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Kore.ai's new Autoloop engine addresses a critical gap in enterprise AI deployment by automating post-launch optimization to prevent performance degradation over time. By continuously adjusting agents against defined business goals like cost, accuracy, and rule adherence, the system mitigates the common issue of manual patching causing unintended side effects. This approach enables scalable, deterministic maintenance for complex agent networks without sacrificing safety or efficiency.

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Kore.ai launches Autoloop to keep tuning enterprise AI agents after they go live

SiliconANGLEOctober 7, 20264 min read

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 they’re deployed. Autoloop goes after the way most enterprises maintain agents today, fixing failures […] The post Kore.ai launches Autoloop to keep tuning enterprise AI agents after they go live appeared first on SiliconANGLE.

Kore.ai launches Autoloop to keep tuning enterprise AI agents after they go live 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 they’re deployed. Autoloop goes after the way most enterprises maintain…

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