Rhiz
PricingConsole

Enterprise / Operate

Connect what
works. Operate
what’s missing.

Rhiz takes responsibility for one governed path from signal to decision to action to evidence across the systems, people, and agents already involved.

Scope the first operating loop One bounded loop. Direct founder access. Explicit stop conditions.

The Operating Ledger: Workforce Placement

Illustrative
GoalMove qualified people into durable work faster
OwnerVP Workforce
Target outcome500 verified placements this quarter
AssuranceHuman approval on every match
Outcome threadsIllustrative operating view
Outcome threadOwnerConfidenceNext move
Qualify incoming candidatesTalent OpsResolve 12 incomplete records
Route employer demandPartnershipsConfirm three priority roles
Approve placement matchesProgram LeadReview exception queue
Verify starts and outcomesImpact OfficeCollect first-week receipts
Recent governed movesEvery move leaves a receipt
MoveBySourceApprovalCorrectionsReceipt
Routed 18 qualified candidatesRhiz agentATS + intakeProgram Lead0#2814
Confirmed employer capacityPartnershipsCRMVP Workforce1#2815
Approved 11 placement matchesProgram LeadShared ContextVP Workforce0#2816
Open threads24
Pending approval7
Corrections3
Evidence receipts186

Before Rhiz

Systems hold pieces.
No layer owns the outcome.

Fragmented responsibility

With Rhiz

One governed Context.
One accountable loop.

Aligned and adaptive
Rhiz

The operating loop

Rhiz turns the break
into impact.

The engagement stays narrow enough to govern and consequential enough to measure.

1

Understand

Name the costly break and the outcome that should change.

2

Connect

Bring the relevant systems, people, rules, and evidence into Context.

3

Route

Send each signal to the right person or agent with a clear next move.

4

Approve

Keep decision rights, exceptions, and consequential actions with people.

5

Act

Move the work across tools and teams without losing accountability.

6

Remember

Record the outcome, evidence, correction history, and next pattern.

Human authority

People approve
consequential action.

  • Set priorities and limits
  • Approve commitments
  • Hold accountability
  • Correct the record

Agent work

Agents research, route,
draft, and monitor.

  • Surface relevant Context
  • Draft plans and updates
  • Route to the right people
  • Monitor progress and risk

Agents expand capacity. People hold authority.

A bounded responsibility

Clear ownership before integration.

Rhiz owns

The coordination layer

  • Context model and routing logic
  • Governed human and agent handoffs
  • Receipts, exceptions, and outcome memory
Your team owns

Domain authority

  • Operational policy and final decisions
  • System access and accountable owners
  • Real-world delivery and correction
We prove together

The outcome change

  • Baseline and target measure
  • Evidence sources and review cadence
  • Continue, adapt, or stop decision

Good fit

One repeated break costs time, trust, revenue, or outcomes.

  • An accountable executive owns the outcome
  • Existing systems hold usable pieces of the truth
  • Decision rights can be made explicit
  • Improvement can be evidenced

Wrong fit

A vague transformation mandate without a bounded loop.

  • No clear owner or outcome measure
  • A request for staff augmentation
  • Automation without human authority
  • A universal data grab across private Contexts

Evidence before scale

Run one loop.
Make the change legible.

Cycle timeStalled handoffsDuplicate workOutcome receipts
Baseline first. Claims only after evidence.