Service
AI integration into existing systems and processes
We integrate large language models and other AI capabilities where they genuinely take work off your employees' hands: in your software, your CRM or ERP, your document storage. Privacy-compliant, measurable and without creating new silos.
Start a projectWhy many AI projects get stuck in the pilot phase
A chatbot is quick to build. It gets difficult when AI has to work with real company data, fit into existing processes and deliver reliable results. This is exactly where many pilot projects fail: because of missing interfaces, unresolved data protection questions or because nobody knows how good the results actually are.
That is why we do not start with the model, but with your process: which task should be done faster, cheaper or better – and is AI the right tool for it at all? Sometimes conventional automation is the better solution. If so, we will tell you.
What we build for you
Document processing
Incoming documents, e-mails and forms are classified automatically, relevant data is extracted and passed on to the right systems – with a review step where necessary.
Knowledge search across company data
Employees ask questions in natural language and get answers from manuals, contracts or tickets (retrieval-augmented generation) – with sources, so every answer can be verified.
AI features in your software
Summaries, draft texts, translations or intelligent search directly in your existing application, CRM or ERP – via clean interfaces instead of copy and paste into a chat window.
Model integration and operation
Selection, integration and operation of suitable models – with providers processing data in the EU or as an open-source model on your own servers – including monitoring of cost and quality.
Typical use cases
Quotations
Enquiries are read, matched against product and price data and prepared as a draft quotation that sales only needs to check and approve.
Customer service
Incoming requests are categorised, prioritised and enriched with suggested answers from your knowledge base.
Contract review
Contracts are checked for specific clauses, deadlines or deviations from the standard and summarised for the relevant department.
Internal knowledge
New employees find answers about processes, policies and products themselves instead of having to track down colleagues.
Data protection and security from the start
AI integration means processing company data. We therefore design your solution so that confidential and personal data stays protected – technically and organisationally.
- Providers processing data in the EU with a data processing agreement under Art. 28 GDPR – or open-source models in your own infrastructure
- Data minimisation: personal data is pseudonymised or removed before it reaches a model
- Your data is never used to train third-party models
- Permissions: the AI only sees data the respective person is allowed to access
- Logging, so that inputs and results remain traceable
How we work
1. Assess the use case
We analyse the process, the data and the benefit – and tell you openly if the task is better solved without AI.
2. Prototype with real data
A prototype is tested with your data. Together we define the quality level at which the use pays off.
3. Integration and safeguards
We integrate the solution into your systems, add review steps, permissions and logging, and document the data flows.
4. Operation and improvement
We monitor quality and cost in live operation and adapt models, prompts and data when requirements change.
Frequently asked questions about AI integration
Do we need our own training data?
In most cases, no. Language models are not retrained for this; instead they are given the relevant information from your data at runtime (retrieval-augmented generation). This is cheaper, faster to implement – and your data does not flow into a model.
Can we use AI in compliance with the GDPR?
Yes, if the choice of provider, the contracts and the data flows are right. We rely on providers processing data in the EU with a data processing agreement, or on open-source models in your own infrastructure, minimise personal data and support you with the documentation.
Which AI models do you use?
We work vendor-independently – with models from OpenAI, Anthropic and Google as well as open-source models. The choice depends on quality, cost and data protection requirements, and on where your data may be processed.
What does an AI integration project cost?
That depends on the scope: a prototype for a clearly defined use case costs considerably less than a company-wide solution. After an initial conversation you receive a transparent effort estimate; ongoing costs for model usage are shown separately.
What happens if the AI gives wrong answers?
We plan for this from the start: with sources, human review steps at critical points and tests with real cases before a solution goes live. In operation, we monitor quality continuously.
Do you have a specific use case?
Briefly describe your process. We will tell you honestly whether and how AI helps – and what it costs.