For the past two years, enterprise AI has largely centred on copilots and conversational assistants. These tools offered real productivity gains, but they worked in isolation, each operating within a single workflow or system. As organisations now begin deploying multiple autonomous AI agents across departments, a new competitive landscape has emerged. Vendors are now vying for control of the ‘agent layer’: the infrastructure used to orchestrate, govern, monitor, and optimise enterprise AI agents at scale.
Artemis enters the contest
It is against this backdrop that Kore.ai has chosen to launch Artemis, a new generation of its Agent Platform which provides an AI-programmable, AI-native foundation for building, governing, and optimising enterprise AI agents. The platform is currently available on Microsoft Azure, with further cloud availability to follow.
Three technical innovations underpin the platform. Agent Blueprint Language (ABL) is a language that standardises how agents are defined, validated, and governed, with six built-in orchestration patterns covering delegation, escalation, and agent-to-agent coordination. Arch, described by Kore.ai as an AI agent architect, turns business objectives into production-ready agent designs and continuously refines them using real-world signals. A Dual-Brain Architecture combines agentic reasoning with deterministic flows, managed by a single system and operating through shared memory.
The competition is intensifying
Artemis is the latest indication that the enterprise AI battle is shifting, or at least expanding, in this direction. Raj Koneru, CEO and Founder of Kore.ai, said the launch reflects the arrival of what he calls enterprise AI's “third wave”: “The Kore.ai Agent Platform reflects this shift [towards governance, observability, and trust] by bringing an AI-native architecture to market that enables enterprises to build, manage, and optimise multiagent systems with confidence.”
Other multi-agent orchestration layers to have entered the market recently include Salesforce’s multi-agent orchestration within Agentforce, SAP’s autonomous enterprise, Zendesk’s autonomous service workforce, and 8x8’s Engage model.
Kore.ai's model-agnostic approach positions it against platforms with tighter ecosystem dependencies. Where Salesforce is built around CRM and Microsoft around Azure and Copilot, Kore.ai is positioning itself as a layer designed to operate across all of them.
Governance becomes the product
As an increasingly in-demand aspect of the AI agent layer, Artemis has sought to make governance architectural rather than a compliance add-on. Research from Sinch found that 73% of organisations had rolled back AI customer agents as the realities of governance are taking effect. Kore.ai's response is to enforce every agent action as a “logged, traced, and analysed” event in real time, with deterministic constraints applied at the platform level rather than being left to the agent.
The battle for the agent layer
As enterprises deploy growing numbers of interconnected AI agents across customer journeys, priorities are evolving from simply deploying AI to coordinating it at scale. Growing demands around interoperability, observability, governance, and the risk of agent sprawl across systems, workflows, and departments are pushing vendors beyond standalone assistants and toward enterprise-wide orchestration platforms.
For CX leaders, the next competitive advantage may not belong to the companies with the most capable agents, but to the platforms best able to manage increasingly complex AI ecosystems.