Augento

Augento is for developers and teams whose language-model agents make recurring mistakes on tasks that can be checked against clear success criteria. It helps improve an agent’s behavior through reinforcement-learning fine-tuning, rather than relying only on longer prompts or collecting example answers for supervised fine-tuning. Connect an existing agent through Augento’s API-compatible endpoint, review its recorded runs, and select queries to use for training. Then provide a reward function that scores the agent’s outputs—for example, whether generated code compiles or a response follows a required format. Augento manages the training process and hosts the resulting fine-tuned model for use through an API. Typical applications include coding agents, agents that use custom tools, browser navigation, and other workflows where success can be evaluated. Augento is aimed at teams comfortable defining how to measure a good result; it may be less suitable when task quality is subjective or difficult to score automatically.

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