A business self-iteration method and system of an intelligent agent
By constructing a business objective evaluation matrix and a closed-loop mechanism, the intelligent agent can automatically identify the direction of problems, locate the failure links, and generate optimization measures. This solves the problems of insufficient adaptability and low iteration efficiency of the intelligent agent in business scenarios, and realizes safe and sustainable business self-iteration.
Patent Information
- Application Number
- CN202610545869.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-23
- Publication Date
- 2026-07-17
AI Technical Summary
Existing intelligent agents lack a goal-driven closed-loop mechanism in business scenarios, resulting in insufficient adaptability and long-term stability. The execution process is not traceable, and improvement actions lack verification, leading to low iteration efficiency.
By transforming business objectives into calculable evaluation dimensions, a business objective evaluation matrix is constructed to achieve a closed-loop mechanism of execution assessment, attribution diagnosis, and improvement verification. This generates an evaluation report containing failure labels and verifies improvement actions in a sandbox environment.
It enables autonomous optimization and sustainable iteration of intelligent agents, improves adaptability and business compatibility, and avoids the risks of directly deploying untested optimizations.
Smart Images
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