Agent cost visibility and attribution

Agent spending is attributable at the reasoning-cycle, agent, workflow, and tenant level rather than only at the account level.

Orchestration overhead and worker execution costs are separable, so teams can tell where each dollar is spent.

Cost traces follow every handoff in multi-agent workflows, producing a true cost-per-workflow-completion.

Tenant identifiers flow through all agent operations, supporting consumption-based billing, noisy-neighbor detection, and quota enforcement.

Technical telemetry is translated into business metrics. Cost-per-decision, cost-per-task-completion, and ROI against manual processes are reported, and they are available to business stakeholders through self-service dashboards.

Cost reporting stops at the AWS account level, so teams can't separate supervisor overhead from worker execution or identify which reasoning phase consumes disproportionate tokens.

Tag taxonomies exist on paper but are applied inconsistently across model invocations, function executions, and data operations, which silently breaks per-agent and per-workflow attribution.

Multi-agent workflows are analyzed one agent at a time because no workflow trace ID propagates across handoffs, producing inflated orchestration costs that go unnoticed.

Multitenant deployments lack tenant context in metric dimensions and cost allocation tags, which helps prevent consumption-based billing and allows noisy-neighbor tenants to drive infrastructure scaling for everyone.

Cost data stays inside engineering dashboards, so business stakeholders see only raw token counts and Lambda execution times, and can't translate agent spending into business outcomes or ROI against manual processes.