AdResonance turns fragmented ad channels into a governed decision system. It records what campaigns saw, what rules applied, what actions executed, and which outcomes improved the next decision across Google, Meta, Shopify, and vertical demand environments.

Today I’m launching AdResonance, an omnichannel advertising intelligence layer. The problem is simple: advertising data is fragmented across platforms. Google, Meta, Shopify, TikTok, analytics tools, and vertical demand channels all show partial truth. Teams are left trying to understand what happened, why performance moved, and what decision should come next. AdResonance is built to turn those fragmented signals into a clearer decision record: campaign context, budget movement, creative choices, attribution signals, outcomes, and next-step recommendations. The first version is focused on helping operators see across channels instead of reacting inside disconnected dashboards. This is also part of a larger GENYS thesis: AI systems need memory, rules, and verification. AdResonance applies that thesis directly to advertising. I’d value feedback from marketers, agency operators, founders, AI builders, and anyone working on paid media, attribution, or campaign automation.