It has a default platform from where Pega provides a PRPC. Inside that, we need to deploy Pega Robot Manager. From there, we can deploy to Pega Robot Manager. From there, we can assign it to multiple users for daily use.

It was easier to deploy before. In some newer versions of Windows, we used to face some of the update tree issues. Currently, we need to download the update tree separately, and we need to install it on our machines. Then, we need to install Pega. Normally, it is easier, however, with these newer versions in Windows - 10 and 11 - we are facing some issues. 

There are Office versions that are not working perfectly. We need to uninstall and reinstall it, and for some Windows 11 versions, the toolbox icons are not visible. We have tried multiple times, uninstalling and installing. 

Deployment times vary. Normally, it will take hardly less than half an hour. However, if the solution is ready and we have groups assigned, we can directly deploy it to our servers. From servers, we can directly deploy to the users as well from Robot Manager. In the user's machines are the VDAs that we are using. We need to configure all the settings, the run-time, the config files, and everything. That takes ten minutes to one hour at a maximum. Once the setup is done in every machine, we can easily deploy that that will be hardly five minutes. 

Setting up Pega Robotic Process Automation is complex. It's not simple to set up.

The deployment process depends on which project we are working on and what kind of delivery we are doing. Also, it depends from customer to customer. 

So, maybe if it is a decisioning framework as it is in telecom, maybe it will take at least six months because it has to self-learn the models, and there is a continuous interaction between artificial intelligence and machine learning teams. But if it is a typical workflow, maybe it is easier, but it depends on how quality engineers are working on that particular workflow. It changes from customer to customer.

It's a bit more complex than ABBYY. It should take around three to four weeks to set it up to render all the files inside and do things over there. 

They offer both on-premises and cloud models. The deployment is pretty simple. One developer is enough to do the deployment. It's also very easy to maintain. You can reach out to their support team at any time. So, the maintenance part is pretty good.

I would rate my experience with the initial setup an eight out of ten, with ten being easy. 

It could be deployed both on-prem and cloud. The deployment takes around five days. 

This use case itself is not that complex, which meant the setup was easy. It is pretty much a straightforward solution. It is A to B to C. There were no exceptions. On paper, it was a very good solution with a good process and a very stable process at that, which made things easy. Some are relatively easy to implement. They vary. I’ve had others that were harder in the past.

The last project was entirely an individual project. For the deployment, we tested along with the user. We did user acceptance testing. Once it was approved by everyone, we did a pilot run, and then we handed this over to the deployment team. They deployed it. They were a team of six or seven members. They handled setups individually as well. Typically there are not more than three hands on an entire solution. Once the solution was handed over to the client, it took them a day or two to set everything up.

Maintenance is handled via tickets. If there are any improvements to be made, we get tickets and resolve the issue. The engineers typically work on the solution and fix anything. Upgrades depend on the ticket's priority. It’s allocated to whoever has time to pick it up and action the maintenance.

The initial process is very straightforward. 

The initial setup is  moderate, not simple, and not complex. Adding integrations can make it a bit more complex. 

A team of two to three people would be able to handle deployment and maintenance tasks. 

The tool's setup is easy and gets completed in minutes. I would rate it an eight out of ten. We have a platform team who can take care of the deployment process. 

The initial setup is very straightforward.

The initial setup is a bit complex.

The deployment took a while to execute. It wasn't as simple as some of the other options that we had been looking at.

The complexity of the initial setup depends on if the customer is new and if they have an existing enterprise structure environment. This determines the kind of installation that is needed.

Initially, the setup is straightforward. With the upgrade to the new version 19.1, there were some challenges with the configuration files, the common config, the studio config, and the runtime configs.

When we work on a project we go on the config and look at the 19.1 version, but normally it was a simple set up.

I took one hour to set up the Pega Robotics.

We would like to see the initial setup be a bit easier. Right now, it's a complex process. 

The initial setup only took about six to eight hours or so. 

We have a big team that can handle deployment or maintenance. We have about 30 or 40 people who can handle any related tasks. We have mostly engineers and then a few team leads. If you include the team leads, we're looking at about 50 or so people that can cover this area. 

The setup was straightforward as the team working with Pega support was quite competitive.

The deployment of Pega Robotic Process Automation is very easy because they made deployments very simple. Earlier they were manual deployment but now they're automated.

The initial setup was straightforward.

It took a couple of weeks for the team to set it up.

The initial setup of Pega RPA was easy.

The initial setup was straightforward. We didn't face any difficulties with the implementation.

Deployment took six months.

The initial setup is not bad at all. I would say it was medium complexity. We got up and running and we could build a robot pretty quickly. For us, what we spent more time on is deciding what we were going to build a robot for. It was more the opportunity assessment. Once people heard that we could build robots, they flooded us with requests for building all sorts of robots. When we started getting all the requests, we started having problems with how to balance what went first right from the start. Any problems had nothing to do with Pega in general.  

We had to decide which request to do first and which one was more valuable. What we put in place was an opportunity assessment. If we got 15 requests, of course everybody thought that their robot was the most important to build first. It was coming up with that understanding and assessing the value of each of the robotic opportunities that became more difficult.