> For the complete documentation index, see [llms.txt](https://public-docs.anvilogic.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://public-docs.anvilogic.com/welcome-to-anvilogic.md). # Welcome to Anvilogic What is Anvilogic? Anvilogic is an AI SOC solution and multi-data platform that enables detection engineers and threat hunters to detect, hunt, and investigate seamlessly across disparate data lakes and SIEMs without the need to centralize data, learn new languages or deploy new sensors. **Anvilogic empowers enterprise SOCs to rapidly mature their detection programs with a dual approach: instantly deployable, curated detections and a powerful low-code builder for crafting correlated custom alerts.** With thousands of expert-built detections ready to deploy in a single click, teams can accelerate threat coverage from day one. Anvilogic’s platform also features automated workflows and AI-driven insights for tuning, triage, maintenance, and critical alert escalation—helping SOCs hunt threats with greater speed and precision. Real-time SOC maturity scoring gives teams continuous visibility into their detection posture, mapped against their most critical threats. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://public-docs.anvilogic.com/welcome-to-anvilogic.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.