Kore.ai launches Autoloop to keep tuning enterprise AI agents after they go live
Kore.ai's Autoloop turns agent tuning into continuous optimization—no more manual fixes after deployment.
Why it matters
Enterprise AI agents today require manual intervention to stay aligned with business targets after go-live. Autoloop automates that feedback loop, adjusting agent behavior in production without redeployment—a concrete step toward operationalizing agents at scale.
The key facts
5 to knowKore.ai launches Autoloop optimization engine for its Agent Platform
Autoloop automatically adjusts deployed agents to hit business targets without manual fixes
Targets real operational gap: most enterprises manually maintain agents post-deployment
Feature enables continuous tuning after go-live, not just pre-launch tuning
Positions Kore.ai against the enterprise-agent productization bottleneck (post-demo adoption friction)
Go to the source
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Publisher excerpt: Enterprise artificial intelligence platform company Kore.ai Inc. today launched Autoloop, an optimization engine for the AI agents that customers build on its Kore.ai Agent Platform. Businesses set the targets, and Autoloop keeps adjusting the agents to hit them automatically, including after…