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AI image and video generation platform development
Generation is the easy demo. Making it part of a tool people use every day — editable, repeatable, consistent and affordable — is the actual work.
What we build into products
- Image generation and editing pipelines — text to image, image to image, inpainting and outpainting, controlled by the user rather than by prompt roulette
- Background removal and segmentation, benchmarked across models because the quality difference on fine edges decides whether people trust the tool
- Layer extraction — pulling an object out of flat artwork and handing it back as an editable layer with its own mask
- Style transfer and brand consistency, so a set of outputs looks like one campaign
- Video generation — multiple models behind one roster, storyboarding, lipsync, upscaling and shot-to-shot consistency
- Batch generation with comparison and selection, because one output is never enough
The part that separates a product from a demo
AI output has to survive contact with an editor. If a background removal returns a flattened image, the user is stuck with whatever the model decided; if it returns a layer with a mask, they can fix the one bad edge and carry on. That single architectural decision is usually the difference between a feature people use and a feature people try once.
The second is cost. Every generation is real money, so pricing, caching, model tiering and quota ceilings have to be designed in from the start rather than bolted on after launch.
Common questions
Which models do you work with?
Whichever is best for the job and the budget — the architecture puts providers behind one internal interface so you are never locked to a single supplier's pricing or availability. Models are benchmarked on your actual content before one is chosen.
Can you add AI generation to our existing product?
Often that is the better project. Adding generation or editing to software that already has users and revenue is far lower risk than building a new AI product from nothing.
How do you keep a set of outputs visually consistent?
With a look or style system — a saved set of parameters, references and constraints applied across every generation in a project, so a sequence of shots or a campaign of adverts holds together instead of drifting.
How do you control generation costs?
Per-generation cost prediction before a job runs, credit holds, caching of repeated work, cheaper models on cheaper plans, and hard quota ceilings per user and per team.
Tell me what your customers should be able to design.
If your process today is an email, a sketch, and somebody rebuilding it by hand afterwards — that's the problem I work on.
or email hello@bytefold.io