Kore.ai launches Autoloop to keep tuning enterprise AI agents after they go live
SiliconANGLE Duncan Riley
Kore.ai launched Autoloop, which keeps tuning enterprise AI agents after they’re deployed. It’s aimed at the messy part: fixing agent mistakes without opening new ones.
Based on reporting by SiliconANGLE, Duncan Riley — read the original for the full story.
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Kore.ai has rolled out Autoloop, an optimization engine for the AI agents built on its Agent Platform. The pitch is simple enough: companies set the goals, and the system keeps adjusting agents to hit them, even after they’re already live in production.
That matters because enterprise AI upkeep is still mostly a manual grind. Kore.ai says teams tend to patch failures one by one, and that fixing one problem often creates another. In its 2026 Kore.ai Agent Productivity Index, 79% of enterprises said they had reversed an action taken by an AI agent, while 70% said they’d run into a failure they couldn’t trace.
Autoloop starts from the company’s operating procedures, writes the first version of an agent and its tests, then keeps iterating until it meets the goals. Those goals can include task completion, business-rule compliance, cost and accuracy, with accuracy judged against the enterprise’s own data. Every proposed change gets measured against the full set, so lower token use isn’t supposed to sneak in at the expense of safety or getting the job done.
The system leans on Kore.ai’s StateTrace evaluation layer to spot where something slipped. It tracks the full production record, down to handoffs, tool calls and state changes across a network of agents. A five-layer validation setup makes most of the checks deterministic, which Kore.ai says is what keeps round-the-clock optimization affordable at enterprise scale.
Autoloop also uses the company’s Agent Blueprint Language, introduced earlier this year, to compile routing, business rules and guardrails into an executable state machine. That gives the system a precise way to rewrite only the piece tied to a miss. Kore.ai says the same approach now shows up in its own software development, where agents write code, contributing about 6,500 commits a month to a 2.6 million-line production codebase under 68 always-on guardrails. Autoloop is available now on the Artemis edition of the Agent Platform, which launched in May, and Kore.ai says it counts more than 500 Global 2000 organizations as customers.
My take — AI-written commentary, not fact-checked reporting
This is the right bet: AI agents don’t need more birthday-cake demos, they need boring maintenance that doesn’t collapse the whole stack. Kore.ai is basically saying the real product is not the agent, but the control loop around it. That’s a much more honest business than pretending deployment is the finish line.
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