# Factual memory **Factual Memory** Fact memory stores discrete pieces of factual data that are extracted from conversations or interactions. These facts are agnostic of time or context and are stored in a **vector database** (e.g., Pinecone) for efficient retrieval. When integrated with the Levia protocol's social media learning capabilities, this memory system: * Extracts and validates knowledge from social media platforms through NLP algorithms, cross-referencing with trusted sources * Maintains metadata about information acquisition time and verification status * Organizes facts hierarchically while preserving semantic relationships * Updates continuously through social media monitoring, validating new information against existing knowledge * Enables semantic search for contextually relevant information retrieval This architecture allows Levia to maintain current knowledge while ensuring information accuracy. --- # 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://leviaprotocol.gitbook.io/leviaprotocol/core-concepts/memory-management/factual-memory.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.