into smaller pieces, leveraging the best AI for each, and intelligently combining the results into unified output. Three levels of AI—OCRs, key/value pairs with fuzzy matching, and custom ML models—learn from humans to make and improve decision making.
  3. An on-demand gig workforce (Data Processing Crowd) is available 24/7 to validate documents, when needed, to ensure quality.

Invoice Parser allows users to specify what fields to extract from Invoices. Users upload their data (PDFs or images) and download results (CSV or JSON file) manually or via RestFUL APIs.  Invoice Parser includes sophisticated role-based access control (RBAC) and HITL capabilities.

User interface screenshot of the super.AI Invoice Parser.

What is Microsoft Azure Form Recognizer invoice model?

Microsoft Azure FRIM combines powerful OCR capabilities with deep learning models to analyze and extract key fields and line items from invoices. Invoices can be of various formats and quality including phone-captured images, scanned documents, and digital PDFs. The API analyzes invoice text; extracts key information such as customer name, billing address, due date, and amount due; and returns a structured JSON data representation. The model currently supports English, Spanish, German, French, Italian, Portuguese, and Dutch invoices.

User interface screenshot of the Microsoft Azure Form Recognizer invoice model.

Microsoft allows users to sign up for an Azure subscription and create a Form Recognizer instance. Users can select Invoices from the pre-built models or upload models, then click on the “Analyze” button to extract a pre-configured set of fields from the invoice and download it in JSON format.  Customers can also upload the document using an API call and download the results.

Super.AI Invoice Parser vs. Microsoft Azure Form Recognizer invoice model

We aren’t just going to tell you our solution is better. The honest answer is… it depends. Both come with pros and cons, and therefore excel (or underperform) in different situations.

  • Who should chose Microsoft Azure Form Recognizer invoice model? Companies with skilled, in-house developers and highly specific requirements that demand extensive customization may want to consider leveraging existing IT or engineering teams to build a custom solution. This will involve ongoing development costs, significant lead time, in-house quality assurance (QA), and feature customizations (e.g., role-based access control, workflow/routing, HITL, active learning, analytics, etc.)
  • Who should chose super.AI Invoice Parser? Companies that are processing large volumes of data, and/or have multiple document processing use cases, the super.AI Invoice Parser would be a better choice. The Invoice Parser allows users to immediately deploy an automated invoice processing solution without incurring development costs or dedicating time to building or customizing a solution. Creating an effective and functional AI application from scratch is a potentially arduous process of trial and error. The Invoice Parser includes a number of features to streamline the process, eliminate development costs, and ensure AI investment delivers on business objectives.

As a packaged IDP solution, the super.AI Invoice Parser gives users advanced capabilities out-of-the-box and can turn even the most complex invoices into a machine-readable format without custom development. Microsoft Azure Form Recognizer invoice model is a modern AI-powered OCR that offers improvements over first-generation OCR. It can process invoices at scale at a very low cost. However, it requires custom software development to turn it into a complete solution.  Both have a place in the enterprise and should be selected based on the project goals and ready access to software developers.

Other Tags:
Invoice Processing
Comparison
Share on TwitterShare on Twitter
Share on FacebookShare on Facebook
Share on GithubShare on Github
Share on LinkedinShare on Linkedin

You might also like