Workflows that run, not just planned.
We automate recurring work with and without AI. From email triage to accounting. Securely designed, operated in compliance with GDPR, and productively in use.
Four building blocks with which we introduce automation.
Most automation projects fail not due to the model or tool, but due to unclear use cases and lack of integration.
Strategy and use case definition
We start with joint workshops to find the right use case. Clearly defined instead of a solution that is supposed to do everything at once.
Architecture and setup
Suitable automation approach for the use case, depending on requirements with or without AI agent. Identities, permissions, logging, and sandbox considered from the start.
Security hardening
Each automation only gets the rights it really needs, every step is logged. Before going live, we actively test where vulnerabilities can be found.
Rollout & scaling
Start small, then roll out. What has proven itself will be transferred to other areas and use cases.
AI that fits in, instead of standing out.
Automation works best when it does not feel like a foreign body. We connect to your existing systems instead of creating new islands.
Existing software remains at the center
The automation runs where your team is already working. In the email inbox, in the accounting tool, in the ticket system.
Subconscious integration possible
Where sensible, the AI runs in the background, for example through our own AI Suite directly in the CMS, without a separate tool that your team has to learn first.
Data retention according to your specifications
Cloud, on-premise, or locally hosted. We choose the infrastructure based on data protection requirements, not trends.
Maintainable and traceable
Each automation is documented, built in a traceable manner, and fully handed over. No special tool that only we understand, but a system that your team supports.
What we have already automated.
Three examples from ongoing customer projects, exemplary of what can be automated.
Automated Email Drafts
Incoming inquiries are analyzed, suitable response drafts are prepared. The team reviews and sends, eliminating the initial draft.
Document Management in Accounting
Receipts and invoices are automatically read, categorized, and directly transferred to the accounting software (e.g., Lexoffice).
Log Analysis and Clustering
Large amounts of log data are automatically grouped, and noticeable patterns are filtered out, instead of the team searching manually.
Six topics for secure AI & automation.
Recognizing manipulated inputs
Inputs can be intentionally designed to mislead the AI into incorrect behavior, either directly by the user or hidden in documents and emails. We separate sources cleanly and check inputs before they are processed.
Controlled actions
Each automated action only gets the permission necessary for that specific step. This way, a gap cannot lead to full access.
Own identity per workflow
Each automation has its own identity with clearly defined rights. No shared access, no inherited permissions.
Controlled data flow
Automated processes may only communicate with explicitly permitted targets. This prevents data from being leaked unnoticed.
Seamless traceability
Each action is logged with input and decision, unchangeable. In case of doubt, it can always be traced what happened.
Ongoing security tests
Instead of a one-time check, we continuously test whether the automation can be tricked or abused, and close any gaps found.
What AI and automation has proven in practice.
Sales and CRM
Lead qualification, proposal preparation, prospect research. The agent documents directly in the CRM.
Support and service
Ticket triage, response suggestions from the knowledge base. Complex issues go to humans.
Back office and data maintenance
Master data maintenance, duplicate detection, import from invoices, orders, and contracts.
Content and marketing
Research briefings, headlines, SEO cluster analysis, social adaptations. The editorial team remains in control.
Development and IT ops
Code review preparation, bug triage, deployment preparation: connected to repos, ticketing, and monitoring.
Frequently Asked Questions about AI and Automation Projects
How do we start if we don't have a concrete use case yet?
With a situational assessment. We will look together at where AI can really save time in your processes and prioritize based on effort and impact before anything is developed.
Will our data remain in Europe?
Yes, upon request. We rely on GDPR-compliant models and European infrastructure, and for sensitive data, also on locally hosted models.
Can we further develop the automation ourselves?
Yes. We build workflows visually and transparently, document clearly, and train your team so that you are not dependent on us.
What does such a project cost?
That depends on the use case. We start with a clearly defined first step that shows quick results, rather than a monster project.