Every brand hits the same wall with imagery. Stock is generic and rarely on-brand, custom shoots are slow and expensive, and raw AI generation is inconsistent and looks it. The usual compromise is scrolling through endless stock for b-roll that almost fits, then settling for close enough.

The brief was to build an integrated generative AI workflow that removes that compromise: on-brand imagery you generate on demand rather than go and find. The inputs that actually define a brand's look, its visual references, brand guidelines and target audience are fed in and held in place by system prompts. These act as guardrails, so subject matter, colour grading, shot composition and overall aesthetic are captured as a reusable specification rather than left to chance on each run.

Two decisions carried the build. The first was to separate defining the look from generating the asset: an extraction step reads the reference imagery and distils it into one visual specification, composition, lighting, camera angle, colour temperature and subject, so the brand's visual language is written down once and reused rather than re-argued on every image. The second was to treat the system prompts as guardrails rather than instructions, because an ordinary prompt drifts with whoever writes it. With the brand's rules living in the system layer, the brief decides what the image is about and the guardrails decide whether it’s on brand, so consistency holds no matter who runs it.