Built to Be Trusted
When software touches advertising spend, there’s no room for ambiguity.
Don’t Break What Already Works.
Engineering for agencies means understanding that progress should never come at the cost of current performance. Our system is architected to prioritize account stability over aggressive change.
Only What’s Necessary.
No payment access
We use 'Limited Scopes' that explicitly exclude billing and credit card information. Your financial data remains entirely invisible to our engine.
No ownership change
Administrative rights are never requested. We cannot delete accounts, change ownership, or modify user permissions within your ad platforms.
No third-party sharing
Your proprietary campaign data is siloed and never shared with other clients, used for training external models, or sold to third parties.
Automation without limits is risk.
Every automated decision follows a rigorous, human-first logic chain.
Monitor continuously
Real-time polling ensures anomalies are caught in seconds, not days.
When in doubt, it waits
If any signal is ambiguous or falls outside historical variance, the system pauses and requests human review. We never force a guess.
Act only when clear
Execution only occurs when statistical confidence exceeds our strict 95% threshold for safety.
Log everything
Every thought, evaluation, and action is permanently archived for total traceability.
Intervention Prevented
Reason: Ad-set ROAS below stability floor. Action aborted.
Bid Shift (UK_Main)
Status: Applied. Confidence: 98.4%.
Sync Verification
Status: Integrity verified. 14,202 nodes stable.
Nothing Happens
In the Dark.
Every adjustment is logged, visible, and can be reviewed. We believe that for automation to be trusted, it must be auditable at any scale.
Automation Doesn’t Mean Absence.
Our philosophy is simple: technology handles the heavy lifting so that people can focus on the critical decisions. We empower operators to set, observe, and improve — carefully.
Restraint over Aggression.
Most automation fails because it chases short-term efficiency at the expense of long-term health. Our system favors restraint and consistency, ensuring that ad accounts maintain their algorithmic 'learning status' and baseline stability.