Our journey started with a migration initiative with something that already existed in an RPA solution. Then we started expanding and we started going into finance and HR activities. We use it in different entities and have been working with Automation Anywhere to build automation. We're seeing a lot of very good use cases that help deliver very good ROI.
Our company is quite large. We have several hundred applications and systems, including legacy systems. As part of a recent merger, part of our work is consolidating these systems. There are a lot of challenges. Someone has to manually perform activities, for example, to be an integrator between two systems. We use Automation Anywhere to bridge the gap. Wherever we can find and remove the human from repetitive tasks, we use Automation Anywhere.
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.
The improvements have already been rolled into recent releases, like better governance models. From a GenAI perspective, there are good releases like automation pilot and copilot that are already part of the product's release agenda.
They need to improve the stability of the core functionality. If they keep the core constant and constant, they will continue to thrive. It needs to stay consistent.
I have a long history with the solution. With my current company, we've been using it since 2021. However, in my previous roles, I've worked with it as well.
The platform is highly scalable. That's one of the key advantages. We build at first on a smaller scale, and build it up over time. The scaling part has been really seamless. It's been good so far.
We've had a great experience with technical support. They've partnered with us in terms of the challenges we face. We have a collaborative relationship and have had a positive experience.
As the product evolves, it would be great to have more support and have them up to date on the latest and greatest. The teams should be constantly upgraded to ensure that if something goes wrong, they can handle anything - that will be important for the future.
We do use other tools that are low code/no code, such as ServiceNow, SalesForce, et cetera.
Everyone tries to improve their opportunities. This competitiveness has helped the product evolve.
We've deployed processes within a week, while others might take four or six weeks, depending on the complexity. We have release schedules and release controls in place. Everything is streamlined, and we test before the automation goes live.
We're on the cloud, so we do not have to upgrade anything.
Maintenance is more on the partner-owner and device side. There might also be work upgrading and testing packages and new features. We do spend some time when a new feature comes out to test it before we actually upgrade our packages.
The licensing isn't an area I can discuss in great detail.
I'd rate the product eight out of ten. They have been an industry-leading automation solution provider. They have a lot of experience, and the core functionality is great. Keeping up with the market and putting in new competence into the product - the constant innovation - makes the product impressive.