Governed AI automation
Agentic optimization without giving up enterprise control.
DataX agents can detect, explain, approve, execute, verify, and audit runtime actions across analytics platforms. Every action is scoped by policy, permission, confidence, and rollback posture.
Approval-to-auto-execution maturity
Teams can start read-only, move to approvals, and later auto-execute low-risk actions when trust and controls are proven.
Observe
Agents detect waste and risk but do not create actions.
Recommend
Agents prepare actions with reason, owner, estimated impact, and confidence.
Approve
Higher-risk actions wait for a Data Platform or FinOps decision.
Auto-execute
Low-risk actions run inside explicit policy boundaries.
Verify
DataX records outcome, savings signal, rollback readiness, and audit evidence.
Provider action matrix
DataX separates declared capability from executable readiness. A provider can be connected for visibility while still missing the permissions required for runtime actions.
| Provider | Low-risk action | Approval action | Guardrail |
|---|---|---|---|
| Snowflake | Suspend idle warehouse | Resize warehouse | Tune auto-suspend |
| Databricks | Stop SQL warehouse | Right-size cluster | Cancel runaway query |
| BigQuery | Cancel query | Resize reservation | Reassign slots |
| Redshift | Pause cluster | Resize capacity | Route concurrency issue |
| Synapse | Pause pool | Tune DWU capacity | Flag serverless scan waste |
| Fabric | Capacity guardrail | Workspace routing | Throttle risk alert |