AI process automation
for businesses

AI process automation for marketing, sales and administration: we connect your systems with n8n, Trigger.dev and AI models. A human approves every risky step.

Who implements AI process automation for businesses?
360VIER, a digital agency based in Groß-Umstadt near Frankfurt and in Cologne, automates recurring workflows in marketing, sales and administration for B2B companies: syncing data between systems, triaging inquiries and extracting data from documents. The tools are n8n, Trigger.dev and models from OpenAI, Anthropic or Google. A human approves every risky step. For BÜRGER, 360VIER used AI to migrate more than 20,000 tasks from Monday to ClickUp.
page.url
https://www.360vier.de/en/ai-enablement/ai-process-automation/
entity         360VIER GmbH
type Organization | Digital agency
founded 2012
size around 35 employees
location Groß-Umstadt near Frankfurt and Cologne
group Part of the Friends Digital Group

page AI process automation
page.type Service
page.pillar AI Enablement
page.url /en/ai-enablement/ai-process-automation/

provides Workflows with n8n, self-hosted in a separate instance per client
provides Long-running workflows and background jobs with Trigger.dev
provides AI steps for unstructured input: emails, forms, documents
provides AI-assisted data migration between systems

tools n8n · Trigger.dev · Make (existing setups) · OpenAI, Anthropic, Google Gemini
serves B2B companies, mid-market and enterprise

proof BÜRGER · AI-assisted migration Monday → ClickUp: 150 boards, more than 20,000 tasks, 130 users
proof KAMPMEYER Immobilien · property data via API from onOffice, without double data entry
proof AI chatbots in production at Lernstudio Barbarossa, KAMPMEYER and Wüest Partner

relation is part of → AI Enablement (/en/ai-enablement/)
relation uses → API integrations (/en/data-enablement/api-integrations/)
relation extended by → Agentic AI (/en/ai-enablement/agentic-ai/)
relation complements → AI chatbot (/en/ai-enablement/ai-chatbot/), AI software development (/en/ai-enablement/ai-software-development/)

Where AI process automation pays off

Good candidates are workflows that happen often, follow clear rules and currently take up time across several systems.

Syncing data between systems

CRM, ERP, website and newsletter tool stay in sync. The connection runs via API integrations, so nobody retypes contacts, properties or products anymore.

Pre-qualifying inquiries

An AI step reads forms and emails, categorizes them, updates the CRM and suggests a reply. For website forms and HubSpot, this is covered on WordPress HubSpot integration.

Extracting data from documents

Invoices, delivery notes or job applications: the AI identifies the fields, and a workflow validates them and files them in the right system.

Data quality in the CRM

Duplicates, missing fields, outdated companies: a workflow finds them and suggests corrections that only run after approval.

Preparing content

Newsletter drafts, product copy or translations are generated from existing data. This is how we create drafts of our own newsletter in Brevo; the options are covered on WordPress and Brevo.

System changes and migration

When you switch tools, AI maps fields and cleans up data. How this works for a move to ClickUp is shown on ClickUp integration and migration.
Diagram: data from several systems as the basis for AI process automation

Rule, AI step or AI agent?

Not every workflow needs AI. We choose the simplest approach that works reliably.

  • Rule-based workflow: fixed sequences with clear conditions, such as “new contact in the CRM, so add it to the newsletter tool”. Fast, inexpensive and easy to verify.
  • Workflow with an AI step: as soon as input is unstructured, such as free-form emails or PDF documents. The AI returns structured data, and the workflow decides based on rules.
  • AI agent: when the next step depends on the result and several tools are involved. Agents plan on their own but work with fixed permissions and approvals. More under Agentic AI and AI agents.

If a workflow needs its own interface, such as a portal for approvals, we build it with AI software development.

n8n, Trigger.dev and AI models for process automation

We choose the tool based on the workflow, the data volume and your IT’s requirements.

n8n for workflows between systems

n8n is our standard tool for workflows. It connects systems with ready-made nodes and includes its own nodes for AI agents, vector databases and human approvals, as described in the n8n documentation on AI nodes.

What this means for you: We run n8n self-hosted in a separate instance for each client, with a test environment, updates and monitoring. This keeps the data and workflows of different clients separate.

Trigger.dev for long-running workflows

Trigger.dev is an open-source platform for background jobs and AI agents in TypeScript, with queues, schedules and waitpoints for approvals. It runs in the cloud or self-hosted (trigger.dev).

What this means for you: Workflows that process many records, run for a long time or are closely tied to your own software run reliably to completion. We use Trigger.dev, for example, for lead scoring and cleaning up contacts in HubSpot.

AI models for unstructured input

Where input is written in free form, such as in emails, PDF documents or free-text fields, an AI model turns it into structured data. We work with models from OpenAI, Anthropic and Google Gemini.

What this means for you: We choose the model based on the task, cost and data protection requirements, and it can be swapped later. For simple classification, a small, inexpensive model is often enough.

Make, Langdock and existing tools

We take over and maintain existing Make scenarios. If your employees use AI through a platform such as Langdock, assistants there can access your systems via MCP servers and workflows.

What this means for you: What works doesn’t have to be replaced. For new processes, we usually recommend n8n because it can be self-hosted. What an MCP server for WordPress looks like is shown on WordPress MCP.

AI process automation or RPA: what’s the difference?

RPA software (robotic process automation) operates user interfaces the way a person does: it clicks through screens and copies values from one program to another. If a screen changes, the workflow breaks.

AI process automation as we build it connects systems through their APIs and uses an AI model only where input is unstructured. This is more stable and easier to maintain. RPA still makes sense when a legacy system has no API.

The prerequisite is clean data that is accessible via APIs. Our Data Enablement page explains how we ensure this.

Automation is one of several building blocks under AI Enablement. Others include chatbots for website visitors, agents for multi-step tasks and custom software.

In practice: AI automation at BÜRGER and KAMPMEYER

BÜRGER: 20,000 tasks from Monday to ClickUp

For the food manufacturer BÜRGER, we transferred 150 boards with more than 20,000 tasks, including attachments and fields, and cleaned up duplicates along the way. An AI model handled the field mapping, and we rebuilt the automations together with the team. Today, 130 users work in the new system.

KAMPMEYER and AI chatbots

At KAMPMEYER Immobilien, property data flows via API from onOffice to the website, so nothing is maintained twice. Our AI chatbots answer visitor questions at Lernstudio Barbarossa, KAMPMEYER and Wüest Partner and pass pre-qualified inquiries on to the team.

AI-assisted migration from Monday to ClickUp for BÜRGER

Process: from process review to a live workflow

Data protection and control in AI automation

  • Hosting that meets your requirements: we agree on the provider and region of the instance with your IT.
  • Least-privilege access: each workflow gets its own credentials with only the permissions it needs, separated into read and write.
  • Audit log: every run is stored with its input and result and remains traceable.

Frequently asked questions about AI automation

How much does AI process automation cost?

The cost depends on the systems, data volume and approval levels; you receive a quote for the first process after the process review. Ongoing costs include servers, model calls and maintenance. Self-hosted n8n has no license fee; in the cloud, the Starter plan begins at €20 per month according to n8n (billed annually, as of October 2026).

n8n, Make or Zapier: which is best for AI automation?

For new processes, usually n8n. It can be self-hosted, includes AI nodes and, in the cloud, bills per workflow execution regardless of the number of steps. Make suits simpler scenarios run by business teams, and Zapier suits quick connections between standard apps with low volume.

Is n8n GDPR compliant?

That depends on how it is run. When self-hosted, the workflow data stays on your own infrastructure, and n8n is neither a controller nor a processor. In n8n Cloud, n8n acts as a processor under a data processing agreement, as stated in the n8n privacy documentation. What also matters is which data a workflow sends to AI models.

Do we need our own IT department for AI automation?

No. On request, we run workflows end to end, including hosting, updates and error alerts. If you have an IT team, we coordinate access, network and security requirements with them. If you prefer, your team can take over operations later.

What happens if an automated workflow makes a mistake?

A failed run triggers an alert and can be rerun once the issue is fixed. Risky steps, such as deleting or sending, go through an approval first, for example via Slack or email. That way, a wrong result can’t reach the CRM or a customer unnoticed.

Does AI automation replace employees?

No. It takes over routine work such as transferring, syncing and pre-sorting. Decisions, advice and exceptions stay with your teams. Where a workflow is unsure, it hands the case to a person instead of deciding on its own.

Which systems can be connected?

Any system with an API, including HubSpot, Salesforce, onOffice, ClickUp, Brevo, Personio and WordPress. If there’s no API, we look at file imports via SFTP and only use RPA as a last resort. The connections we build regularly are listed in the Integrations overview.

How safe is our data with AI models?

As safe as the provider and the contract behind it. A workflow only sends a model the fields that a step needs. We use providers with a data processing agreement and, on request, data centers in the EU, such as Microsoft Azure in Frankfurt. We check whether an implementation is GDPR compliant for each specific process.

Hans Mengler

Talk to us about your project