Use case
Use case3 min readBy The Data Workers Team

AI cost management, run by agents

Token and compute spend on agents and copilots grows without anyone knowing which work it buys. Here is how Data Workers runs it instead.

Key takeaways

  • •The problem today. Token and compute spend on agents and copilots grows without anyone knowing which work it buys.
  • •What changes. Every mission and agent run shows its token cost, and the Autopilot dashboard ties spend to outcomes per domain.
  • •What stays with your people. Budget limits and approvals: finance sets them.
  • •The result. AI spend is visible per outcome.

The problem today

Token and compute spend on agents and copilots grows without anyone knowing which work it buys.

What changes with Data Workers

Every mission and agent run shows its token cost, and the Autopilot dashboard ties spend to outcomes per domain.

The workflow: Autopilot → Usage Intelligence agent (get_cost_enrichment) → Cost Savings & Data Cleanup agent (detect_dead_assets) → Autonomous Data-Conductor (verify_data).
Fig. 1:The workflow: Autopilot → Usage Intelligence agent (get_cost_enrichment) → Cost Savings & Data Cleanup agent (detect_dead_assets) → Autonomous Data-Conductor (verify_data).

The workflow, step by step

  1. 1.Autopilot estimates cost before each mission.
  2. 2.The Usage Intelligence agent calls get_cost_enrichment and tracks spend per run.
  3. 3.The Cost Savings & Data Cleanup agent calls detect_dead_assets and removes waste.
  4. 4.The Autonomous Data-Conductor calls verify_data and ties spend to outcomes.

The impact metrics we move

  • •Cost per mission known: from about a month to seconds
  • •Spend report: from about a week to ~1 h
  • •Waste removed: from about 3 months to 1 day
Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.
Fig. 2:Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.

What goes on autopilot

  • •Every mission shows its cost up front, so no surprise bills.
  • •Spend ties to outcomes, so budgets follow value.

Where your people stay in charge

Budget limits and approvals always go to a named approver, because finance sets them. Everything starts at L1, observing only, and autonomy rises only on evidence.

The pilot

  • •Scope. Cost visibility for one domain.
  • •First week. Agents run at L1, observing only, and show the fixes they would have made, with receipts.
  • •By week two. The routine work above runs on its own; anything sensitive stays with a named approver.
  • •At day 30. We review the impact metrics against your baseline:
  • •Cost per mission known: from about a month to seconds
  • •Spend report: from about a week to ~1 h
  • •Waste removed: from about 3 months to 1 day
  • •Cost. Start with a pilot ($7,500 one-time, credited in full against the first year). Scale is from $1,000 a month and Enterprise from $3,000 a month, billed annually, with unlimited seats, no usage meter and no markup on model spend. See pricing.

Related: The AI and automation page · The full team playbook

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