Your business should be safer with AI than without it.
That means limits. Transparency. Launch in Ask me first mode, expand authority only when the behavior earns trust, and keep every move inside the rules you set.
If the move does not belong on autopilot, it routes back to the safer path with the prior state preserved.
Pause pathReview queueRollback window
Decision audit
Marko wants to increase Hero Campaign budget by $180.
High conversion velocity opened room to press, but the request crossed the auto-pilot budget limit.
Marko / Held for approval
Guardrails checked
ACOS target
Campaign is below target, so expansion is allowed to be considered.
Passed
Budget ceiling
The account stays inside the daily budget cap after the proposed change.
Passed
Auto-pilot threshold
The +$180 request is above the $150 limit for automatic budget moves.
Held
Contained path
Signal
High conversion velocity detected on Hero SKU.
Constraint check
Budget increase requested: +$180.
Guardrail triggered
Request exceeds the "$150 auto-pilot" threshold.
Status
Held for human review.
Safety in motion
You can see the controls working in real time.
Every move is logged, sensitive data and unsafe inputs get screened before model access, and requests outside your thresholds get slowed down, routed to approval, or stopped automatically.
Audit every move.
Recommendations, approvals, pauses, and reversals land in one visible trail with timestamps, reasons, and the exact rule that allowed or blocked the change.
Checked hero SKU against price floor
08:14 PM • Oracle • pricing boundary pass
Routed budget jump to approval
08:12 PM • Marko • change exceeds spend threshold
Blocked bid expansion on zero-conversion campaign
08:09 PM • Marko • emergency brake triggered
Reverted overspend spike from the previous cycle
08:05 PM • Claudia • rollback window used
Escalated listing conflict for human review
08:02 PM • Brett • protected catalog scope
Keep AI safe.
Add built-in checks that catch sensitive data and unsafe inputs before anything is sent or saved, so you can use AI with confidence.
Only your workspaceSeparate from other brandsNot used to train others
Authority expands after proof.
Profasee compares what the employee proposed, what actually happened in the account, and whether the move stayed inside your guardrails. Clean cycles can widen scope. Bad outcomes send the employee back to Ask me first mode.
THINK
PLAN
EXECUTE
REFLECT
Bad outcomes route back to Ask me first
Data sovereignty
Your data stays inside your workspace, not someone else's model memory.
The same safety system that controls actions also governs where account context lives, who can use it, and what leaves the platform.
Isolated by workspace
Each brand keeps its own rules, approvals, context, and audit history inside its own workspace.
No cross-brand reuse
Your account data is not reused to train another seller's system or mixed into another brand's memory.
Controlled access and export
Permissions, approvals, rollback history, and exports stay scoped to the people and employees you allow.
Export histories and decision logs any time. Permissions and approvals stay scoped to your workspace.
Transparency
Every decision can show its work.
See what the employee saw, what constraints applied, what it decided, and whether the action can be rolled back.
1
Structured actions
Every action has an owner, status, expected outcome, and reasoning trail.
2
Execution trace
The checks, API calls, and rollback points remain visible after the move runs.
3
Append-only history
Approvals, pauses, reversals, and outcomes stay in one audit trail you can inspect or export.
What they saw
Keyword "hepa filter replacement" generated 0 sales on $84 spend over 14 days
Constraints applied
Minimum 3% conversion rate threshold. Budget cap of $500/day for this campaign.
What they decided
Pause keyword. Reallocate $6/day budget to top-performing search terms.
Expected outcome
Save $84/14 days. Redistribute spend to keywords with proven conversions.
Can it be rolled back?
Yes.Keyword can be re-enabled with one click. Historical data preserved.
Progressive autonomy
Autonomy is earned, not given
Every employee can start at recommendations, move into Ask me first, and only widen authority once the work stays clean inside your guardrails.
1
Recommendations only
Observes and suggests. Takes no action.
2
Ask me first
Proposes actions. Waits for your approval.
3
Limited handling
Handles routine tasks. Escalates edge cases.
4
Broader handling
Manages most decisions within guardrails.
5
Full autonomy
Trusted employee. Acts within your boundaries.
1
Recommendations only
Observes and suggests. Takes no action.
2
Ask me first
Proposes actions. Waits for your approval.
3
Limited handling
Handles routine tasks. Escalates edge cases.
4
Broader handling
Manages most decisions within guardrails.
5
Full autonomy
Trusted employee. Acts within your boundaries.
Pause. Resume. Override. Reassign. Terminate. Autonomy is a privilege you grant, not a default.
More built-in controls
Safety is layered, not a single switch.
The big demos show the system at work. These controls reinforce the boundaries underneath them.
Confidence thresholds
Low-confidence moves route to review instead of live execution.
Double check
Bids, budgets, and prices are verified before execution, not after the damage.
No-fly zones
Lock specific ASINs, keywords, launches, or time windows from any change.
Anomaly pause
Unexpected patterns slow or stop the employee before drift compounds.
Rollback
Recent changes can be reversed quickly with the full trail preserved.
Fresh-data checks
If the signal is missing, stale, or weak, authority narrows and the action waits.
Operational controls
Cost is bounded too.
Safety is not only about bad moves inside Amazon. It is also about bounded spend inside the AI layer. Every employee has a budget, stop condition, and visible operating cost.
AgentBudget usedCost
Marko
PPC Manager
$42 / $60
Oracle
Pricing
$18 / $40
Bruno
Demand
$25 / $50
Brett
Listings
$31 / $40
Claudia
COO
$14 / $30
Total
$130 / $220
Track costs per agent, per task, and per cycle. See which employees are expensive, which tasks burn tokens, and where the stop conditions sit before costs drift.
Per-agent budget caps with auto-pause
Real-time cost tracking per action
Monthly spend reports by agent and task type
FAQ
Common questions
Yes. You stay in control. Ultra can start in Ask me first mode, you can approve or decline moves, and authority only expands when you want it to.
The system is built to catch risky moves before they spread. If a request crosses your thresholds, Ultra slows it down, routes it to approval, or stops it automatically with the full reason attached.
That is exactly what the guardrails are for. Ultra does not need you awake to stay inside the rules. If confidence drops or conditions shift, it reduces authority and stops the move.
Inside your Profasee workspace. Your brand's context, approvals, and decision history stay scoped to your account and are not mixed across brands.
No. Your data runs your employees, not someone else's. We do not use your account data to train another seller's system.
You do not go from zero to autopilot on day one. Employees can start with recommendations, move into Ask me first, and only earn broader authority after the behavior proves itself inside your rules.
Yes. You can lock specific ASINs, keywords, launches, or time windows from any change. Those boundaries are hard limits, not suggestions.
You are not trapped. Your history, approvals, and exported data stay yours, and you can leave without rebuilding your business around a black box.
Yes. You do not have to rip out your current operator to try Ultra. Most teams start alongside their agency or internal team, compare decisions, and expand only after they trust the output.
The safest automation is the one that can show its work, stay inside limits, and fail conservatively.
