Automating Invoice Processing: Super.AI vs. Google Document AI

By super.AI

This article is the second in a series of comparisons that pit super.AI’s Intelligent Document Processing (IDP) technology against alternatives. Previously, we wrote about Super.AI Invoice Parser vs. Microsoft Azure Form Recognizer invoice model (FRIM). In this piece, we’ll compare our Invoice Parser to an alternative offered by another industry heavyweight, Google Document AI Invoice Parser. Note that this article is a comparison, not a competition, in part because these solutions are fundamentally different:

• Document AI is Google’s document understanding platform that takes unstructured data from documents and transforms it into structured data, making it easier to understand, analyze, and consume. Invoice Parser is a specialized procurement processor that is part of the Google Document AI suite. It is a building block rather than a complete AI application.
• 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 Google Document AI Invoice Parser?

Google Document AI allows you to extract data from documents using pre-trained AI models. Document AI includes specialized models for common, industry-specific use cases like invoice processing within procurement. It also includes a human-in-the-loop (HITL) capability to allow users to review and/or correct extracted data with a low confidence level. There are many steps involved in setting up Document AI Invoice Parser before it can be used to extract information. As mentioned above, this tool is a building block rather than a packaged solution, and therefore has a significantly more extensive setup process.

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, guarantees outcomes, and offers access to an on-demand data processing crowd to accelerate automation while reducing costs and complexity. There are a few key features that set our platform apart from the competition, and enable us to process even the most complex documents with higher degrees of accuracy and automation than alternative solutions.

1. Guaranteed Output: Users define processing priorities for quality, cost, and speed. The platform then automatically routes tasks to the best combination of AI, human, and software workers to achieve the desired outcome.
2. Multi-level AI: 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. Data Processing Crowd: An on-demand gig workforce (Data Processing Crowd) is available 24/7 to validate documents, when needed, to ensure quality.

Super.AI Invoice Parser vs. Google Document AI Invoice Parser

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 choose Google Document AI Invoice Parser? 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 choose super.AI Invoice Parser? For 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. Users will also get better results from multi-level AI and have access to on-demand data processing crowd for validation/post-processing. 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.

Which IDP solution is right for you?

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. Google Document AI has more capabilities than Microsoft Azure Form Recognizer Invoice model, such as HITL support. However, the solution still requires significant setup and confidence intervals tuning to be useful. Additionally, its HITL functionality limits the pool of validators/labelers to 10, making it poorly suited for processing large volumes of documents. Google provides several building blocks for creating an AI application. However, developers are required to build a functional solution.