AI & Automation for processes that need to become faster, clearer, and better.
Concept development, UX/UI design, and development of AI-powered tools, automations, and assistance systems for businesses that want to streamline repetitive tasks, make better use of data, and make digital processes smarter.
We develop AI solutions not as experiments, but as practical tools: aligned with brand guidelines, controllable, easy to understand, and seamlessly integrated into existing processes.
Features & Integrations for Powerful AI and Automation Projects
When AI isn't meant to impress—but to help.
Many companies recognize that AI has potential. But there’s often a big difference between demos, tool hype, and real-world benefits. Individual employees test ChatGPT, teams develop their own workarounds, files are checked manually, content is created multiple times, and processes remain cumbersome nonetheless.
So the question isn’t: How can we somehow implement AI?
The better question is: Where, specifically, can AI make work easier, ensure quality, make knowledge actionable, or support decision-making?
That’s exactly where we come in. We develop AI-powered tools and automations for real-world use cases: brand-compliant illustrations, structured document analysis, intelligent search, assistance systems, content workflows, data preparation, and process support.
Not as a black box. But as a digital tool that supports people and makes results transparent.
AI is no substitute for strategy.
It needs a clear task.
A good AI solution doesn’t start with a model. It starts with a problem, a process, and a quality standard.
What needs to be faster? What information needs to be analyzed? What rules apply? What data can be used? Which results require review? And at what point do humans remain actively involved in the decision-making process?
For companies, this means that AI isn’t randomly thrown into everyday operations, but is strategically deployed where it measurably reduces the workload.
For teams, this means: less repetitive work, better templates, faster orientation, and more time for evaluation, decision-making, and creative output.
What matters is not just what AI produces. What matters is how well it is guided, limited, reviewed, and integrated into everyday work.
LLM and Prompt Systems
We develop structured prompt and system logic that guides AI applications in a targeted manner and aligns them with specific tasks, tones, rules, or brand requirements.
RAG and Access to Knowledge
With retrieval-augmented generation, internal documents, knowledge, policies, or data sources can be used as context to make answers more relevant and easier to understand.
OCR and Document Analysis
Documents, transcripts, certificates, or forms can be scanned, organized, and prepared for further processing.
Image and Illustration Generation
AI can support creative processes when style, brand, rules, and quality are carefully managed. This produces results that don't look random but instead align with the visual identity.
Brand Guidelines and Brand Logic
We translate brand guidelines, style principles, tone, visual language, and design logic into digital workflows so that AI outputs can be better controlled.
Approval and Review Processes
AI results should not be published without being reviewed. We are developing workflows that allow suggestions to be reviewed, evaluated, corrected, and approved.
Interfaces and System Integration
We integrate AI tools with existing systems such as DAM, PIM, ERP, CRM, portals, databases, file storage systems, and custom applications.
Dashboards and User Interfaces
We design interfaces where AI doesn't feel technical, but can be used as an intuitive tool: with inputs, suggestions, status updates, results, checks, and clear next steps.
What AI and automation make possible.
Leverage knowledge. Streamline processes. Ensure quality.
Our Services.
From use case to a usable AI tool.
AI projects succeed when they start not with the technology, but with a specific use case. That’s why we first determine what problem needs to be solved, what data is available, what level of quality is expected, and how people, processes, and AI work together.
Based on this, we develop digital solutions that not only impress but can also be used in everyday life.
AI Consulting & Use Case Definition
Together, we assess which tasks are suitable for AI or automation. In doing so, we consider the effort involved, the available data, quality standards, risks, data protection, user groups, and the expected benefits.
Process Analysis & Automation Concept
We analyze recurring processes, manual checks, document workflows, content workflows, and internal handoffs. Based on this analysis, we develop a plan that identifies where automation can truly reduce the workload.
Prompt and System Logic
We develop structured prompts, system instructions, rules, and contextual logic that guide AI applications in a targeted manner and enable better results.
RAG, Search & Knowledge Access
We develop AI solutions that can access existing knowledge: documents, guidelines, databases, product information, project knowledge, or internal content.
Document Analysis & Data Extraction
We develop workflows that extract data from documents, recognize content, structure information, and prepare results for further processing.
AI-powered image and content tools
We design and develop tools that support creative tasks, such as brand-compliant illustrations, variations, text modules, image ideas, or structured content suggestions.
UX/UI for AI Tools
We design user interfaces that make AI understandable, controllable, and helpful. These include input forms, previews, result evaluations, corrections, status indicators, and approvals.
Interfaces & Integration
We integrate AI tools with existing systems, portals, file storage solutions, DAM, PIM, ERP, CRM, databases, and custom applications. This ensures that the solution is not an isolated experiment, but rather an integral part of the digital process.
MVP, Pilot, and Further Development
A controlled rollout makes sense, especially for AI projects. We can start with an MVP or pilot, test the results, reduce risks, and gradually improve the solution.
Support & Ongoing Optimization
After launch, we continue to support AI tools through monitoring, adjustments, new use cases, prompt optimization, UX improvements, interface customization, and ongoing development.
Eight good reasons.
Why it's a pleasure to work with us.
Frequently Asked Questions About AI & Automation
AI is worthwhile when recurring tasks are time-consuming, large amounts of information need to be analyzed, or teams need better templates, summaries, suggestions, or reviews. AI is particularly useful when there is a clear process, good data, and specific quality standards in place. Not every use case requires AI. Together, we’ll assess where AI provides real value and where traditional automation makes more sense.
Automation reliably executes defined steps. AI can also interpret, formulate, summarize, classify, or recognize patterns. The combination of the two is often particularly powerful: AI prepares information, automation incorporates it into a process, and humans review or make decisions at the relevant points.
Yes, provided that brand logic, style guidelines, tone, visual language, and approval processes are clearly defined. AI should not generate content arbitrarily but should be guided by clear inputs, rules, and quality assurance. This allows for brand-compliant suggestions that accelerate creative work while still remaining controllable.
Yes. AI-powered document analysis can extract, structure, and interpret content from PDFs, scans, forms, transcripts, or certificates. It is important to precisely define the quality of the documents, the required fields, validation rules, and responsibilities. In many cases, human review remains useful or necessary.
That depends heavily on the setup. Clear data rules, access restrictions, secure interfaces, logging, roles, approvals, and a mindful approach to handling sensitive information are all important. We design AI solutions so that they do not emerge unchecked within the company, but are integrated into clear technical and organizational frameworks.
Not always. Many use cases can be addressed using existing models, effective prompting, clear system instructions, RAG approaches, or structured workflows. Developing a custom model only makes sense if the requirements, data volume, quality, and long-term benefits justify it. We’ll evaluate which setup is appropriate and cost-effective.
Yes. AI tools can be connected to portals, DAM, PIM, ERP, CRM, databases, file storage systems, or custom interfaces. The key factors are which data can be used, which system serves as the primary system, and where the results should be processed further.
Ideally, start with a clearly defined use case. We often recommend an MVP or pilot project that allows you to test the benefits, quality, data availability, and user acceptance. This approach avoids creating a large, abstract AI project and instead provides a concrete starting point with real learning value.
The costs depend on the use case, data sources, interfaces, user interface, security requirements, model usage, approval processes, and desired feature set. A lean prototype is priced differently than a production-ready tool with roles, workflows, and system integration. Following an initial analysis, we’ll provide a transparent quote with clearly defined service components.
Yes. AI and automation solutions should continue to be monitored, adjusted, and improved after launch. We provide ongoing support, including prompt optimization, new use cases, interface adjustments, UX improvements, and continuous development.
