AI Consulting & AI Integration: We Implement AI in Practice
From roadmap to live AI: We find the right use cases, connect GenAI and your data, and run it securely.
AI with real added value – not just a PoC
AI is only successful when it fits into processes & systems
Many have tried ChatGPT and similar tools. Real value comes when AI is part of daily work: clear goals, good data, solid links to your systems, and a plan to run it.
We help you choose the right use cases, reduce risks, and implement AI so it has a real impact – in customer service, knowledge, sales, operations or quality.
AI Services – Focus on Implementation & Integration
- AI Potential Analysis, Strategy & Roadmap
Goals, KPIs, use cases, data and governance – a clear plan for rollout and running it
- Generative AI & RAG Integration
Connect AI to your docs and systems (DMS, Wiki, ERP, CRM) for accurate, up-to-date answers
- AI Agents & Process Automation
Agents for recurring tasks (e.g. research, ticket triaging, quote preparation)
- Prompt Engineering & Guardrails
System prompts, checks and safeguards for consistent, safe results
- MLOps, Monitoring & Operations
Rollout, monitoring, quality checks and ongoing improvement so AI keeps working well
Partners Who Trust Us
Experience from Real Projects
Selection of clients & organizations (excerpt).
Approach
From Idea to Productive AI Deployment
We reduce risk with clear steps: use case, data, integration, operation. We deliver in small, visible steps.
1) Analysis
Goals, processes, data sources, stakeholders & risks
2) Roadmap
Use cases, prioritization, KPIs, governance & security
3) PoC/Pilot
Test quickly, evaluate, guardrails & quality
4) Integration
Connection to ERP/CRM/DMS, APIs, roles & rights
5) Operations
Monitoring, feedback loops, MLOps and continuous improvement
Advantages of AI Consulting & Implementation with Groenewold
We combine strategy, build and run – so AI doesn't just look good, it delivers.
Pragmatic & Measurable
We set clear KPIs and deliver in steps. You see real impact on processes, costs or quality.
Integration Instead of Island Solution
AI only works in context: We integrate into your systems (ERP/CRM/DMS) and processes.
Security & Data Protection
Roles & rights, audit logs, data minimization and governance – planned from the start.
RAG with Company Knowledge
We connect LLMs with your knowledge sources – for answers that are documented, up-to-date and traceable.
Operations & Development
Monitoring, evaluation and continuous improvement – so quality and benefit remain stable long-term.
End-to-End from One Source
From the roadmap to production implementation – including frontend, backend, data and integrations.
You want to use AI sensibly – but without buzzwords, with clear benefit? We give you a pragmatic initial assessment and suggest the next sensible step.
AI Solutions: Practical Intelligence for Real Business Challenges
Artificial intelligence has moved far beyond the experimental phase, yet many companies struggle to extract real value from it. The gap between a promising ChatGPT demo and a production-ready AI system that integrates with your ERP, respects access controls, and delivers consistent results is significant. We bridge that gap by focusing on practical implementation rather than theoretical possibilities, starting with clearly defined use cases that have measurable business impact from day one.
Our approach to AI consulting centers on Retrieval-Augmented Generation and intelligent agents that work with your existing company data. Rather than training custom models from scratch, we connect proven large language models to your knowledge sources through secure RAG pipelines. This means your employees can query internal documentation, product catalogs, or process guides in natural language and receive accurate, source-cited answers without sensitive data ever leaving your infrastructure.
The difference between a successful AI deployment and a failed experiment often comes down to operational readiness. We build monitoring dashboards that track response quality, implement guardrails that prevent hallucinations in critical workflows, and establish feedback loops so the system improves over time. Our MLOps practices ensure that AI models stay reliable in production, with automated evaluation pipelines that flag degradation before users notice any change in output quality.
Security and governance are not afterthoughts in our AI implementations. Every solution we deploy includes role-based access controls, comprehensive audit logging, and data minimization principles aligned with GDPR requirements. We offer deployment options ranging from European cloud providers to fully on-premise installations for organizations with strict data residency requirements. This pragmatic approach to AI security lets companies in regulated industries adopt intelligent automation without compliance concerns.
The Technical Infrastructure Behind Successful AI
Successful AI projects depend on the right infrastructure. Vector databases like Pinecone, Weaviate, or Qdrant form the foundation for high-performance RAG systems: they store semantic representations of your company documents and enable lightning-fast similarity searches that far surpass traditional full-text search. Python frameworks like LangChain and LlamaIndex have become the de facto standard for orchestrating LLM applications – they abstract the complexity of prompt chaining, tool use, and memory management. For organizations with strict data protection requirements, edge computing enables on-premise inference: smaller, optimized models run directly on local hardware, ensuring sensitive data never leaves the corporate network.
Making AI Measurable: Evaluation and Continuous Improvement
An AI system is only as good as its provable quality. A/B testing is an indispensable tool: through controlled experiments, we compare different prompt strategies, retrieval configurations, or model versions and measure which variant actually delivers better results. For chatbot applications, we use automated evaluation frameworks that assess response quality, relevance, and tone – supplemented by human feedback from real usage scenarios. Monitoring and logging ensure that quality degradation, increased latency, or unexpected costs are detected and addressed immediately. This ensures AI systems deliver stable results not just at launch, but on an ongoing basis.
AI and Automation: Working in Concert
AI delivers its greatest leverage when combined with process automation. While traditional automation operates on rules, generative AI brings understanding and decision-making capability to automated workflows: incoming emails are not just sorted by keywords but understood contextually and routed accordingly. Through API integrations, we seamlessly connect AI components with your existing systems – from CRM to DMS to ticketing systems. This interplay of intelligent recognition, automated execution, and human oversight at critical points drastically reduces manual routine work and creates room for value-adding activities.
Related Topics in Our IT Glossary
Related Services
Frequently Asked Questions
AI Consulting
Getting Started & Governance
How do we start sensibly with AI – without a finished data strategy?
We start with a quick check: your goals, processes, data and risks. Then we pick 2–3 use cases and plan the steps (PoC → Pilot → live).
What does an AI project typically cost?
It depends on the use case, your data and how much we need to connect. A small proof of concept can often be done in a few weeks. For live systems we plan governance, security and support from the start.
Can existing systems (ERP/CRM/DMS) continue to be used?
Yes. We add AI where it helps – via APIs, events or links to your knowledge base and docs. Your core systems stay as they are; we add AI on top.
How do you ensure data protection and security?
We build security in from the start: minimal data, clear roles and rights, logs and secure links. We can use EU or in-house models and on-prem or private cloud if you need it.
Why do AI projects often fail – and how do you prevent that?
Often: unclear goals, bad data, or a demo that never goes live. We set KPIs, plan data and operations (MLOps), and deliver in steps with clear results.
Related Topics
Complementary Services from Other Areas
These services are frequently requested together with AI & Machine Learning or complement it thematically.
Data, Analytics & Databases
Consulting & Strategy