Your beta reader loved chapter seven. Your critique partner thought it should be cut entirely. And your writing group? Four opinions, none of them compatible, plus a heated side argument about semicolons.
Manuscript feedback is subjective. Good readers disagree. Good editors disagree. Agents pass on books that become bestsellers. There’s no blood test for “ready to publish.”
Timo Bozsolik-Torres spent years thinking about this problem from two very different angles. By day, he was a software engineer and data scientist at Google, working on Kaggle (the world’s largest data science platform) and deep in the question of how algorithms learn patterns from massive datasets. During paternity leave, when sleep became theoretical, he wrote a debut thriller called The Scaevola Conspiracy and discovered just how opaque the path from finished manuscript to published book really is.
What if you trained a model on what actually sells instead of what critics think makes a good book? Skip the taste debates and the theory. Just look at the data.
That question became Iris.
A Data Scientist Walks Into Publishing
Timo’s background reads like someone designed him to build exactly this tool. Two startups, a stint at Google working on AI initiatives and Kaggle, deep expertise in how machine learning models spot patterns in complex data. He’s a Kaggle Master, which in the data science world is roughly the equivalent of making the varsity team at the national level.
But he’s also a novelist. The Scaevola Conspiracy, inspired by the Cambridge Analytica scandal, explores what happens when tech companies abuse market power. He expected the writing to take four months. It took four years. (Writers, am I right?)
Along the way, he experienced every frustration debut authors know well. Opaque submissions, contradictory feedback, zero clarity on whether a manuscript is genuinely ready, and the creeping suspicion that agents spend about four minutes on something that took four years to write.
As a data scientist, that inefficiency was impossible to ignore. Patterns exist in commercially successful books. The question was whether machine learning could identify those patterns well enough to give authors useful, objective feedback before they ever hit “send” on a query letter.
What Iris Actually Does
Iris comes in two flavors, both focused on analysis rather than creation.
Iris Editor provides editorial guidance across 25 metrics. Upload your manuscript, and it flags sections where your pacing deviates from genre norms, where reading difficulty spikes or drops, where emotional resonance flatlines, where your sentence variety could use work. Think of it as a diagnostic tool. It doesn’t rewrite your prose, but it highlights the passages that might need your attention and tells you why based on data from books in your genre.
Iris Assessment evaluates your manuscript’s commercial viability. In a few seconds, it generates an overall score predicting how your book would perform in the market and how it compares to books that actually sell. That kind of feedback usually requires hiring a professional manuscript assessor and waiting weeks for a response.
The analysis spans over 30 dimensions. Pacing, reading difficulty, emotional resonance, genre fit, sentence structure, and more. Each metric is benchmarked against a large dataset of texts connected to real performance data from platforms like Amazon and Wattpad. Iris learned what sells by analyzing the full spectrum of books that thrived and books that didn’t, training on the real distribution of success and failure.
The practical workflow is simple. Upload a manuscript, get a report, see where your numbers deviate from the genre average, revise, run it again. Timo tracked seven major drafts of his own novel through Iris, watching his overall score climb from 61 to 67 as his edits addressed the patterns the tool identified. Other authors have reported improvements of up to 12 points, which Timo says “can absolutely make the difference between a bestseller that gets picked up by a publisher and an ignored submission.”
The AI That Doesn’t Write
Every other AI tool for authors right now is racing to generate better prose. Iris doesn’t generate anything. It reads.
That distinction matters way more than it sounds like it should. Generative AI (tools like ChatGPT, Claude, Sudowrite, NovelAI) creates text. Predictive AI, what Iris uses, analyzes existing text and identifies patterns. It’s the difference between a ghostwriter and an editor. One produces words on your behalf. The other evaluates the words you’ve already written.
This positioning has earned Iris a kind of credibility that generative tools struggle to claim. NAC Literary, a literary agency that represents authors, explicitly states that manuscripts improved with Iris are welcome in their submission pile, while manuscripts touched by generative AI are not. When an agency draws that line and puts Iris on the acceptable side, that tells you something about how the publishing industry sees the tool.
It also addresses a concern many authors carry about AI, the worry that using it means the writing isn’t really theirs. With Iris, every word is yours. The tool helps you see your manuscript the way data sees it, but it never puts a single word on the page.
The training data matters here too. Timo built the model using donated manuscripts and works under permissive licenses, plus publicly available sample chapters. The output is purely numerical, so the system can’t reproduce any training material. For authors worried about the copyright concerns that shadow generative AI, that’s a meaningful distinction.
And the industry is paying attention. The first known publishing deal for a book enhanced by predictive AI was signed on Christmas Eve 2024, with a second following in June 2025. Both used Iris. Publication details haven’t been announced yet, but publishers signing books that openly credit predictive AI analysis in their development process? That’s new.
What You Should Know Before Signing Up
The pricing isn’t publicly listed. Quantifiction offers a free trial and what’s described as a “small annual subscription” for ongoing manuscript analysis with multiple passes. The exact cost isn’t on the website, though. You’ll need to sign up to see current pricing, which is a real friction point for authors who want to comparison-shop before committing. (C’mon, just put the price on the page.)
It tells you what, not how. Iris can flag that your pacing in chapters four through seven deviates from genre norms. It can’t tell you whether that’s a problem or a deliberate creative choice. As Timo puts it, Iris “can’t judge whether a potential problem is a real problem.” You still need editorial judgment to interpret the numbers.
It’s web-only. No desktop app, no mobile app. Browser and internet connection required.
The user base is still growing. With over 2,000 subscribers, Quantifiction is a smaller operation than many established writing tools. That’s not a bad thing (small teams can move fast and stay responsive), but it means the community and support ecosystem aren’t as developed as what you’d find with larger platforms.
It’s a specialist. Iris does one thing well. It doesn’t help you outline, draft, worldbuild, or manage a series. If you’re looking for an all-in-one writing platform, this isn’t it. You’d use Iris alongside your existing writing tools.
Who This Is For
If you’re preparing a manuscript for submission to agents or publishers and want a second opinion that isn’t shaped by personal taste, Iris offers something genuinely different. It’s especially useful for authors deep in the revision process who want an objective benchmark, or for self-published authors gauging commercial potential before investing in covers and a marketing push.
If you’re early in the drafting process, or if you want AI that helps you write prose, Iris isn’t the tool. And if the idea of reducing your novel to numerical scores makes your skin crawl, that’s fair. Not every author wants their book scored like a term paper.
But for those of us who’ve finished a manuscript and are staring at the submit button wondering if it’s truly ready… Iris gives you something that didn’t exist before. Not an opinion. A measurement.
