Scalability can be challenging, but we successfully applied IBM RPA in various areas of our company. For example, we used it for payment processing in the medical services department. The tool proved to be very stable for these processes.

Its availability and scalability are pretty high. I have used LDAP with the IBM tool because I have to sync a few members with AD groups. For that, I used JavaScript. I developed the communication outside of the IBM tool, but I can do the execution within the IBM tool using CMD commands.

My whole team is using this tool, so there are about 20 people.

It is a scalable solution. You can scale up without limits, especially when it comes to cloud automation, where various solutions are available like including data capture, process mining, fast scripting, and decision-making software.

The scalability is very good since IBM is very interested in artificial intelligence and very interested in expanding this field as soon as possible.

The solution is scalable. Three to four departments in the telecommunication department use it, which covers about 1,000 people. We have four environments with five or six administrators.

I rate the solution's scalability as five out of ten.

So far we've built 10 robots, so we haven't scaled it to the 100s, but from what I've seen on the architecture diagrams, and how we're building it, it seems like it's going to be scalable.

The tool’s scalability is good. We can get more tools if we need them.

If you are working on-premises then scalability could be a problem. This is certainly not a problem with cloud solutions but again, this is the same problem for us. Our clients would like to remain working on-premises. we all know that cloud-based solutions are the best, in order to have scalability and in order to grow in the number of bots or applications.

Most of our clients are mid-sized banks, and we have a lot of government entities.

The size of a container is quite small. I think it's only a single MB, so not big. Initially, we started from 20 containers and it grew to around 50 containers or maybe more, depending on the configuration. I think we now have approximately 50 to 100. The assumption is that each container will run a separate process.

The solution is scalable.

The solution is very scalable. If a company needs to expand this service they should be able to without much difficulty.

Just from an IT perspective, increasing the number of bots or reducing the number of bots on demand is a click of a button. It's as simple as that.

But from a business perspective, scalability takes a different meaning altogether because they want the same kind of bot to do a variety of different use cases. The key comes out in terms of design. At our company, one of the key things that we do regarding bots is to lay out the governance structure and always think from a microservices architecture perspective. Once it is from a microservice architecture perspective from the business side as well, it just looks like Lego blocks. You just combine them together and complete the use case and it becomes more scalable.

I rate the tool’s scalability a nine out of ten.

It's scalable.

IBM RPA is totally scalable. It's precisely the reason we have all of them in Kubernetes and the cloud. This makes them available for scalability, and it's very easy. In Kubernetes, you can scale up very easily, without any interruption of the service.

The solution is scalable. Around three to five people use IBM Robotic Process Automation in our company. 

As for scalability, we are starting with a very small footprint. We will explore and see how it performs when it is scaled.

The solution is scalability.

We approximately 100 people working on this solution.

It's very easy to scale. We have done it many times with many machines running simultaneously with integration between RSP and EDM quality management.