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Kore.ai launches Artemis AI agent platform, expands challenge to Microsoft and Salesforce
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Kore.ai launches Artemis AI agent platform, expands challenge to Microsoft and Salesforce

VentureBeat AI · May 21, 2026, 1:00 PM · Also reported by 1 other source

Why this matters: a development in AI with implications for how people work, create, and decide.

Kore.ai on Wednesday launched what amounts to a ground-up reinvention of its core technology: the Artemis edition of its Agent Platform, a system designed to let enterprises build, govern, and optimize AI agents using AI itself — compressing what has traditionally been months of engineering work into days.The platform arrives at a moment when every major technology vendor — from Microsoft and Salesforce to Google and Service Now — is racing to become the default infrastructure for enterprise AI agents. Kore.ai's answer to that crowded field is a bet on neutrality, a proprietary intermediary language for defining agents, and a philosophy that AI, not human developers, should do most of the heavy lifting."We're trying to change the paradigm about how people design, build, deploy and optimize agentic AI applications," Raj Koneru, the company's founder and CEO, told VentureBeat in an exclusive interview ahead of the launch. "The whole theme that we are now coming out with is you do AI with AI — you design with AI, you build with AI, you test with AI, you deploy with AI, manage with AI, and optimize with AI."A new YAML-based language aims to standardize how enterprises define and govern AI agentsAt the technical core of the Artemis platform sits Agent Blueprint Language (ABL), a compiled, declarative language built on YAML that standardizes how AI agents, workflows, and multi-agent systems are defined, validated, and governed. Kore.ai describes it as an intermediary layer that sits between the natural-language instructions a business user might provide and the production infrastructure where agents actually run.ABL comes with its own parser, compiler, and runtime. It supports six built-in orchestration patterns — supervisor, delegation, handoff, fan-out, escalation, and agent-to-agent federation — that govern how multiple agents coordinate on complex tasks.Koneru framed ABL as addressing a fundamental gap in the current AI landscape. "There's a lot of

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