We are using this product for natural language processing. Part of what it does is take our unstructured data and turn it into structured data.
Our industry is related to health and benefits, and one of the things that we do is to help companies secure good benefits that they can provide to their employees. There are a variety of things to consider such as demographics when we work with different carriers to provide companies with the best rates.
One of the problems that we have is the ability to process all of the carrier proposal documents for enrollment. There are different demographics, different costs, and different plans. Currently, all of the information is being processed by humans. However, we want to use machine learning to process it instead.
We rely on CMR Plus to process structured, semi-structured, and unstructured data, which is something that is very important to us.
This product has helped to boost our overall efficiency and performance. I would rate it an eight out of ten in terms of improving the way our organization functions. It has given us the ability to automate many manual tasks. Furthermore, it has helped us to collect the right data for our analytics. This is huge for us because it allows us to serve our clients more effectively.
Once the ML algorithms are deployed, the machine can deliver the benefit.
Our overall confidence in the data provided by this product is pretty good. We have to have confidence in the data.
Using CMR Plus creates value-added work for skilled workers. A lot of the manual back and forth, such as emailing Excel files and PDFs, is now gone. As a consulting company, it is important that we leverage the power of digital and machine learning, leaving more time for employees to tackle jobs that demand more skill.
The ability of this product to scale across businesses is good. We built a set of APIs around AntWorks, where the AntWorks engine is exposed. As such, we have a set of microservices that interact with it. This elasticity is important to us because it helps to handle the peaks as the workload is seasonal by nature. Furthermore, we don't want to overload or underutilize our server.
