The classification feature is very good. That's the initial reason why we switched from the other product that we used to resell and then decided to utilize it within our own product. This feature doesn't require a bunch of samples like the previous technology that we utilized.

Previously, for instance, if we were classifying mortgage documents or bank statements, I had to get three or four representative samples of all of the bank statements that are out there in the country. With thousands of community banks, it's almost impossible to get all those samples. As such, we always had an issue with being able to classify a bank statement.

However, with Grooper we didn't even use samples. Instead, we put in what's called positive extractors that look for certain keywords or characteristics of what makes up a bank statement. By doing it that way, we were able to classify probably 98% of all bank statements without ever having received a sample of each.

The second most valuable feature is extraction accuracy. That was an add-on bonus for us because initially, we were just doing classification, and being able to do more accurate extraction opened up another revenue source for us. We were able to add on the extraction capabilities to our classification and so now, pretty much everybody that we talk to wants not just classification, but they want extraction. Furthermore, when they see the accuracy of the extraction, everybody's very happy.

Grooper can extract from and ingest pretty much every image file type. It can handle TIFFs, JPEGs, PNGs, BMPs, basically all image file types, PDFs, all of the Office docs including Word, Excel, PowerPoint, Text files, XML files, and more. There's no limit on which file types they can process.

The data output and reporting are fully customizable. We have total control over what data we extract and have that included in an XML file. Grooper has a couple of export modules to allow you to export that XML data raw, it can do XSLT conversions to reformat it in a different manner if we have a specification for that, or we can output that to a database. For database output, we can have it inserted into the tables and fields in the way that we want them.

Grooper does not necessarily do the actual reporting, other than internal reporting as far as statistics like the batch state, how many batches, where they're at, if there are any errors, and that kind of thing. But, in terms of extraction data reporting, we do have the mechanisms to export all of the data to either a database, XML files, and other formats. We will take it from there and load that into whatever system we're going to do the actual reports in.

The user interface is easy to use, and the flexibility is noteworthy. Because of the way the system is architected, different people can follow different approaches and get the same result. For example, there are three of us in my company that are trained on Grooper. If each of us were to do the same project, the chances are that each of us would do it differently. Depending on how you think and how you would set things up, such as the extraction and the order that you want to do things in, it could differ based on these. However, the outcome would always be the same.

That's one of the nice things about it because it's not like, "Okay, you only can do it one way." Rather, you can do it in different ways. Some people don't like that, because they want to be taught using a fixed sequence like, "Okay, you do A, B, C, and D, and then you get your result." The system is flexible enough that I may do step D first and then A, and then C and then B and still get the same result.

From a user interface perspective, most things are available via drop-down menus, you can select references, and point back to your extractors, and other things like that. From a GUI perspective, it's very effective.

The extraction is the most valuable feature. That's the part that really is the heavy lifting of what we do. We have to either extract everything accurately or we're going to have to full key the complete itemized bill, which can take days. So now we're doing stuff that takes literally minutes, or even sometimes seconds, and we've reduced the labor by a hundredfold.

Grooper processes difficult sorts of data and unstructured or semi-structured content very well. It's probably one of the better solutions I've seen compared to other solutions I've seen out there. It does a lot more things like segmentation extraction. It does it a lot better. Grooper has more focus on these types of freeform documents where other solutions are very generic and this is a little more elaborate in what they've done. I think they take it to the next level of extracting freeform data.

Using the GUI-based application to configure extract jobs is better now. I've just gone through some training on this and it was like drinking from a fire hose. To be fair, once I got into it, it is a lot easier than it was. In the beginning, it could be a little difficult to figure out where everything is, just because it's a new environment, but it's pretty medium in how difficult it could be.

It enables us to modify the output. It's very important to us because right now we're extracting data before we have it sent to someone to look at it to correct any issues, and after so we can do comparison data.

The data classification abilities are very good. Using the keyword labeling, entering keywords, and the way that they could do it in different layouts as well is good. It could be horizontal, vertical, or it could just be an and/or-type situation with the keywords to identify different documents.

1. There is a lot of flexibility with extractors. There are many options and customizations that you can make to each individual extractor that allows you to tweak it for exactly what you need. You can then create a collection of extractors for a single field with rules about which one(s) to prefer.
   
2. Image processing and OCR. Technically these are two different segments of the platform, but they can be interdependent. Being able to clean up a document before OCRing it and having multiple OCR options lets us get the best results for each document.

The whole idea of Grooper, where the selected physical files can be extracted into a database and be analyzed. In the world of data science, data is the most important part of the problem and without it, there is nothing to work with.

With Grooper, the old archive of information can be obtained with the models we built.

Lexicons where the key vocabulary can be inputted it is very helpful.

The table extractors are very efficient with the three main methods. The transpose method can be used as well.