Self-Host Your Own Workspace for Building and Managing AI Agents

You've probably played with AI agents in one form or another—a chatbot here, a workflow builder there. But once you want to move past demos and actually deploy something you control, the options get thin fast. Sim is an open-source workspace for building, deploying, and managing AI agents and workflows, and you can run the whole thing yourself.

What It Does

Sim bills itself plainly as "a workspace to build, deploy and manage AI agents and workflows." That's the core of it: a place to assemble agents, wire them into workflows, and then run and monitor them rather than leaving them as one-off experiments. The README frames the product around four phases—integrate, context, build, and monitor—so the intent is to cover the full lifecycle, not just the canvas where you drag things around.

You've got three ways to get it. There's a cloud-hosted option at sim.ai if you just want to try it. There's a self-hosted path, which is the interesting part for anyone who wants their agents and data on their own infrastructure. And there's a desktop app for macOS (12+, both Apple Silicon and Intel), which you can point at a self-hosted deployment if you want a native client on top of your own stack.

The self-hosted setup runs on Docker Compose. The production compose file spins up the services, and there's a separate compose file with an Ollama profile if you want to run local AI models instead of relying on hosted providers.

Why It's Cool

• Self-hosting is a first-class option, not an afterthought. The README leads with a one-line setup command (npx sim-setup) and also documents the full manual Docker Compose path. Having both means you can go from zero to running without reading a wall of docs, or take the manual route if you'd rather see exactly what's being deployed.

• You can run it against local models. The Ollama compose profile is a genuinely useful detail. If you're building agents and don't want every inference call leaving your network, the project gives you a documented path to keep models local.

• The setup friction is acknowledged and handled. The manual instructions are explicit that the stack won't start without generated secrets—auth secret, encryption key, internal API secret, cron secret, and a Postgres password. It's the kind of thing that trips people up silently, so spelling it out (complete with openssl rand commands) saves you a confusing debugging session.

• There's a Cursor-assisted setup flow. The README includes a "Set Up with Cursor" link that hands your editor a full step-by-step prompt—verify Docker, clone the repo, generate secrets, start the stack, wait for health checks, troubleshoot common issues. It's a small thing, but it's a smart way to meet developers where they already work.

• The honest system requirements are refreshing. The troubleshooting notes call out that you'll need 12GB+ of RAM and that ports 3000 or 3002 may already be in use. Projects that tell you the bad news upfront tend to save you time.

• A desktop client that talks to your own backend. Pointing the macOS app at a self-hosted deployment is a nice split: your infrastructure, your data, but a proper native interface instead of a browser tab.

How to Try It

The fastest route is the self-hosted one-liner:

npx sim-setup

If you'd rather do it by hand, the README walks you through the Docker Compose approach. You'll need Docker installed and running first, then:

git clone https://github.com/simstudioai/sim.git
cd sim

Generate the required secrets (the stack won't start without them):

cat > .env << EOF
BETTER_AUTH_SECRET=$(openssl rand -hex 32)
ENCRYPTION_KEY=$(openssl rand -hex 32)
INTERNAL_API_SECRET=$(openssl rand -hex 32)
CRON_SECRET=$(openssl rand -hex 32)
POSTGRES_PASSWORD=$(openssl rand -hex 24)
EOF

Start the services and wait for the containers to report healthy (give it a minute or two):

docker compose -f docker-compose.prod.yml up -d
docker compose -f docker-compose.prod.yml ps

Then open http://localhost:3000. If you want local models via Ollama, use the Ollama compose file with the setup profile instead. And if you'd prefer the guided route, the Cursor link in the README walks an AI assistant through the whole thing, including troubleshooting port conflicts, Docker not running, and memory shortfalls.

You can find the repo at github.com/simstudioai/sim, with docs at docs.sim.ai.

Final Thoughts

Sim is aimed at developers who want agent-building tools without handing their stack to a vendor—and who are comfortable running Docker Compose. The 12GB RAM requirement and multi-service deployment mean it's not a lightweight weekend toy, but the documented setup paths (one-liner, manual, Ollama-local, Cursor-assisted) show the team has thought about where people get stuck. If agent workflows are part of your roadmap and self-hosting is a requirement rather than a preference, this is worth a look before you build your own internal tooling.

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