Can I host Hexabot myself?

Yes. The product is positioned as self-hostable so teams can deploy it on their own infrastructure rather than a vendor cloud.

Which AI models does Hexabot support?

The platform integrates with multiple large language models, letting teams swap providers based on their own constraints.

Do I need to code to build flows?

The visual editor is designed for non-developers, with optional plugin extensions for engineers who need custom logic.

Is Hexabot open source?

Yes. The project is described as open source, which lets teams audit and modify the code before deploying.

Hexabot: Open-Source AI Chatbot Builder

What is Hexabot?

Hexabot is an open-source, self-hostable AI chatbot builder for teams that want to keep conversational data on their own infrastructure. The product is positioned as an AI workflow automation platform with a visual flow editor and support for multiple channels and large language models.

Why Hexabot works

Hosted chatbot tools force teams to send conversation logs and customer data to a third-party SaaS. Hexabot removes that constraint by letting teams deploy on their own infrastructure, while keeping a visual editor so non-developers can still design flows.

Hexabot features

Visual flow editor. Lets non-developers design chatbot conversations without writing code, while still exposing branching logic for complex flows.
Multi-LLM support. Integrates with multiple large language models so teams can pick the provider that matches their privacy and cost constraints.
Self-hosted deployment. Runs on the team's own infrastructure, addressing data residency and privacy requirements regulated industries usually have.
Plugin system. Extends the platform with custom plugins for integrations, channels, or business logic beyond the core feature set.
Multi-channel reach. Supports several messaging channels so the same flow can serve web chat and messaging apps without duplicate authoring.

Who Hexabot is for

Internal IT and platform teams at regulated companies that cannot send customer conversations to third-party chatbot SaaS.
Agencies building white-label chatbot solutions for clients who want full control over branding and hosting.
Developers prototyping LLM-backed assistants who want a visual editor on top of their own model and vector store choices.
Open source enthusiasts evaluating a self-hostable alternative to closed chatbot platforms before committing budget.

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