With this announcement, we’re excited to bring you another powerful update from AgilePoint’s AI and Machine Learning toolkit — introducing the AI Control Tower. This cutting-edge feature is designed to revolutionize how you integrate Predictive AI into your processes, all while maintaining governance, control, and a close collaboration between humans and AI.
This actually started back in 2016 when we released the first Machine Learning AI Extenders with AgilePoint NX v6, and then on April 22 with AgilePoint NX v8 SU2.4, released the integration with AWS SageMaker, but those were all just setting up the fundamentals, stage, and theme for the AI Control Tower.
With AI Control Tower, you can seamlessly harness the power of Predictive AI to streamline operations, reduce risk, and optimize decision-making — all without sacrificing oversight.
So, what exactly is AI Control Tower?
It’s a suite of Monitoring Activities that work in tandem with Predictive AI, forming what we call the Predictive AI Agent. These agents enables real-time monitoring, control, and adaptation of your process instances, dynamically adjusting them based on AI-driven predictions.
Let’s dive deeper.
The AgileExtender framework, which are at the heart of this feature, are custom monitoring activities. These go beyond traditional workflow activities by adding custom event-handling capabilities to your AgilePoint processes. This allows enhance and adapt process behaviors in real-time, based on specific instance events, and even connect with external systems or services.
Now, here’s the key difference. Unlike regular workflow activities, monitoring activities aren’t part of the linear flow of a process. Instead, they “float” on top, subscribing to various process instance events — such as when an activity starts, completes, or encounters a particular condition.
When these events occur, monitoring activities trigger predefined actions. This could be anything from sending a notification, initiating a sub-process, etc., enabling to enhance and adapt process behaviors in real-time.
Powering the monitoring activities with Predictive AI, makes 1+1=4, and you get a super power smart Agent which monitor your processes at real-time, powered with decision making and capable to apply on-the fly actions to adapt your process instances on the fly, to proactively make sure process, operation and KPIs meet their goals.
By integrating Predictive AI with Monitoring Activities, you essentially create an AI super-powered smart agent. This agent monitors your processes in real time, making informed decisions based on your company’s private decision-making training data, and dynamically applying actions to adapt your process instances on the fly. The result? Proactive management that ensures your processes, operations, and KPIs consistently meet their goals.
With the AI Control Tower and Predictive AI Agent, you’re not just reacting to changes — you’re proactively managing them, adapting your processes in real time, and leveraging the full potential of predictive AI.
In the following video, we are going to show how to configure Predictive AI Control Tower and then show it in action at runtime. We have broken this video in two parts.
Please note that these videos are meant for AgilePoint app designers who wish to go deep into the concept of AI Control Tower and their configuration. If you are interested in getting just a high level overview of AI Control Tower, please click here.
Design Time – Configure AI Control Tower
Run Time – AI Control Tower in action
Stay tuned for more updates, and as always, we’re here to help you make the most of these exciting new capabilities. See you in the next update!