Manuscript assessment for language quality, AI-assisted.

Language quality scoring to help publishers assign the right levels of copy editing to manuscripts. Built on linguistically-informed rule-based deep learning models.

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.