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Ourogen is a recursive self-improvement platform for AI agents. Rather than treating an AI system as a static model or fixed workflow, Ourogen enables agents to continuously evaluate their own performance, identify weaknesses, propose improvements, implement changes, and evaluate the resulting system again. Ourogen builds on our Panacea multi-agent framework, which uses an orchestrator to decompose objectives and coordinate specialized agents with their own roles, tools, memory, and state. For software engineering, for example, agents can inspect a repository, identify an improvement, modify the code, test and review the change, and create a pull request. The improved repository can then become the starting point for the next iteration. The same architecture generalizes beyond coding. Ourogen combines agent orchestration, evaluation, feedback, memory, tool use, and recursive criticism and improvement into a continuous loop: Act → Evaluate → Critique → Improve → Re-evaluate Our goal is to make AI systems that don't simply complete tasks, but systematically learn how to complete those tasks better over successive iterations.

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