AI automation with OpenClaw
AI agents that run on your own infrastructure.
Hand repetitive work over to software – but keep it traceable, reviewable and in your own hands. Built with OpenClaw, an open-source agent platform I run in daily operation myself.
What this is about
Not AI for its own sake, but the tasks that quietly cost time every week.
AI automation here means one thing: an agent handles a clearly defined task, repeatably and on the record. It reads out data, pre-sorts enquiries, produces reports, checks systems, prepares texts or connects tools that previously did not talk to each other. What matters is not the model but the process around it: what the agent is allowed to do, what it is not, where things are logged and at which point a human still decides.
So the starting question is always the same: which work is repetitive, describable and noticeably time-consuming? Everything else comes later – or not at all.
OpenClaw
An open-source agent platform – the technical core of this service.
OpenClaw is an open-source platform for AI agents: the code is public, the operation is yours, and nothing is a black box. An agent receives a clear assignment, a defined set of tools and a bounded area of access. Everything it does can be reviewed afterwards.
The decisive difference from ready-made AI services: OpenClaw runs on your own machine or on one I maintain for you. The platform, its configuration, the logs and the data stay where they belong. Which provider supplies the language model is a deliberate choice – and it remains replaceable rather than hard-wired.
Open source
The code can be inspected and audited. You do not have to rely on a vendor’s assurances; you can check what actually happens.
Self-hosted
OpenClaw is installed and operated on your own infrastructure – an in-house server, a dedicated VM or an environment I maintain.
Clear boundaries
Every agent gets exactly the permissions its task requires. Critical steps are only carried out after explicit approval.
Traceable
Tasks, tool calls and results are logged, so it stays possible to reconstruct why an agent did something.
Adaptable
Agents, tools and workflows are tailored to your processes instead of forcing your processes into a rigid product.
No lock-in
Because the platform and its configuration stay with you, switching remains possible – technically and commercially.
From my own practice
I run several OpenClaw agents in everyday operation.
What I offer, I use myself first. Several OpenClaw agents run permanently in my own environment: a coordinating main agent plus specialised agents for system administration, data tasks, security checks and editorial work. They monitor servers, prepare analyses, document each step and ask before touching anything critical.
That operation is where the most valuable part of the experience comes from: where agents genuinely take work off your hands, where they are overestimated, which safeguards are necessary, how failures become visible, and what it really costs to keep such a setup running. You get that assessment before implementation – including when it argues against a project.
Services
From the first assessment to ongoing operation.
Opportunity review
Going through which workflows are suited to automation – and which are better left with people.
OpenClaw setup
Installation, hardening and configuration on your own infrastructure, including access rights, logging and backups.
Agents & tools
Tailored agents with defined assignments, connected to your existing systems, files and interfaces.
Automated workflows
Recurring tasks run on a schedule or on events, with status reports and approvals at the right points.
Support & operation
Monitoring, updates, adjustments and a contact person when something does not behave as expected.
Documentation & training
Every setup is documented and handed over so your team understands it and can keep running it without me.
How it works
Start small, judge honestly, then expand.
Limits
What AI automation does not do.
Agents make mistakes, and language models occasionally invent things. So: no automation without a checkpoint, no critical action without approval, and no processing of sensitive data before it is clear what goes where. Where a workflow occurs too rarely, varies too much or is legally delicate, I will advise against it – that is more honest than a project nobody ends up using.