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Agentune: The Path to Self-Improving AI Agents

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At SparkBeyond, we believe that operational AI agents in general, and customer-facing AI agents in particular, should improve over time effectively.

Operational agents are designed and built with KPIs in mind. To optimize an agent, whether it's a sales agent optimizing conversion rates and order values, or a support agent increasing the customer satisfaction rate, we systematically apply the cycle:

Analyze → Improve → Simulate

That is, we analyze what is driving each KPI up or down and propose decisions and actions to improve each KPI. The improved agent is then tested using a customer simulation. Once tested and deployed, we restart the cycle with the agent's new operational data!

We are looking to release the different modules that are part of this framework in the coming months. At start, we are now releasing the Agentune Simulate customer simulator.

Looking to use Agentune and need help? Please contact us at agentune-dev@sparkbeyond.com.
We are committed to assist early adopters in making the most of it!