Kore.ai Autoloop is an optimization engine built into Kore.ai’s Artemis Agent Platform that helps enterprises maintain reliable, high-performing AI agents from development through production. Autoloop enables teams to set measurable business goals, continuously evaluate agent behavior against those goals, trace failures to their root causes, apply precise fixes using Kore.ai’s Agent Blueprint Language (ABL), and validate every change rigorously to avoid regressions.
Key Features
Autoloop evaluates agent behavior across seven goal dimensions: task completion; accuracy and grounding; business-rule adherence; token and cost efficiency; end-user experience; robustness; and guardrails and safety. These goals guide both pre-launch readiness and ongoing production performance. StateTrace traces full execution paths—including handoffs, tool calls, context, and state—to reveal hidden failures. ABL maps each step in these execution paths back to specific constructs like routing rules or business logic, so fixes are targeted. Changes proposed by Autoloop undergo a gate process where they must pass all goals; if not, they’re rejected or held for human oversight. Three operating modes let organizations decide how much automation they want: Autopilot applies changes automatically, Copilot requires human approval, and Advisor only recommends changes. Autoloop is part of the broader Artemis platform, which also includes Arch, an AI architect that helps design agents from plain-language intent.
Pricing
As of October 2026, Kore.ai does not publish public, fixed pricing figures for Autoloop or the Artemis Agent Platform. Pricing is custom-quoted and depends on factors such as usage volume, number of agent seats, voice channels, integrations, and governance requirements. Kore.ai’s billing model includes “tiers” typically called Essential, Advanced, and Enterprise, plus usage-based billing for 15-minute conversational sessions and seat-based fees for agent-oriented tools. For example, the “per-session” rate is often reported as approximately $0.20 per 15 minutes. Support add-ons and infrastructure usage can further affect cost. Businesses must contact Kore.ai for a personalized quote.
Who is it for?
Autoloop is designed for businesses that rely on AI agents across complex, high-volume workflows—particularly those in regulated industries or with strict compliance requirements such as finance, healthcare, telecoms, or large-scale customer service. It suits organizations where agent performance must be consistent, auditable, and safe, especially when conversational AI is integrated with custom tools, business rules, and sensitive data. It benefits technical leaders (CIO, CISO) needing observability, governance, and controlled deployments, but also business stakeholders who care about outcomes like cost, efficiency, and user experience. Organizations with internal engineering capacity, who can define clear goals and create evaluation tests, will gain most from Autoloop’s diagnostic and repair features; smaller teams or ones with only simple chatbot needs may find the complexity and investment less justified.
Final thoughts
Kore.ai Autoloop delivers a compelling solution for enterprises seeking continuity and reliability in AI agent performance. Its goal-based evaluation, traceability, and targeted repair mechanisms set it apart from optimization workflows that rely solely on manual review or generic fixes. However, the lack of public pricing transparency and the investment required to define meaningful goals, tests, and governance practices mean it’s best suited to organizations with sufficient scale and rigor. For companies that need highly reliable, compliant AI agents—and are ready to commit to disciplined agent management—Autoloop is a strong candidate. For others, simpler tools or incremental automation may be more appropriate.
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