AI Agents & Agentic Workflows

AI Agents & Agentic Workflows introduce autonomous, intelligence-driven execution directly into Stack Porter’s operating system. Rather than acting solely as analytical tools, AI agents observe data, make decisions within defined boundaries, and execute actions across the platform. This enables a shift from manual operations to intelligent automation.
Each agent is designed around a specific operational or strategic function, such as inventory optimization, cost monitoring, customer experience management, or performance analysis. Agents continuously monitor relevant data streams and respond to changes in real time.
Agentic workflows allow actions to be taken automatically based on intelligence signals. For example, an agent may adjust inventory allocation, trigger replenishment, escalate operational issues, or recommend pricing actions without human intervention. All actions occur within operator-defined constraints, ensuring control and governance.
Agents integrate deeply with commerce, supply chain, and communication modules. This allows intelligence to flow directly into execution rather than remaining trapped in dashboards or reports. Human teams retain oversight and can intervene, approve, or override agent actions when required.
Learning is continuous. Agents refine their behavior based on outcomes, performance data, and feedback loops. Over time, workflows become more accurate, efficient, and aligned with business objectives.
From an operational standpoint, AI Agents reduce manual workload, improve responsiveness, and enable teams to manage complexity at scale. From a strategic perspective, they allow organizations to act on intelligence faster than human-only workflows allow.
AI Agents & Agentic Workflows transform the platform from a system of record into a system of action.