Specialist consulting
Applied AI and Automation Consulting
Automate processes with AI, n8n and APIs using prepared data, human validation and clear quality criteria.
Request a free initial assessmentThe challenge
An AI proof of concept can look impressive and still fail when it meets inconsistent data, implicit rules or a process without ownership.
Expected outcomes
- Viable use-case assessment
- Data and documentation prepared for RAG
- n8n, webhooks and API integrations
- Quality criteria and human validation
A good fit for
Operations that need clarity before adding more tools.
- Repetitive processes across systems and teams
- Documents or data that need intelligent retrieval
- Businesses evaluating AI without a clear use case or quality criteria
Approach
The solution starts from the process and its risk. The model is one part of the architecture, not the whole product.
LLMsRAGn8nAPIsWebhooksPython
Related work
An AI-ready data platform
See architecture and outcome ↗FAQ
Questions before the diagnosis.
Does every process need AI?
No. An integration or deterministic rule is often simpler and more reliable. AI is used only when it clearly improves a decision or execution.
Do you train an AI model from scratch?
The focus is applied AI: integrating existing models, preparing context and data, building automation and defining validation. Foundation-model training is outside the offer.
How do you reduce wrong answers?
The project makes sources, permissions, quality criteria, usage limits and human validation points explicit according to process risk.
Next step