> For the complete documentation index, see [llms.txt](https://docs.hexabot.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.hexabot.ai/introduction/overview.md). # Overview Hexabot is an open AI automation platform for building and running agentic workflows across channels. It helps teams automate conversations, tasks, and recurring operations in one place. Start with a simple workflow, then expand with actions, bindings, memory, channels, and AI features. ### What you build with Hexabot Hexabot is workflow-first. You define how an automation starts, what steps it runs, and what results it produces. This makes Hexabot useful for customer experiences, internal tools, and background jobs. Hexabot supports three workflow types: * **Conversational** — for assistants, support flows, and guided interactions * **Manual** — for tasks started on demand by a user or operator * **Scheduled** — for recurring jobs, checks, and background automations ### Core building blocks Hexabot brings design, execution, and operations into one platform. * **Workflows** — define automation logic visually or in YAML * **Actions** — run tasks like messaging, data processing, and service calls * **Bindings** — reuse shared capabilities across workflows * **Memory** — keep useful context available across runs and interactions * **Channels** — run workflows where users already interact * **Runs** — inspect executions, debug issues, and improve reliability ### Built for teams and developers Hexabot keeps the product simple for operators and flexible for developers. * **Visual editing with YAML support** — use the editor for speed and YAML for precision * **Modern developer workflow** — work with the CLI and shared packages in one monorepo * **Flexible data layer** — start with SQLite and scale with Postgres * **Schema-driven configuration** — use typed settings and validation across the platform * **Open and self-hosted** — keep control of your infrastructure and data ### Why teams use Hexabot * **One platform** — design, run, and monitor automations in one place * **Flexible execution** — support conversational, manual, and scheduled work * **Extensible** — add actions, channels, helpers, and integrations as needs grow ### Explore next * [Features](/introduction/features.md) * [Workflow Editor](/workflow-editor.md) * [Create your 1st workflow](/quickstart/create-your-1st-workflow.md) --- # 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 dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.hexabot.ai/introduction/overview.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.