This is a cloud solution. The framework we had before was on-premises. We wanted to move to the cloud, and that was a huge change. We're also able to redesign and refine processes that may have already been in place.
During our migration initiative, we were able to talk to different customer groups and revisit aspects to make things better and do things that may be needed. We were able to effectively optimize the processes and redo what was already in the existing platforms.
There is a lot of interest in operationalizing AI. There's a lot of buzz around generative AI. We've been reviewing different AI services. However, our focus has been more on orchestrating an entire end-to-end process, not just the AI. When we're talking with all the groups, we try to identify which steps can be automated, and add AI into the mix, if it is needed and it makes sense. We've had a lot of opportunities to work within legal, corporate, finance, HR, et cetera, and we're working to bring more use cases into production. Right now, it's all in proof of concept.
The leadership is very invested in generative AI and doing a lot of research. There's a separate team that does InfoSec reviews. We're undergoing a stringent vetting process. We're in the analysis phase to ensure the data stays within the model and doesn't go outside the LLM for training.
We are finding opportunities to implement some hyper-automation options.
Automation Anywhere and even previous versions, which I've worked on, have good core functionality. The core functionality of being able to automate and build a solution that is local and low code is one of the key differentiators that's allowed us to find success.
It's easy for business users who don't have technical skills. We try to build and help users build automation quicker. We've built a framework around it that's made it easier for everyone to build automation.
The learner curve for users is okay. The curves are different for end users. We have a large footprint of citizen developers, and some take quicker or longer depending on prior project commitments. It depends on the amount of time they can commit to it.
We've used the automation copilot, which is quite useful.
We have a lot of internal tools. A lot of finance and HR, for example, have specific apps and platforms. We've established a lot of connectivity with other apps. If there's an interest that business users want to start building, we already have the framework in place, which makes integrations fast.
We get a seamless experience when using the packages. There are constant upgrades. It doesn't stay stagnant; there are new features added to it. The consistent growth of the packages has remained seamless.
We save time and money. I can't share exact details, however, we do have good ROI. We track time, compliance, cost avoidance, et cetera. Everything is heavily tracked, and we make it available for leadership to review.