# Usage data ## General Logs are kept for the following types of usage, for invoicing purposes: * [**DeepL**](https://www.deepl.com) **translation requests**: user ID, timestamp and number of characters. The actual query and the answer returned by DeepL is not saved. * **LLM requests**, either with ClauseBase's key or with the customer's key: user ID, timestamp and number of tokens. * **OCR requests** (conversion of scanned PDF documents): user ID, timestamp, outcome (result or failure), error messages and number of pages. * **Exported documents** (DOCX or PDF): user ID, template number, template title, timestamp, number of pages, whether the end-user interface or instead the API was used, optional identifier given by the user and ID of the brower session. The content of the exported documents is not saved. ## ClauseBuddy On the basis of the data stored in the [central logging system](/data-collected/logging-data.md) each customer's administrator can request an overview of the usage of ClauseBuddy by each of its users. The administrator can get an overview of the following data: * Amount of clauses, templates, users and saved answers being created, updated and stored at a given moment. * Which clauses were most frequently inserted into MS Word documents by users. * How many times ClauseBuddy was opened by each user. * How many keyword-based searches and browse sessions were performed in ClauseBuddy's Quality Library. * How many AI-related requests were made.

Platform activities

In addition, administrators can check the time patterns of its users — i.e. at which times of the day that ClauseBuddy was used in the company, on a per-user basis. For privacy reasons, this usage is grouped per block of 15 minutes.
--- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://legal.clausebase.com/data-collected/usage-data.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.