Efficient editorial workflows with Language Central

Manuscript assessment for
language quality, AI-assisted.

Accurate assessment of
language quality

Language Central assigns a language quality score to manuscripts to determine the most optimal editing workflow for your content.

Significant cost savings

With close to zero time spent on manual assessing of language quality, one publisher has seen a net annual saving of $500,000.

Outperforms language skills of all other tools

A thorough study of the most popular grammar tools puts Language Central right at the top, as it is trained specifically for scholarly content.

Ideal editorial workflows with ideally-paired editors

By predicting the quality of the language of the manuscript to a very high degree of accuracy, Language Central helps journal editors map papers to the right copy editors swiftly, so every article gets the attention it needs.

Built on a convolutional neural network

Language Central leverages deep learning models and linguistically informed rule-based systems to evaluate content based on sentence structure, parts-of-speech components, text sequences, spellings, and word similarity patterns on a sentence level.

Granular decision-making, exceptional efficiency

Move from a journal-level to an article-level workflow, assigning articles within a single journal to different copy editors based on the level of intervention required.

Scalable for diverse publications

Language Central is built for scalability. Our customers process both journal articles and book chapters via Language Central, plugging it into copy editing workflows for their entire catalogue of publications.

What our clients are saying

“Elsevier was looking for a solution to improve the quality of copy editing by matching the manuscript to a copy editor with the best skills. Language Central was piloted for 6 months and showed tremendous potential where its ML models accurately predicted the quality of language and therefore the level of intervention needed. This has not only improved the quality of our products, but has also led to greater efficiency in our production process.”