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AI Content and Imagery

Three illustrated textbooks with ~550 consistent images

Volumes 3, 4, and 5 of an English-language collection for children, with characters that stay consistent across hundreds of images, QA at scale, and a client approval portal.

3
volumes produced and assembled
≈550
images generated
~R$ 320
in generation credit
Client
Bilingual school (elementary education)
Period
2026
Stack
Image generation (multiple APIs, benchmarked) · Python · Claude Design · PIN-protected portal on R2

The problem

Illustrating an entire book with AI is easy; keeping the same character consistent across 200 pages is not. And manually checking 550 images doesn’t scale.

What was built

A pipeline that generates, redoes, and links images to their positions in the book, with verification against the reference document (not guesswork) and prompts written in pure positive phrasing — negation doesn’t work in image prompts. APIs were benchmarked before selection: only one delivers an alpha channel, another always returns JPEG, and pure PNG costs 2x more and takes 5x longer.

The client approves through a dedicated portal with a PIN — nothing hosted on third-party services.

What was learned

A consistent image library is a matter of method, not luck: a canonical reference, batch verification, and a “redo” path that doesn’t break what’s already been approved.