I design, build, and ship agents for marketing, sales, and operations: research, enrichment, outreach drafts, monitoring. They run in your own tools, and your team approves what goes out.
We choose the repetitive job that costs the most time. One workflow, one clear definition of done.
02
Map it and build
I map the steps, data, and approvals, then build the agent in your tools: n8n, OpenAI or Anthropic, your CRM.
03
Test on real data
The agent runs on your real inputs with a person approving every output until the results are right.
04
Hand over and run
You get the source, a setup video or handover session, and docs your team can maintain.
FAQ
Questions, answered
Which one should we start with?
Start with Marketing Agents if you have one clear, repetitive marketing job and want to see an agent working within a week. Choose the AI Agent Sprint when the workflow touches several systems or teams and needs scoping first.
Will the agent send things without us?
Not unless you decide it should. Every step that sends a message or changes data waits for a person to approve it. You can loosen that later, once you trust the output.
Which tools do you build with?
n8n or Make for the workflow, the OpenAI or Anthropic APIs for the model, Custom GPTs or Claude Projects for simple assistants, and Supabase with a small React app when an agent needs its own interface.
Is our data safe, and is it GDPR-compliant?
Agents run in your own accounts where possible, and I use API access, where OpenAI and Anthropic do not train models on your data by default. We sign a data processing agreement, and I prefer EU hosting for n8n. Have your data protection officer review the final setup.
What does it cost to run?
Model and hosting costs depend on volume. I estimate them in the scoping call and design the agent so the monthly cost stays predictable.
What happens when our process changes?
You get the source code and documentation, so your team can adjust the agent. I can also maintain it for you; we agree the details at handover.