Yes—Grok can use real-time data from X (formerly Twitter), but it’s not as simple as “always streaming everything live.” In practice, real-time access is typically implemented as an on-demand retrieval step: when a query requires freshness, the system can search or fetch relevant X posts (and sometimes web/news sources) and then use that retrieved text as context for generation. Whether this happens automatically, and what sources are allowed, can depend on the product surface (X app vs grok.com vs API), your settings (search on/off/auto), and policy constraints (safe search, allowed accounts, region restrictions). So the accurate mental model is: Grok can incorporate live X posts when live search is enabled and available, but the model still generates the answer from a prompt + retrieved snippets, not from a magical always-on firehose.
For developers, this distinction matters because it affects reliability and evaluation. If you test Grok on the same prompt on different days, results can change because the retrieved “live” context changes. That’s expected behavior when freshness is part of the system. It also means you should log retrieval metadata if you need auditability: which posts were consulted, which handles were included/excluded, and what filters were applied. If you’re building with the API, you’ll typically have controls to specify whether live search is enabled and which sources it can use (X posts vs web vs news vs RSS). This is important for compliance and for reducing prompt-injection risk from untrusted content.
In production apps, you often combine “real-time public data” with “private authoritative data.” For example, you might want to answer: “What are people complaining about today, and what is our official policy response?” Live X retrieval can handle the first half, but the second half should come from your controlled documents. That’s where a vector database such as Milvus or Zilliz Cloud fits naturally: store your official policies, runbooks, and product docs as embeddings; retrieve the relevant sections based on the question; and provide those alongside any live X snippets. This split design lets Grok summarize real-time chatter while keeping your “ground truth” anchored in internal sources you can version and govern.