Route AI tasks between Anthropic Claude models with Postgres policies and SLA

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Overview This workflow implements a policy-driven LLM orchestration system that dynamically routes AI tasks to different language models based on task complexity, policies, and performance constraints. Instead of sending every request to a single model, the workflow analyzes each task, applies policy rules, and selects the most appropriate model for execution. It also records telemetry data such as latency, token usage, and cost, enabling continuous optimization. A built-in self-tuning mechan