Prompt architecture systems
A documented prompt grammar for your brand: locked style tokens, subject slots, negative sets, sampler and CFG ranges, plus a variation matrix per shot family.
- Prompt handbook
- Style token library
- Variation matrix
Services
Everything between a creative brief and ten thousand approved files.
Engagements are modular. Most brands start with a pilot on one product family, then scale the same pipeline across the catalogue.
Request a scopeSix production services, delivered as one system.
ControlNet node tuning
Conditioning stacks built per shot type — depth for interiors, canny for packaging edges, pose for talent, segmentation for background swaps — with weights tuned against reference crops.
- Node graphs
- Conditioning maps
- Weight presets
LoRA model training
Dataset curation, captioning, balanced training runs and evaluation against a holdout set, delivering adapters that hold product geometry and label detail.
- Trained adapters
- Eval report
- Trigger-word spec
Campaign art direction
Concept boards, lighting and lens language, prop and set treatment translated into generation parameters your pipeline can execute repeatedly.
- Concept boards
- Reference sheet
- Shot list
Batch production runs
High-volume generation with per-batch reference comparison, artifact detection, upscaling and crop derivatives for every placement in your media plan.
- Master renders
- Placement crops
- Batch manifest
Governance and handover
Versioned pipeline recipes, rights and provenance documentation, and training for in-house designers who will run regenerations after handover.
- Recipe repository
- Rights dossier
- Team training
Technical stack
Tooling chosen per job, not per habit.
Midjourney gives us fast, opinionated exploration for mood and art direction. Stable Diffusion with ControlNet gives us the determinism production needs. LoRA adapters close the gap when a real product must be rendered accurately.
- Exploration
- Midjourney, style references, moodboarding
- Production
- SDXL-class checkpoints, fixed seeds and samplers
- Conditioning
- Depth, canny, pose, segmentation, inpainting
- Fidelity
- LoRA training, evaluation, upscaling and QA
Ways to engage
Pilot
One product family, one pipeline. Proves consistency and sets the production baseline before you commit volume.
2–3 weeks · fixed scope
Production retainer
Ongoing monthly output across categories and campaigns, with pipeline maintenance as models and checkpoints change.
Rolling · monthly volume tiers
Systems build
We build and hand over the full generation stack, then train your team to operate it in-house.
6–10 weeks · project fee
Send a reference set. Get a pipeline outline back.
Share ten representative images and your quarterly volume target. We return a proposed model route, conditioning approach and pilot scope with a fixed timeline.
Start a project