How your AI team works
The team prepares. You decide.
Agents work ready inputs into reviewed owner outputs. You approve every send or order. Fictional example below.
Synthetic demonstration01
Give agents the right sources
Location, period, vendor, and source stay attached.
POS exportinvoice lineslabor summaryrecipe map
02
Hold what cannot be trusted
Missing, stale, or conflicting facts enter review.
coveragereview holdhuman decisionmissing ≠ zero
03
Put ready agents to work
Each close, forecast, cost, and buying comparison earns its status.
calculationseffective dateslocation scopeapproved rules
04
Review the owner output
A human reviews the decision, evidence, exception, and next action.
Owner view
Monday's decisions, controls attached.
SOURCE STATUS
- Sales + labor: accepted
- Invoices: one produce line REVIEW
- Affected recipe costs: withheld
NEXT-WEEK PLAN
- Forecast: $34,200 (planning estimate)
- Food ceiling: $10,300
- Labor: $8,200
WHAT CHANGED
- Dairy price rose after pack normalization.
- Fuel remains separate in landed cost.
OWNER DECISIONS
- Review dairy before Thursday's order.
- Resolve the produce line.
- Keep affected recipe costs blocked.
Decision support. No order placed.
Truth states
Built, ready, shadow, and live differ.
Built & tested
Code and synthetic cases.
Readiness-authorized
Private sources under controls.
Shadow / review
Beside current operations.
Client-live / public proof
Accepted use plus permission.
Find the right first workflow.
See what can run, what it needs, and the first useful output.
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