Text Generation: Pitch for a new product, slogan for marketing campaign, sales email, social media post, title for an article, and job description.

Conversation: Ask questions in natural language or submit text through documents and emails to the LLM, which will provide intelligent answers according to the text.

Data Extraction: Extract specific pieces of data from the whole text, such as dates or sums from a contract, insights or trends from data tables, and many others.

Summarization: Summarize long-form documents or any type of text, such as contracts, blog posts, documents, emails, articles, product reviews, and social media posts.

Classification: Text is classified into predefined categories, such as providing a list of support tickets; now, it will be classified by the department that handles them.

Style Transfer: The style or tone of the text can be changed by rewriting, rephrasing, and suggesting grammatical improvements.

Semantic Similarity: Evaluation of inputs similar in their meaning. For example, evaluate a list of questions and extract the most relevant answer given to similar questions in the past for a new question.