Explore the logic, controls and outputs without a sales call. Every demo states whether it uses your inputs, synthetic examples or authorized Amazon data.
Connect authorized Amazon data in read-only mode and see up to three fully explained opportunities plus a protected preview of the remaining decision queue.
What you can see
Evidence, missing inputs, confidence, risk and a forecast range—never an unexplained score.
Enter your own advertising and margin assumptions to explore how ACOS and conversion changes could affect contribution profit.
What you can see
A scenario calculation based only on your inputs. It is not an account diagnosis or performance promise.
Follow one decision from observation through supporting and contradicting evidence to the recommendation, approval state and later outcome review.
What you can see
A product-faithful demonstration with clearly marked, synthetic data. No customer result is implied.
Compare detected, connected, discovery, monitored and actionable marketplace states without confusing visibility with a paid operating scope.
What you can see
A readiness view showing which data is present and what would still be needed before AdsPilot may act.
Explore Observe, Recommend, Approval, four-eyes review and Guarded Automation with veto windows, daily limits and profit safeguards.
What you can see
See exactly which control blocks or permits a simulated change. The demo never connects to or changes an Amazon account.
Filter commonly owned Seller IDs and third-party client mandates, rank decisions by expected contribution and open a named second-reviewer workflow.
What you can see
A product-faithful multi-account view with separated ownership, risk, readiness and approval state.
See how verified product facts can flow into listing copy, image directions, A+ storyboards and marketplace variants with QA and approval steps.
What you can see
Generated product examples are labelled as demonstrations and never presented as real customer work.
Open one protected decision in a responsive reviewer view and approve, reject, question or defer it with evidence and guardrails attached.
What you can see
A synthetic mobile workflow showing named responsibility and mandatory revalidation before execution.
Your inputs
Results are mathematical scenarios derived from values you enter. They do not claim knowledge of your Amazon account.
Synthetic examples
Demonstration data is realistic and internally consistent, but explicitly labelled and never presented as a customer case.
Authorized data
Only an authorized read-only connection can produce account-specific findings. The scan never changes Amazon data.
