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Inference Wire

What happened in AI today, explained in 5 minutes.

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Media & Marketing·AI Agents & Automations·8 Weeks

NovelCraft AI

One Platform, 3x More Published Titles Per Author

Planning a novel takes weeks of upfront work across characters, settings, and plot structure before an author can start writing. We built an AI agent platform that handles that entire planning phase and generates multi-chapter manuscripts that stay consistent from start to finish.

15 minutes

Framework Generation

12+

Weekly Hours Reclaimed

5

Annual Titles Per Author

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Responsive UI mockup of the NovelCraft AI writing dashboard on laptop and mobile screens, a custom SaaS design case study by Hexaa.
“They got what we needed fast and the agents they built are now central to how our platform works.”
PL

Peggy Lake

Head of Content, NovelCraft AI

Before

Weeks of upfront planning, Manual chapter-by-chapter reviews, 1 to 2 titles per author yearly

After

15-minute story frameworks, Automatic cross-chapter memory, 4 to 6 titles per author yearly

Narrative

The full story.

The Challenge

A typical novel requires 4 to 6 weeks of character development, world-building, and plot structuring before the first chapter gets written. On top of that, authors spend 10 to 15 hours a week reviewing earlier chapters just to keep details consistent as the story grows. The team wanted a way to compress that timeline and let authors focus on the creative work instead of the admin around it.

What We Built

We built a system of AI agents that splits novel creation into clear steps. One agent builds out the full story blueprint, a second writes chapter-level prose that matches the genre, and a memory agent keeps every detail consistent across the manuscript. A background queue processes the heavy generation work so the interface stays responsive, and the full framework for a novel comes together in about 15 minutes.

Results

Authors now move from concept to a complete story framework in a single sitting instead of spending weeks on it. Weekly review time dropped by 10 to 15 hours per author. Title output per author grew from 1 to 2 per year to 4 to 6, with the same team. The platform paid back its build cost within one quarter through the additional titles published.

Story gallery

Project snapshots.

Technical proof

How it was built.

Implementation details and the stack behind the delivery.

Implementation highlights

Key engineering decisions from this project.

Novel framework creation compressed from weeks to a 15-minute session
Memory agent maintains consistency across 20+ chapter manuscripts
Set up automated pipelines that move tested features from development through staging to production with minimal manual steps

Stack snapshot

Tools and platforms used in the delivery.

OpenAILangchain FastAPICeleryReact

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