Runtime budget authority for autonomous agents - a set of tools to check, reserve, spend, and release budget before and after every costly, risky operation. The agent asks "can I afford this?" before acting, and reports what it actually used afterward.
Enables monitoring of running agent loops with token and monetary cost estimation, pruning of verbose thinking chains near limits, and routing sub-tasks between fast/cheap and deep reasoning models. It provides deterministic, MCP-compatible budget optimization for autonomous agents and copilot frameworks.
Enables agents to track real-time token spend and cost velocity, automatically throttle or freeze execution when budgets are exceeded, and enforce sandbox and safety guardrails.
Enables agents to monitor running loops, estimate token consumption and monetary cost, prune verbose thinking chains near limits, and route sub-tasks between fast/cheap models and deep reasoning engines. It provides budget-aware model routing and telemetry through MCP.
Enables AI agents to pre-flight estimate query costs, enforce hard budgets, reconcile actual billed spend, and suggest cheaper rewrites across BigQuery, Snowflake, and Databricks.