AI Integration and Process Automation | RAG, n8n, OpenAI

Does this sound familiar?

If any of these are true for you, we can help.

You enter the same data into several systems by hand.

Processing incoming emails and questions eats a lot of time.

You extract data from invoices and PDFs manually.

Company knowledge sits in documents, but nobody can find what they need.

You use several tools that are not connected.

You want to use AI but do not know where it would actually pay off.

Handling repetitive workflows by hand is time-consuming and error-prone. And AI on its own solves nothing: it is worth something when it makes a specific business process faster, cheaper or simpler.

So we do not build a separate AI product; we fit it into your existing systems and processes. We look at where most of the manual work goes, and automate that first.

Typical examples: processing incoming customer questions and drafting replies, extracting structured data from PDFs and invoices, natural-language search over company documentation (RAG), or routing data automatically into a CRM or email.

The result: fewer errors, less administration and more time for real value creation.

What we can take on

Concrete work we do in this area.

Integrating OpenAI, Claude and other AI models
Building AI features into an existing web system
Document processing and structured data extraction
Internal AI search and RAG (Retrieval-Augmented Generation)
Customer support AI and chatbots
Designing and running n8n, Make and Zapier workflows
Connecting CRM, email and invoicing systems
API and webhook integrations, data synchronisation
Replacing manual administration

What you get

Not just code, but a working system you can keep building on.

01

A process review: where most of the manual work goes.

02

A working automation in production, with monitoring.

03

Documented workflows that you can modify yourselves.

04

A cost estimate for AI calls, so there are no surprises.

05

Error handling and alerts when a process gets stuck.

06

A measurable result: how much time was freed up.

How we work

Four steps from the first conversation to handover.

1

We understand the problem

We go through the current situation, the business goal and the technical environment.

2

We propose a solution

We define the approach, the development needed and the expected effort.

3

We build

The system is built transparently, with version control and continuous communication.

4

Handover and beyond

You do not need to find a new developer after handover: we also take on maintenance and further development.

What we work with

Technology is not the message, it is the professional background.

OpenAI API Claude API n8n Make Zapier Laravel Vector DB REST API

Frequently asked questions

What most people ask before we start.

Not always. That is why we start with a process review: we look at where most of the manual work goes and estimate the return. If it is not worth it for a given process, we say so.

With the right setup, yes. We use business APIs where data is not used for model training, and we decide what leaves your system at all. For sensitive data we anonymise or propose a locally hosted solution.

RAG means the AI answers from your documents rather than general knowledge. It helps when you have a lot of internal material (policies, documentation, contracts) and want to search it in natural language.

It consists of the workflow tool subscription and usage-based AI call fees. Before rollout we estimate the expected monthly cost and build in limits so it cannot run away.

We build in error handling and alerts, so it does not fail silently. Critical processes always have a manual fallback.

Let's talk about your project

Tell us briefly what you are working on and where you need help. We will look at how we can get involved.

Let's see what can be automated

AI and Automation