For us, AI is more than a chat window. We use it daily in operations and analysis, and we bring the same methods to our clients. AI adoption (part-time AI officer): For clients we act as an AI officer: we identify where AI makes business sense, connect it to company data and processes (customer support, analysis, reporting), train staff and keep an eye on security and output quality. Our approach:
- map processes and pick those where AI saves real work,
- prove the benefit in a small pilot,
- connect AI to your data and systems,
- move it into production and measure the benefit – what doesn’t pay off gets switched off. Connecting AI to your systems:
- AI agents on top of a ticketing system that triage requests and draft replies for human approval,
- MCP servers that let AI query accounting, sales or BI data securely – no copying spreadsheets into a chat,
- automated analysis, infrastructure management and documentation with Claude Code,
- a knowledge base that captures findings from operations so nothing has to be solved twice. Own models on own hardware:
- open language models running on NVIDIA DGX Spark and Apple Mac Studio machines, including large models split across several machines linked at 200 Gb/s,
- RAG over company documents: answers with source citations and no answers the source text does not support,
- a knowledge wiki continuously maintained by a language model from your source material,
- design and build of an AI server at your site. What you get: sensitive data never has to leave the company, AI works with your real systems, and we measure accuracy on your own questions. We’ll also tell you when a local model isn’t worth it – for some tasks a cloud model is the better choice, if the nature of the data allows. Before you buy hardware, we can arrange trial access to a GPU machine.