Summazer is the free app for summarising a text or a web page by highlighting the sentences with the highest information content. "Summazering" a text is very simple: just enter or paste the text or the address of the page, select the language (in addition to English it supports texts in: German, Spanish, French, Italian, Russian, Arabic, Chinese and many other languages) and the desired synthesis percentage. Summazer also performs spell-checking, grammar and morphological analysis to obtain - highlighted - the most important sentences, where the size of the characters is proportional to their semantic relevance.

Abstrazer is the free app to generate an automatic abstract of an article or web page. To obtain the abstract of an article or a thesis, simply enter/paste the text of the article or the address of the web page where it is published and select the language (in addition to English, it supports texts and websites in: German, French, Spanish, Italian, Russian, Arabic, Chinese and many other languages). You will immediately get an extract of the processed text with the most semantically relevant sentences.

the web application for the automatic extraction of the keywords (tags) and the most salient sentences contained in a plain-text or web page. To extract keywords and keyphrases from a text/hipertext, therefore, enter the text or the page URL, select the language (supports texts and websites in: English, German, Spanish, Italian, Russian, Arabic and many other languages) and the desired granularity. You will immediately get the tables of keywords and the most important phrases with its saliency score. It can order the results by saliency score or reading order.

Clustezer: the app for the automatic extraction of the main topics of a text or web page through the auto-classification of the keyphrases contained in the text. To obtain the summary of topics and related keyphrases, enter the text or the address of the page to be processed, select the language (the app supports texts and websites in: Italian, English, German, Spanish, Russian, Arabic and many other languages) and the number of expected topics (clusters). You will get the summary of the topics with the relative sets of related phrases found in the processed text.