AI Integration & Automation
AI integration and automation for your business
We put AI to work where it takes real work off your team’s plate: documents, inquiries and repetitive processes. Every AI integration we build is planned around privacy, cost and reliability.
AI Integration & Automation
Language models can sort incoming email, extract data from invoices or answer questions about internal documents. The value comes from solid AI integration into the tools your team already uses, not from yet another chat window.
That’s why we start with your processes, not the technology. Together we look for tasks that come up often, follow clear rules and eat up a lot of manual effort today. We test AI on a small scale there first, then expand what proves itself in daily use.
Privacy is part of the design from day one. Depending on how sensitive your data is, we connect the latest models from OpenAI (GPT), Anthropic (Claude) and Google (Gemini) through their APIs in a GDPR-compliant way, with a data processing agreement and, where available, processing in European data centers. Alternatively, we use open-source models running on servers in Germany or on your own premises. The latter makes sense when your data shouldn’t leave the building at all. We work in English and German.
At a glance
Our AI integration services
AI assistants for your team
Assistants that answer questions from your own documents, manuals or product data, with a link to the source so every answer can be checked.
Document processing
Invoices, delivery notes, forms or contracts are read, checked and passed on as structured data instead of being retyped.
Workflow automation
Repetitive processes run on their own: routing inquiries, moving data between systems, drafting replies.
Integration with existing systems
We connect AI features to your current software, your email inbox or your customer portal through APIs.
GDPR-compliant GPT, Claude and Gemini
The right models and providers, EU hosting or local models, logging and clear rules for which data goes where.
Proof of concept
A limited test with real examples from your day-to-day work shows how well an approach performs before you invest in scaling it.
Typical use cases
Triaging the inbox
Incoming email and inquiries are sorted by topic and urgency and routed to the right person.
Capturing documents
Data from invoices and delivery notes lands in your system as structured records. Your team only reviews the exceptions.
Putting internal knowledge to use
Employees ask an assistant about processes, product data or policies and get an answer that points to the source document.
Drafting text
First drafts of proposals, product descriptions or answers to common questions that your team just reviews and adjusts.
How we approach AI integration
- < 24 h response to inquiries
- Fixed price
- We come to you in person
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Step 1
Free initial consultation
We talk through your processes and identify the tasks where automation would make the biggest difference.
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Step 2
Feasibility check
Using real examples, we test how reliably a model handles the task and settle questions of privacy, running costs and hosting.
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Step 3
Iterative integration
We build the solution into your tools step by step. Your team tests early, and we refine based on their feedback.
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Step 4
Operation and quality control
After launch we keep an eye on quality and cost, adjust instructions and switch to better-suited models when it makes sense.
Technologies we use
- OpenAI GPT (API)
- Anthropic Claude (API)
- Google Gemini (API)
- Local open-source LLMs
- TypeScript
- Node.js
- .NET / C#
- SvelteKit
- PostgreSQL
- MongoDB
- Docker
- Linux servers
- Hosting with Hetzner
FAQ
Frequently asked questions
Is using AI compatible with the GDPR?
It can be, if it’s planned properly. Up front we clarify what data is processed, whether personal data is involved and which provider fits under which contract. For sensitive data we use EU hosting or local models on servers in Germany. The legal assessment is yours or your data protection officer’s to make; we provide the technical facts it needs.
Will our data be used to train AI models?
According to OpenAI and Anthropic, data processed through their business APIs is not used for training by default. Their consumer chat apps follow different rules, which is why we use the APIs for client projects. When open-source models run on a dedicated server, your data never reaches an AI provider in the first place.
How reliable are the results?
Language models make mistakes, and we plan for that with clear instructions, automated sanity checks and human sign-off wherever errors would be costly. The proof of concept shows you in advance how well an approach works for your specific task.
What drives the effort and running costs?
Development effort depends on how many systems need to be connected, how varied your documents are and how accurate the results must be. After the free initial consultation, you receive a proposal with a fixed price for the agreed scope. Running costs come from model usage or from operating your own server and scale with data volume; we estimate those transparently after the proof of concept.
How soon will we see results?
A proof of concept focuses on a single task, so it comes together much faster than a full integration. How long the rollout takes afterward depends on the integrations involved, the quality of your data and how much coordination your team needs.
Do we need AI expertise in-house?
No. We handle selection, setup and operation, and we explain to your team how the solution works and where its limits are. In the Ruhr area and Düsseldorf, we’re glad to do that in person at your office, and video calls work too, in English or German.
More services
AI Integration & Automation in your region
Where could AI take work off your team’s plate?
Bring one concrete process to a free initial consultation. We’ll give you an honest take on whether AI helps there and what a small, low-risk test could look like.
- < 24 h response to inquiries
- Fixed price for the agreed scope
- We come to you in person