Image alternatives

What are you optimizing for?

  • Speed: publish-ready images quickly
  • Control: exact masking, compositing, retouching
  • Consistency: uniform look across large catalogs
  • Risk: avoiding artifacts, especially on edges and text
  • Privacy: sensitive visuals and data exposure

Common approaches

Quick refinement workflow (RefineAI-style)

  • Best for: upscaling, artifact cleanup, background removal for everyday publishing.
  • Tradeoffs: can produce edge artifacts on hair/fur/transparent objects; requires review.
  • When it wins: volume work and fast iteration.

Manual editors (traditional)

  • Best for: high-end retouching, complex masks, precise compositing.
  • Tradeoffs: slower and harder to standardize at scale.
  • When it wins: flagship assets (hero images, print campaigns).

Template-first design workflow

  • Best for: consistent layout, backgrounds, and export sizes for marketing.
  • Tradeoffs: doesn’t fix underlying image quality issues by itself.
  • When it wins: teams producing many variations of similar creatives.

Local/offline image pipelines

  • Best for: strict privacy constraints and controlled environments.
  • Tradeoffs: more setup; may require compute and tooling knowledge.

How to decide quickly

  1. If you need pixel-perfect compositing, start manual.
  2. If you need fast publish-ready polish, start with refinement.
  3. If you need catalog consistency, prioritize presets + batch testing.

Neutral note

Any enhancement can introduce artifacts. Always review outputs, especially around edges, small text, and gradients.

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