Kore.ai Launches Artemis Agent Platform on Azure for Governed Multiagent AI Workflows

Kore.ai has officially launched the Artemis edition of its Agent Platform, selecting Microsoft Azure as the inaugural cloud home for this innovative enterprise system. The platform is engineered to facilitate the building, governance, and operation of sophisticated multiagent AI workflows. This announcement signifies a shift in the conversation around AI agents, moving beyond mere capability to focus on the crucial aspects of control and administrability within an enterprise context. The core of Kore.ai's Artemis offering is its emphasis on a 'compiled' approach to agent construction. This is a deliberate move to transform agent development from a potentially chaotic mix of prompts, glue code, and API calls into a more disciplined software engineering practice. The platform introduces an Agent Blueprint Language (ABL), which provides a declarative method for defining agents, their workflows, orchestration patterns, and essential governance rules before these systems are deployed into production environments. This structured methodology is particularly vital for enterprises, especially those in regulated sectors like banking, insurance, healthcare, and government contracting. These organizations require AI agents not just to complete tasks, but to do so in a manner that is auditable, repeatable, and secure. Artemis aims to provide the necessary control layer to ensure that fleets of AI agents can operate safely and in compliance with organizational policies. The platform's design acknowledges that while AI agents offer significant potential for automation, the more consequential the workflow, the greater the need for robust governance. An agent handling sensitive data, such as claims adjudication or employee records, demands a higher level of oversight than one summarizing public documentation. Kore.ai's vision is to reduce the engineering bottleneck in agent deployment, enabling faster adoption while ensuring that organizational bottlenecks related to compliance, user training, and support are appropriately addressed. By centralizing the definition of agent behavior and governance, Artemis positions itself as a critical infrastructure layer for the evolving landscape of enterprise AI, where the ability to administer autonomy is paramount.