> For the complete documentation index, see [llms.txt](https://docs.ilert.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ilert.com/ai-and-agents/ai-features.md). # AI Features The AI features built into everyday ilert workflows, and how to turn the ones using external models off. AI Features use contextual understanding, external or ilert-hosted large language models (LLMs) to enhance common workflows in ilert.

Feature	Description	LLM usage type
Intelligent alert grouping	Automatically groups related events using semantic similarity to reduce noise.	Self-hosted
Schedule generation	Builds recurring schedules from a chat interface	External LLM
Status update generation	Drafts status update messages and status page posts based on ongoing incident context.	External LLM
Post-mortem generation	Generates incident post-mortems using alert timelines, notes, and status updates.	External LLM
Global search	Semantic search across alerts, incidents, services, alert sources, schedules, escalatio policies, ...	Self-hosted

{% hint style="info" %} AI features that use **external LLMs** can be turned off globally in the [account settings](/ai-and-agents/introduction.md#model-endpoints-and-data-residency). {% endhint %} --- # 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://docs.ilert.com/ai-and-agents/ai-features.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.