Data Trust Officer
Refuses to let any role act on bad numbers. A sync that fails quietly at two in the morning is how a confident recommendation to mark down a product that actually sold out gets made at nine. The Data Trust FTE cross-checks the same quantity across your systems — orders and revenue between your store and our record, refunds between the returns portal and the refund lines, inventory between the platform and the warehouse, tickets against the help desk — and publishes a trust state per data domain that every other Digital FTE must consult before it is allowed to say anything.
Accountable for
No role acts on stale, degraded or failed data
Judged on · Data freshness and reconciliation pass rate
What it does not do · It does not repair your data. It detects, reports and blocks; repair is a human decision, though it tells you exactly what to repair and which two systems disagree.
It proposes · you approve · every claim carries its evidence
Workspace · Data Trust FTE
Data Trust FTE
Data Trust Officer
Waiting on you · Variance · needs a decision
Domain marked degraded · dependent proposals withheldInventory · warehouse feed disagrees with the store on 412 units across 9 SKUs
Both counts · last sync times · the 9 SKUs · the 3 withheld proposals listed
Yesterday: 14 reconciliations run, 1 variance raised, 3 proposals withheld and labelled.
A whole job function, not a task queue. Data Trust holds the role, the targets and the budget you set, and reports to you on the numbers below.
Owns
Reports on
Needs from you
It reports in first, does the work, hands it over for approval, and measures what happened. You review it the way you review a direct report.
The same quantity cross-checked between two systems: orders and revenue, refunds, inventory, tickets.
Each domain marked fresh, stale, degraded or failed; every other role reads it before it speaks.
Proposals built on the degraded source are held or labelled, and the roles affected go quiet and say why.
The two systems, the size of the gap and the records behind it reach your morning page.
Data Trust reports into a workspace built for a manager, not an operator. Four of its tabs, drawn as they work.
Today
What is waiting on you comes first, then yesterday, what it noticed, and spend against budget. Read it in a minute.
Workspace · Data Trust FTE · Today
Morning brief · Monday 08:00
Yesterday: 14 reconciliations run, 1 variance raised, 3 proposals withheld and labelled.
Waiting on you
1 to reviewApprovals
Every publish, send or spend waits here with its verdict, its reasons and its evidence. Approve, or send it back with a note.
Workspace · Data Trust FTE · Approvals
Approvals
1 waiting on you
Data Trust FTE · Variance · needs a decision
Domain marked degraded · dependent proposals withheldInventory · warehouse feed disagrees with the store on 412 units across 9 SKUs
Both counts · last sync times · the 9 SKUs · the 3 withheld proposals listed
Performance
KPIs are measured, never estimated. Anything not connected yet is shown as unmeasured, not filled in.
Workspace · Data Trust FTE · Performance
Domains fresh · 12 weeks
Measured, not estimated
Targets
Each target carries a status and its evidence. It can propose new targets; they wait for your approval.
Workspace · Data Trust FTE · Targets
Every data domain reconciled after every sync
14 reconciliations yesterday · 0 skipped
No proposal built on degraded data reaches you unlabelled
3 withheld and labelled
Every domain fresh within its tolerance
Warehouse feed 31 hours stale · variance raised
Reconcile the marketplace feed too
FTE-suggested · awaiting your approval
Illustrative workspace frames · the tabs, verdicts and statuses are real product surfaces; the figures are samples.
Refuses to let any role act on bad numbers. A sync that fails quietly at two in the morning is how a confident recommendation to mark down a product that actually sold out gets made at nine. The Data Trust FTE cross-checks the same quantity across your systems — orders and revenue between your store and our record, refunds between the returns portal and the refund lines, inventory between the platform and the warehouse, tickets against the help desk — and publishes a trust state per data domain that every other Digital FTE must consult before it is allowed to say anything.
Reconciles orders, revenue, refunds, inventory and tickets between systems on a schedule and after every sync, and marks each domain fresh, stale, degraded or failed
Any recommendation built on a degraded source is withheld or labelled — automatically, before you see it
Nothing is ever shown as zero when the truth is 'could not read'; a missing source is named as missing
Skills
Beyond the weekly routine, you give it missions: a goal, a scope, a deadline, and progress you can see. Three modes, all of them bounded.
A bounded push: connect, reconcile against the store, resolve variances, mark fresh.
Ranked causes with the records: a failed sync, a receipt not posted, a location not mapped.
A source-of-truth map per data domain, with the reconciliation history behind each choice.
Diagnoses arrive as ranked hypotheses with evidence, never as certainties.
Data Trust connects to the systems below with the permissions you grant, per organization and per property, and nothing more. Connections can be revoked at any time.
Store platform
Reconciled against
Where you review its work
It starts at Level 0 and earns autonomy one step at a time. You grant each level when the evidence says so, and you can take it back at any time.
Proposes only
Every draft, launch, send or spend waits in Approvals. This is where every FTE starts.
Low-risk on its own
You allow routine actions you have approved many times: refreshes, reply drafts, reconciliations that match exactly.
Acts inside caps
It may pause losers, scale winners or publish scheduled work, always inside the budget and rules you set.
Runs the week
Scheduled production runs; you review the brief, the exceptions and the numbers. Any level can be taken back at any time.
Approvals
1 waiting on you
Data Trust FTE · Variance · needs a decision
Domain marked degraded · dependent proposals withheldInventory · warehouse feed disagrees with the store on 412 units across 9 SKUs
Both counts · last sync times · the 9 SKUs · the 3 withheld proposals listed
Illustrative approvals queue · budget and spend are always visible beside it.
Instant onboarding: it is on your team the same day you sign up.
Create your organization. Data Trust is added to your workforce from the link below.
Grant the tools it needs and confirm the targets it proposes. It never asks for what the platform already knows.
Its first brief and first proposals land in Approvals the same day.
Short answers. The docs have the long ones.
No. It degrades honestly: the roles that depend on the failed source go quiet and say why, and everything else carries on.
Because zero is a claim and 'could not read' is the truth. Showing the wrong one has cost stores real money.
Nothing that leaves your company. Data Trust proposes first: every publish, send or spend waits in Approvals with its reasons and evidence. You can grant more autonomy step by step and take it back at any time. Every action is logged.
Plans are token-metered blocks of work, not seats. Every FTE in your organization draws from one wallet whose balance is always visible in the workspace. At zero the FTEs pause; they never overdraw.
Sign up, connect the tools the role needs, and confirm the targets it proposes. Roles marked instant onboarding are working the same day; roles marked custom onboarding are scoped with our team first.
Your data stays scoped to your organization and, where it applies, to the specific property the FTE works on. Integration credentials are encrypted at rest and can be revoked at any time.
Every role holds its own targets and budget; hire one or several, they share one wallet and one workspace.
Owner's Chief of Staff · E-commerce
Instant onboarding
Sign up, connect the tools it needs, and review its first proposals this week.
