AI Generation Pipeline
Custom-built creative generation pipeline using Stable Diffusion, Midjourney, Runway, and proprietary fine-tunes. Brand-consistent outputs at scale, not generic stock-AI aesthetics.
Module · Performance Creative
AI-pipeline creative engineered for testing velocity.
100 to 250 brand-consistent creative variants per week — videos, statics, structured iterations. Engineered through AI generation pipelines layered with senior creative direction. The media team never starves for creative; the optimization loop runs continuously.
What's engineered
Six engineered capabilities.
Video Variant Engineering
Programmatic video variants — different hooks, different pacing, different end frames — generated from a single source asset. Dynamic captions, A/B-tested overlays, format adaptation for every placement.
Static Ad Production
Bulk static ad generation — Meta carousels, LinkedIn single-image, Google display, programmatic banners. Engineered with the headline-test matrix and visual-test matrix that performance bidding actually uses to optimize.
UGC-Style Engineering
Creator-style content engineered without requiring a creator network. Authentic-looking video and static work that performs against UGC benchmarks but ships at agency velocity.
Brand Consistency Engineering
Brand systems engineered into the generation pipeline — color tokens, type rules, voice patterns, visual consistency. Output looks like one brand, not 200 random AI experiments.
Performance Feedback Loop
Creative performance data flows back into the generation pipeline. The system learns which patterns convert, then engineers more variants in those patterns automatically.
Why this matters now
Beyond the agency creative bottleneck.
Most creative agencies ship 5 to 15 creative variants per month. Performance media at scale needs 5 to 15 per day to keep optimization loops running at velocity. We engineer creative production as a pipeline, not a per-asset deliverable — which collapses the cost of testing and removes the bottleneck that strangles most performance programs.
Engineered for testing velocity, not vanity.
Volume isn't the goal. Testing velocity is. When the pipeline can generate 50 brand-consistent variants per week against a defined hypothesis, the cost of finding what actually converts drops mathematically. The brands engineering creative this way compound a creative-quality advantage that's expensive to catch up to.
Brand-consistent, not stock-AI generic.
The visible failure mode of AI creative is generic aesthetics — every brand starts looking the same, generated outputs feel uncanny, customers stop trusting visual signals. We engineer brand systems into the pipeline first: color tokens, type rules, voice patterns, visual references. The output looks like your brand at scale, not like an AI dump.
Tooling deployed
The stack we engineer on.
AI generation: Stable Diffusion (custom fine-tunes), Midjourney, Runway ML for video, ElevenLabs for voice, Suno for soundtracks.
Pipeline orchestration: n8n workflows, custom Python pipelines, Replicate API for production-scale generation.
Editing & post-production: After Effects, Premiere, Figma, Adobe Express batch automation, custom Cloudinary transformations.
Asset management: Frame.io for review, Brandfolder or custom DAM for brand asset architecture, Notion for creative briefing.
Performance feedback: Performance data from ad platforms flowing back into BigQuery, custom dashboards surfacing winning creative patterns.
Engineer your creative pipeline
Get an engineered creative production system.
Discovery Audit includes a full creative review — output velocity baseline, brand consistency analysis, performance feedback loop assessment, and the highest-impact engineering moves for your specific situation. Six weeks, fixed scope, your roadmap.