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Read stories illustrated by AI — every scene matched to the text, not generic cover art. Now make your own: give one sentence and it builds the world, cast, and light, then illustrates it scene by scene. Free to start, no login; every scene shows its prompt to copy and reuse. Read deeper, collect faster, make your own.
Hey PH 👋 Danny here. v1 of imaread illustrated stories scene by scene as you read them — not generic cover art. The ask was always the other way: let me make my own. 2.0 is that.
Give it one sentence — a premise, not a finished draft — and it builds the world, the cast, and the light, then illustrates your story scene by scene. You pick which moments earn a picture. The first five steps are free, no login; you only spend credits when you actually generate the images. (Already have a draft? Paste the whole thing instead.)
It doesn't ask you to be good at prompting — and it doesn't hide the prompt either: every scene shows the exact prompt behind it, free to copy and reuse. That's the shape of imaread now — read deeper, collect faster, make your own.
Every story has its own pictures; you shouldn't need to be a prompt engineer to see them. Part of the workbench is still going up — a couple of tools that work on what you've made aren't live yet, and I'd rather say so than fake it.
Try it with one sentence: ima-read.com/cs
Make something and show me — I'll be in the comments.
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About ImaRead on Product Hunt
“Read AI-illustrated stories — or make your own”
ImaRead was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #158 on the daily leaderboard. Read stories illustrated by AI — every scene matched to the text, not generic cover art. Now make your own: give one sentence and it builds the world, cast, and light, then illustrates it scene by scene. Free to start, no login; every scene shows its prompt to copy and reuse. Read deeper, collect faster, make your own.
ImaRead was featured in Design Tools (261.2k followers), Artificial Intelligence (473.1k followers) and Books (122.5k followers) on Product Hunt. Together, these topics include over 157.4k products, making this a competitive space to launch in.
Who hunted ImaRead?
ImaRead was hunted by Daniel Qian. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Daniel Qian