Genflow Ad Studio: A Compound AI Architecture for Brand-Aligned, Self-Correcting Video Generation
Recent advancements in generative video models demonstrate high visual fidelity, yet their integration into enterprise environments is restricted by temporal inconsistencies and severe brand misalignment. Current monolithic architectures struggle to enforce rigid brand constraints, frequently hallucinating unapproved visual assets. We introduce Genflow, a Compound AI System designed to enforce brand consistency in generative media production. Our architecture integrates a retrieval-based 'Brand DNA' extraction module to parameterize generation according to established corporate identity guidelines. Furthermore, we implement an Adversarial Multi-Agent Quality Control (QC) loop. Instead of ...
| Authors | Debanshu Das, Lavi Nigam, Sunil Kumar Jang Bahadur et al. |
|---|---|
| Primary category | cs.GR |
| Published | 16 May 2026 |
| Last updated at source | 16 May 2026 |
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