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This article introduces a new feature allowing users to automatically tag AI generations with structured metadata regarding department, task type, and complexity for better cost tracking and compliance. By running classification asynchronously, the tool provides visibility into agent usage patterns without impacting inference latency, enabling teams to optimize model selection and budget allocation based on actual workload characteristics.

Sources coveringOpenRouter, AI Alignment Forum, LessWrong, Latent Space

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Classifiers: Track What Your Agents Do and What It Costs

OpenRouterJuly 24, 20264 min read

Define a taxonomy and a small model tags every generation in your workspace by department, task type, or agent complexity. Filter your logs and group your Activity analytics by the results.

You can now automatically classify your OpenRouter generations with structured metadata for AI usage reporting. Every request carries information: the type of work, the level of complexity, which department it came from, whether it contains internal data it shouldn’t. Classifiers, now available in beta, give you that visibility. Define your criteria (task type, agent complexity, compliance category, cost center). A model of your choice tags each generation, or a sampled subset, against your taxonomy and write…

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