Three Tools for Better Publications

Artificial intelligence is a red flag for many creative professionals. On the other hand, AI has long since made its way into the world of books, publishing, and self-publishing in one form or another. Not when it comes to writing, though—because I’m not the only one who still wants texts written by people with emotions and feelings, for real, flesh-and-blood people.

When it comes to publishing, writing is just one component of the entire publication process. For publishers, it makes sense to use AI for administrative processes to speed up tasks like managing the backlist.

Over the past few weeks, I’ve been looking into which areas AI models could support me in, both as a freelance editor and as a self-publisher. The selection is certainly larger in the English-speaking world, but for German-language publications, I’ve found three interesting tools (as of March 2026).

LiSA für Autor*innen und Verlage

Bereits gibt es 2018 LiSA von QualiFiction. Verfügbar ist eine Version für Autoren und eine für Verlage. Mit einem kostenlosen Demozugang kann man sich ansehen, was das Tool untersucht: Es ordnet das Thema ein, analysiert den Spannungsaufbau, liefert Zahlen zur Zeichen- und Wörterzahl, zur Satzlänge, zum Vokabular und zur Lesbarkeit, analysiert die Erzählperspektive und Aspekte der Figurenbeziehungen und gibt eine Einschätzung zum Leserpotenzial.

Preise gibt es für einzelne Manuskript-Analysen, die Paketpreise sind interessant, wenn man den Fortschritt des Manuskripts überprüfen will, zum Beispiel in Zusammenarbeit mit einem Lektorat: zur Preisübersicht.

LiSA for Authors and Publishers

LiSA by QualiFiction was already available in 2018. There is a version for authors and one for publishers. With a free demo account, you can see what the tool examines: It categorizes the topic, analyzes the build-up of suspense, provides statistics on character and word count, sentence length, vocabulary, and readability, analyzes the narrative perspective and aspects of character relationships, and offers an assessment of reader potential.

Pricing is available for individual manuscript analyses; the package prices are worth considering if you want to track the manuscript’s progress, for example in collaboration with an editorial service: see the price overview.

narratiQ as an Assistant for Publishing Editors

narratiQ is still relatively new on the scene. This tool also provides analyses of entire manuscripts. You can see exactly what the analyses include by signing up for the free demo account, which now gives access to 12 manuscript analyses, including one non-fiction book. Together with other members of the AI Working Group of the VFLL Editors’ Association, I was able to test this tool extensively. The findings of this test are summarized in a blog post on the VFLL blog: The AI Working Group has tested: Manuscript analysis with narratiQ

There is currently no information about the pricing model on the website, but to the best of my knowledge, there will be prices per manuscript analysis.

A User-Friendly Text Buddy from Scribigo

I’m currently testing Scribigo, which offers a text buddy under the motto “Proofreading meets editing.” This suggests that its features differ from those of the other two tools. While the latter focus primarily on analyzing entire manuscripts, the text buddy also allows for detailed work on specific sections of the text. This means I can decide for myself whether I want to analyze, edit, or proofread an entire manuscript, or whether I want to focus on specific sections of text or use certain features. I also really appreciate that I can import texts in many common file formats, including EPUB.

In my view, all of this makes the tool very appealing. As an editor, the fast AI TextBuddy could assist me with specific steps in the process, allowing me to devote more time to tasks that require human review without unnecessarily straining the authors’ editing budgets. As a self-publisher, I could use Textbuddy to further refine the quality of my texts before passing them on to an editor. Anyone who works with texts knows how many revisions are needed from the first draft to the manuscript ready for publication. And how easily one can become so immersed in the revision process that one simply skims over errors and inconsistencies. In some cases, AI support could certainly be helpful for this aspect as well, before a human ultimately puts the finishing touches on it and approves the final work.

Textbuddy’s flexible options are also reflected in its pricing. Instead of pricing based on analyses of entire manuscripts, it offers “Scribits,” which can be purchased as monthly subscriptions, flat rates, or for individual texts.

Data Protection and Conclusion

Data protection plays a crucial role in the use of all AI tools that handle text. No author wants their texts to be used to train AI models without their consent, and no responsible editor can input client texts into an AI tool without explicit permission. Since the providers of the three tested tools are headquartered in Germany, they comply with the requirements of the GDPR. Furthermore, it makes sense to take a close look at which LLMs are used and how client texts are handled. Even after an extensive search, I could only find the general privacy policy for the website regarding LiSA. Narratiq explicitly explains on its privacy-ai page how manuscripts are handled. According to information on the homepage, Scribigo currently uses LLMs from Anthropic, OpenAI, and Mistral without using them for training purposes; documents are deleted after 30 days.

It remains to be seen how AI will evolve as a tool for editing and self-publishing. There is no stopping AI tools from becoming established, in one form or another, beyond mere research purposes. Striking a balance between responsible handling of copyright and data protection on the one hand, and technical possibilities on the other, remains crucial.