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