Clam: A secure OpenClaw AI sidekick with a fully customizable UI

Hey ProductHunt!

We've been using Zapier, Make, n8n for years. They're great until things get one step too complex. Maybe the workflow runs fine for a few weeks, then an API changes and the whole thing breaks silently. Now you're back in the drag-and-drop builder debugging node #14 at midnight.

We wanted something more autonomous, so we built Clam.

OpenClaw as a manager, not a worker

Under the hood, Clam runs on OpenClaw. We’ve connected it to 800+ tools, including iMessage and web browsing.

But we found the best use case for OpenClaw is managing automations, and not doing the automations itself. You tell Clam what you need, and OpenClaw writes the python files, tests them, keeps them running, and fixes them when they break.

Why not just let the agent do everything end to end? Because that's slow, expensive, and unreliable. If OpenClaw runs your entire workflow through the LLM every time, you're burning tokens on tasks that should be deterministic.

Pulling issues from Linear, formatting a Slack message, posting to a channel. That's just code. It doesn't need an LLM in the loop every run. Worse, without a programmatic codebase, the agent might handle the same task slightly differently each time.

Clam’s AI steps in when something needs to change, something breaks, or you have an ad-hoc task come up (like texting your bot to fetch some information you need).

Dynamic UI

Clam builds you an interface based on what you want to see or what your AI wants you to see. Just tell it how you want the dynamic UI to work and it’ll simply start operating that way.

When your workflows produce data, Clam generates pages with tables, charts, stat cards, and layouts tailored to what you're looking at. You don’t have to scroll through workflow execution logs anymore, since whatever you want to see is top of page.

The power problem

That same power is exactly what makes OpenClaw dangerous to hand the keys to. An agent that can execute arbitrary code can execute *malicious* code. An agent with access to your API keys can leak them. An agent reading your messages can be tricked by a prompt injection into forwarding them somewhere else.
So we built Clam with the management and safety layer on top of OpenClaw. You get all of that power, but contained.

Security

Each user gets an isolated OpenClaw instance in its own VM. A network-level proxy sits on the VM boundary and intercepts all traffic in and out of the agent. It scans for PII, leaked credentials, prompt injections, and malicious code patterns before anything gets forwarded. The agent can't see the firewall, can't address it, and can't prompt-inject its way past it.

All credentials live on the network layer as well, so the bot can’t see them.

Who is this for?

If you’re on your computer ever doing repetitive tasks, Clam can probably help you save time by becoming the control plane for such tasks!

Would love to hear what you think. We're in the comments all day.