Workforce Cloud - human-AI task orchestration that is fully real

Workforce Cloud overview

Workforce Cloud helps teams reduce manual handoffs and tighten SLAs by automating task routing, handoffs, and SLA enforcement between people and AI agents.

For a pilot, set a testable target such as 20–40% fewer manual handoffs or a 10–20% improvement in SLA compliance and measure results against your baseline.

AI agents as first-class workers

Treats AI agents (HUMΛN) as first-class workers with assignable identities, quotas, permissioned access, performance metrics, and auditability equal to people.

Treat AI agents the same way you treat a human in your org: give them an identity, limit what they can see and do, count their throughput, and hold their work to the same SLAs you use for teams.

In‑org deployment and governance

Workforce is fully real, in‑org. Deploy into the cloud you control or a VPC. That deployment model keeps data residency, access controls, and audit logs under your governance while running the same routing and orchestration logic your operations team expects. The security benefit is direct: your policies and monitoring remain the source of truth for data access and audit trails.

Operational automation and metrics

Operationally, Workforce Cloud automates five areas that drive predictable outcomes: intake validation, verified routing to human or AI agent, enforcement of handoffs and SLAs, execution tracking, and outcome reporting. Each step emits metrics you can measure against baseline KPIs so improvements are visible and repeatable.

• Intake validation
• Verified routing to human or AI agent
• Enforcement of handoffs and SLAs
• Execution tracking
• Outcome reporting
• Supports role-based controls, quotas, and audit logs to keep AI agent activity under organizational governance

Task lifecycle

flowchart TD
  Intake[Intake: request or event]
  Verify[Verify & enrich]
  Route{Route -> human or AI agent}
  Human[Human worker]
  AI[AI agent]
  Execute[Execute task]
  Escalate[Escalation path]
  Track[Outcome tracking & SLA]

  Intake --> Verify --> Route
  Route -->|Human| Human --> Execute --> Track
  Route -->|AI agent| AI --> Execute --> Track
  Execute -->|Needs help| Escalate --> Human
  Track --> Reports[Reports & metrics]

Task lifecycle showing intake, verification, routing to human or AI agent, execution, escalation, tracking, and reporting.

Pilot

Start with a single process and run a measured pilot. Recommended pilot parameters:

• Scope: one end-to-end process with 5–15 users (real operators and supporting staff)
• Duration: 4–8 weeks
• KPIs to track: percent of manual handoffs, SLA compliance rate, end-to-end task cycle time

Pilot steps

Pilot steps: map the current task steps, assign the decision rules for routing, give AI agents and human agents identities and quotas, and run the pilot while collecting the KPIs above. Depending on pilot scope, you can begin to see measurable improvements within the pilot window. Use the emitted metrics to compare against your baseline and scale iteratively.

Start small and scale

Start small, measure tightly, and scale the routing and SLA rules that prove highest impact. Workforce Cloud is built to make those operational gains real inside your cloud and under your control.

Start a pilot