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AI automation and MCP

AI automation that does the busywork, safely.

We connect AI models to the tools you already use, so the steps where someone reads, decides and types it somewhere else run on their own. A person still checks anything that matters.

An automation flow: an email comes in, the AI step reads it, and a person approves the action

Sound familiar?

Where this usually starts

What we build

What you get

How we work

From brief to running system

  1. 1

    Map the workflow

    Every step, system and decision, including the exceptions people handle from memory.

  2. 2

    Shadow mode first

    The AI's output is logged and compared with what your team did, before it acts.

  3. 3

    Approval, then autonomy

    It acts with a person approving each step. Approval comes off only for actions with a clean record.

  4. 4

    Least access, full logs

    Each connection gets only the data and actions it needs, and every call is logged.

From the blog

Read before you decide

All AI Automation posts

Questions people ask

What is MCP and do I need it?

MCP (Model Context Protocol) is an open standard for connecting AI models to tools and data. You don't need to know it exists, but building on it means your automations keep working when you switch AI models.

Will the AI make changes without anyone checking?

Not at first. Every automation starts in shadow mode, then runs with a person approving each action. Anything that moves money, deletes data or talks to a customer keeps a human check.

Which tools can you connect?

Anything with an API, plus most databases and file stores. Common ones are CRMs, email, accounting tools, Google Workspace, Slack and automation platforms like n8n or Zapier.