Agents & RAG

Build assistants that read your documents and take actions.

10 applicationssingle tenantfrom $11.99/mo
In short

AI agent hosting means running the framework that plans and executes tasks — Dify, Flowise, AnythingLLM, OpenHands and similar — on a dedicated instance with persistent storage, so agents keep running when your laptop does not and their memory survives a restart.

Agents and retrieval systems are the category where self-hosting stops being a preference and becomes a requirement. These tools hold credentials for other systems, index documents that should not be indexed elsewhere, and in several cases execute code. A shared SaaS workspace is the wrong shape for that; a single-tenant instance is the right one.

They also need to be long-lived. An agent with memory, a vector index built over a week of ingestion, a workflow that runs on a schedule — none of that survives on a developer machine. Persistent storage and an uptime commitment are most of what makes the difference between a demo and something a business relies on.

Questions

Straight answers

Which of these is closest to a finished product?
Dify, if you want workspaces, datasets and published apps with APIs. AnythingLLM if the job is document chat and you want it working this afternoon. Flowise and Langflow are builders rather than products — excellent for prototyping a pipeline.
Is it safe to run an agent that executes code?
On a single-tenant instance with authentication, yes — the sandbox is yours and no other customer shares it. What is not safe is an unauthenticated agent endpoint on a public URL, which our acceptable use policy prohibits.
Do agents need a GPU?
The frameworks do not. They call a model provider — yours, or a local runtime. GPU capacity only enters the picture if you want that local model to be fast.

Put your AI stack on your own box

Pick an app, pick a size, and have it running today. Month to month, cancel whenever.