Kore.ai Artemis | AI Agent Platform: Build, govern & scale enterprise AI

Meet {Artemis}

The AI-programmable platform for the agentic enterprise

The foundation for building AI agents with certainty.

Built with AI from the ground up { Artemis } leverages years of enterprise experience. Agents running on { Artemis} thrive in complex, high volume, regulated workflows where other agents break. This is the AI-native platform that experience made possible.

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What { Artemis } changes for enterprise AI

{ Outcomes in days }

{ Artemis } handles the infrastructure; your team starts at the business logic. Team focuses on outcomes. Agents ship faster.

5x faster time to value

{ Predictability at Scale }

Every agent is clearly defined, tested, and validated before deployment, so what works in design does not break in production.

No surprises in production

{ Security + Governance }

Every action stays within approved policies and boundaries, with full visibility into what happened and why.

Zero unauthorized agent actions

No more{it worked} inthe [Demo]

{ Artemis } has compiled IR, explicit memory contracts, typed trace events for every decision, cycle detection, and real observability.

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AI agents that move metrics

{ Artemis } delivers reliability across complex, high-volume, regulated workflows, continuously running, testing, and optimizing the metrics that matter.

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{ Artemis } is designed for what actually matters to an enterprise

AI Programmable is the new AI advantage

The three pillars behind the AI-native foundation for agentic AI

Auto Loop™

Auto Loop is powered by proprietary technology that eliminates weeks of manual agent engineering by continuously improving agents against outcomes that matter before and after deployment.

™ARCH

Arch is the platform’s built-in AI solution architect. It turns plain-language intent into a complete agent system - including agents, workflows, tools, policies, and handoffs - and helps teams build, manage, and optimize AI agents.

Agent Blueprint Language™ (ABL)

ABL is a typed, schema-driven language purpose-built for agentic AI. It lets enterprises define agent behavior, tools, guardrails, orchestration, and handoff logic in a formal, structured way.

Build.Scale.Optimize.

Build
Scale
Optimize

Build with AI

Build AI agents five times faster.

Scale with AI

Operate AI agents with provable reliability and control, in production, at scale.

Optimize with AI

Turn every agent run into a signal for incremental improvement.

Get started with { Artemis }

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Start AI-programming your next AI Agents

The Auto Loop™ Advantage

Free engineers to build

Issues across every AI agent get found and fixed as they come, before launch and after, so engineers spend time expanding automation instead of catching up on fixes.

Go from build to launch in days

Auto Loop continuously validates, repairs, and retests every change, so agents reach production quality in days instead of weeks.

Optimize for outcomes that matter

Auto Loop keeps optimizing latency, cost, and conversation quality, so agents get faster and cheaper to run the longer they're in production.

Ship with measurable proof of readiness

Objective evidence shows whether an agent or change is ready to deploy, giving teams confidence to ship agents, especially in regulated environments.

Validate the SOP before the agent

Auto Loop first resolves gaps and ambiguity in the SOP, so agents are built and tested against logic that actually holds up.

The ABL™ Advantage

Standardize agent development

ABL gives every team a common way to define agents, tools, guardrails, and orchestration, so agents are built consistently across the enterprise.

Ship AI agents faster

ABL replaces custom orchestration code with structured agent definitions, built-in primitives, and runtime-managed execution.

Make agent behavior explainable

ABL provides step-by-step visibility into not only what the agent did, but also why it did it.