01
A management layer above the native interface
OpenAI Ads Manager provides the native campaign controls. Magnify is designed to add the operating layer around those controls: account structure, context-hint planning, product segmentation, performance interpretation, cross-channel comparison and supervised action workflows.
- Campaign and ad-group structure.
- Context-hint planning and iteration.
- Product-feed and ads_metadata strategy.
- Conversion-measurement readiness.
- Cross-channel budget and performance context.
02
Built for ecommerce operators
Ecommerce teams need product-level evidence, not only campaign totals. Magnify's product intelligence can carry the same commercial segmentation logic across Google Ads and ChatGPT Ads so product groups, margins and lifecycle signals remain useful when a new channel is added.
03
Native platform + operating system
Magnify is not trying to replace OpenAI's delivery system. The stronger model is to use the native platform for execution while Magnify becomes the place where the team decides what to launch, what to test, what to cut and where to put the next dollar.
04
What to demand from a management layer
A serious management layer should preserve advertiser isolation, keep credentials server-side, normalize campaign evidence, separate observation from mutation, retain change context and make cross-channel decisions explainable. For agencies, every client account must resolve to its own advertiser credential rather than a shared global key.
05
Current Magnify execution boundary
Magnify currently has the multi-tenant connection and read architecture in the repository, with live writes deliberately kept behind a product-release boundary. That limitation is explicit because a management product should not market an action path that is not safely available to customers yet.
