Successful AI solutions need good, clean sample data in order to deliver on the promises that are being made.
This is great news to those of us in the AI document processing industry because it validates something we've known for decades: You need good sample data to build a successful document processing system.
However, there's a little more to it than that...
- 2 Secrets About AI Document Processing
- What is AI Document Processing?
- How AI Document Processing Improves Over Time
- How Document Processing Uses AI (and You) to Fix Data Errors
- What's a Use Case for AI Document Processing?
- Benefits of Document Processing with AI
Get Our Free Guide: 7 Ways to Modernize
Your Document Processing
Interested in taking your document / data processing to the next level? Check out our guide "7 Ways to Modernize Your Document Processing." In this packed 6-page guide, you will discover:
- Why many AI document processing systems can't handle everyday projects
- The #1 thing your system needs to carry you into the next big thing in computing
- How to process billions of data items per day
- Much more
Two Secrets About AI Document Processing
Secret #1: You Have to Get Intimate with Your Data
One of the biggest challenges people face in a complex document processing situation is simply knowing about all the variations of a document before they go into production.
I'll let you in on a little secret: We rarely know all the variations.
But the worst part is, most clients don't realize how much variation they have in their documents until they start a document processing automation project. It's just part of the process, and I’ve written about it before.
I jokingly call this "getting intimate with the data." But this is a very important step and is what's needed while the AI document processing system is being built.
So what does this mean? Look for a software vendor that can design a system that will perform exceptionally well in production from that good, clean source data.
Secret #2: Intelligent Document Processing Does Not Improve on It's Own!
You see, AI does not "just get better as it goes." Not on its own. That's another little secret.
It doesn't sound all that technologically advanced. Still, the reality is that if a new variation comes along and doesn't get good recognition, the AI document processing system has to be adjusted by a human to accommodate that new variation.
In my opinion, AI is getting worse right now.
The focus on GPT engines (Generative Pre-trained Transformers) has introduced us to the ugly side of AI: false data that looks correct.
If you’ve recently seen an online article that had blatantly incorrect factual data, the website was probably generated by the newest generation of GPT engines. They are very good at making text that looks like how humans write.
The problem is, and has always been, the AI doesn’t understand what it’s doing: it’s a talking parrot, unable to understand what it is creating.
Even these fancy, state-of-the-art engines, which are creating bad data as well as good data, have been human-trained.
How Document Processing Solutions Improve Over Time with AI
This is why systems don’t “just get better” on their own. And you don’t want your validation operators introducing errors into the system by accepting a change that may or may not be correct.
Some intelligent document processing solutions, like Grooper, have a lot of tools to help you facilitate a timely resolution to adding in new variations of documents. For instance, with these top solutions:
- You can copy or move a batch from production into the test environment with three clicks
- Once you have a document in your test environment, you can test against the published model, quickly find and adjust the model to recognize the new document or data element
- Push the model back into production
- Then, you can update the batches in progress to take advantage of this new model definition
Easy peasy, as they say.
So yes, AI document processing software does get smarter with time. But not on their own.
How Document Processing Uses AI (and You) to Fix Data Errors
With a trained human administrator making the necessary adjustments, the best AI solutions will operate at or nearly at 100% for data extraction. I know this because we've put a lot of time and effort into Grooper's ability to correct poorly OCR'd documents as we know that OCR software alone is not perfect.
Sometimes OCR is 100% confident, and the results are still flat wrong. (If your system doesn't have a way to fix poorly OCR'd data, you need to talk to us!)
The top-of-the-line automated document processing software, like Grooper, can force the data into the format it's looking for. How?
By using natural language processing concepts that are built into an implementation of Regular Expressions (REGEX). Once you turn on "fuzzy" regex, you now have the ability to force data into the form you want it to be in.
What's a Use Case for AI Document Processing?
For example, here's how I used NLP and regex in electronic document processing to correctly extract medical ICD 10 codes:
- I'm no expert in these codes, but I know there must be a library of them somewhere that we can validate against.
- A valid ICD 10 code is from 3-7 characters and starts with a letter. There are other requirements that make it ideal for a Regex pattern.
- I know OCR likes to confuse the number one and the lowercase “l.” They look a hell of a lot alike.
- Through weightings, Grooper can define the swap from an "l" to “cost less” than other character swaps.
- Algorithms favor efficiency, so I usually use .1, or one-tenth of the value of a normal character swap. This means I can run a very high confidence level for my field, 99%, and still have that swap happen.
- Any other character swap will cost 1/x, where x is the number of characters in the field. So in an 8-character word, a normal swap would cost 1/8th, or 12.5% of confidence for a single character.
If the Regular Expression engine wanted to make a swap, the resulting confidence would be below our threshold of 99%, so no match would result.
Benefits of AI Document Processing
This means that with a trained human administrator, you can get better data than OCR will give you. That's the important part here.
It's all about getting good data from bad, and it's an essential part of top-of-the-line AI / cognitive document processing solutions like Grooper.
We can massage data for you at scale to allow you to fully benefit from AI document processing. So what does this mean? Fewer errors directly relates to less cost of ownership and higher instances of straight-through processing.
Grooper was built to succeed where other IDP systems fail. So give us a call, and we'd be happy to show you how Grooper can help automate your processes.
Other benefits include:
Cost-Effective and Flexible
Improve your organization's efficiency by extracting structured data from unstructured documents and making that structured data available to your line-of-business solutions and users.
Improve your data accuracy and compliance
Automate and validate all your intelligent documents extraction to streamline compliance workflows, drastically reduce manual entry, reduce guesswork, and keep data accurate and compliant.
Use your data to meet customer expectations
With AI document processing, you can leverage new insights from your data to meet customer demands and improve satisfaction, advocacy, lifetime value, and spending.
What is AI Document Processing?
AI Document Processing is technology that uses modern methods to automatically read, understand and analyze documents.
Reading and understanding documents is a very challenging task for technology as there is a wide variety of document structures and formats, and poorly scanned document images.