AI References – Chatbots & Knowledge Bases in Action
See how chatbots and knowledge bases are being used by companies – for knowledge preservation, process automation, and employee relief.
AI Projects from Germany: Practical Experience Over Theory
Artificial intelligence is no longer an abstract future topic – it is a production-ready technology that creates measurable value in an increasing number of companies. At Groenewold IT Solutions, we have successfully implemented numerous AI projects in recent years: from intelligent chatbots and RAG-based knowledge bases to specialized machine learning models for industrial applications. On this page, we showcase selected projects that exemplify our approach.
What distinguishes our AI projects is the consistent focus on business value. We do not implement AI because it is technically possible, but because a concrete problem needs to be solved. The AI knowledge base for a machinery manufacturer emerged from the need to preserve the knowledge of long-standing employees before their retirement. The AI cooking assistant Chop-E was developed to offer users a personalized cooking experience beyond simple recipe searches. And the Lullio baby monitor app shows how AI-based sound recognition can create real safety value for families.
Technologically, we rely on a combination of powerful language models (OpenAI GPT-4, Claude, open-source alternatives like Llama and Mistral), modern Retrieval-Augmented Generation architectures (RAG), and proven vector databases like Pinecone, Weaviate, or pgvector. Data privacy is particularly important to us: all our AI solutions are GDPR-compliant. For particularly sensitive data, we offer on-premise solutions that run entirely in your own infrastructure – without external API calls and without data leakage.
Our experience shows that the biggest success factor in AI projects is not the technology itself, but the quality of the data and the clarity of the objectives. That is why we start every project with a structured discovery workshop where we jointly define what problem needs to be solved, what data is available, and how success will be measured. Only then do we select the appropriate technology and develop a proof of concept. This iterative approach minimizes risks and ensures that the AI solution actually delivers the desired benefit.
Our AI Expertise
AI That Solves Problems – Not Just Impresses
We do not develop AI for the sake of AI. Every project starts with a concrete challenge: preserving knowledge, automating processes, supporting decisions. Technology is a means to an end – the value for your company is the focus.
Chatbots & Assistants
Intelligent dialogue systems for customer service, internal knowledge, and process automation
Knowledge Bases
RAG systems that make company knowledge searchable and usable
Machine Learning
Prediction models, classification, and pattern recognition for business processes
Language Processing
NLP for text analysis, summaries, and automatic categorization
Process Automation
AI-powered workflows for recurring tasks and decisions
Privacy-Compliant AI
GDPR-compliant solutions, also with local models without cloud connection
Selected AI Projects
AI Knowledge Base for Machinery Manufacturer
Development of an AI-powered knowledge base for a mid-sized machinery manufacturer. The system captures and structures the expert knowledge of long-standing employees and makes it accessible to all staff via an intelligent chatbot – even after their departure.
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Technologies:
Chop-E AI Cooking Assistant App
Development of an innovative AI cooking assistant called Chop-E that helps users discover new recipes and improve their cooking skills. The app offers various search modes such as search by ingredients, by dish, or random dish. With a friendly user interface and personalized recommendations, Chop-E turns cooking into an interactive and educational experience.
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Lullio Baby Monitor App with AI Sound Recognition
The Lullio Baby Monitor App transforms smartphones into a secure baby monitoring solution with HD live video and audio transmission, night vision mode, and two-way communication. With AI-powered sound recognition, the app automatically distinguishes between different baby sounds (crying, laughing, sleeping) and alerts parents intelligently.
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Your AI Project
AI for Your Company – Where to Start?
Whether chatbot, knowledge base, or process automation – we advise you on which AI solution brings the greatest value for your company. Free and without obligation.
Knowledge & Answers
Frequently Asked Questions About AI Projects
Getting Started & Feasibility
Is AI right for my company?
AI is worthwhile when you want to automate recurring tasks, make knowledge accessible, or improve data-driven decisions. In the initial consultation, we assess if and where AI provides the greatest leverage for you – sometimes a simpler solution is the better choice.
Do I need large amounts of data for AI?
Not necessarily. Modern LLMs (like GPT-4) already bring enormous knowledge. For many applications (chatbots, text processing), your existing documents and processes are sufficient. Only for specific machine learning do you need relevant training data.
What does an AI project cost?
A simple chatbot/FAQ bot: from EUR 15,000 plus VAT. An AI knowledge base with RAG: EUR 30,000-80,000 plus VAT. Complex ML projects with custom model: from EUR 50,000 plus VAT. Plus ongoing costs for API usage (OpenAI etc.) – typically EUR 100-500/month plus VAT depending on volume.
Want to explore AI potential?
In 30 minutes, we will determine if and how AI can help you.
Bjoern Groenewold – Managing Director
Technology & Data Privacy
Which AI technologies do you use?
Depending on the use case: OpenAI GPT-4/GPT-4o for text processing, Claude for complex analyses, open-source models (Llama, Mistral) for privacy-critical on-premise solutions. For embeddings and RAG, we use Pinecone, Weaviate, or pgvector.
Is this GDPR-compliant?
Yes, we strictly adhere to data privacy. For sensitive data, there are several options: OpenAI with EU data processing, Azure OpenAI in German data centers, or completely local solutions with open-source models. We advise on the optimal architecture.
Can our data be used for training?
No, not with proper configuration. OpenAI API and Azure OpenAI do not use your data for training. For particularly sensitive data, we recommend local models that run entirely in your infrastructure.
Implementation & Integration
How long does an AI project take?
An MVP chatbot: 4-6 weeks. A complete AI knowledge base: 2-4 months. Complex ML projects with data preparation: 3-6 months. We always start with a small proof of concept to show results quickly.
Can AI be integrated into existing systems?
Yes, that is often the core benefit. We integrate AI into your website, CRM, ERP, intranet, or as a standalone solution. APIs enable connection to virtually any system – from SAP to Odoo to custom applications.
Who maintains the AI after launch?
We offer maintenance contracts for continuous improvement: updating the knowledge base, optimizing prompts, incorporating user feedback. Alternatively, we train your team so you can develop the AI further yourself.
Ready for AI?
Let us talk about your AI idea and plan the next steps.
Thorsten Frieling – Project Management