AI and LLM automation
Many projects with language models stall between a promising demo and a tool a team can rely on.
Language models that take routine work off your team.
Each language model is one component in a larger system. When the model is uncertain, a fallback path takes over.
- Internal assistants for your team
- Support chatbots for first-line questions
- Document summarisation and classification
- Routing of requests to the right person or system
- Workflow automation built on language models
At handover your team can inspect and change every part of it.
- A production-grade integration of the model
- Logging and fallback handling for every workflow
- The prompts and the logic behind each step
- Cost monitoring per workflow
What can AI automation take over in a business?
AI automation takes over the repetitive, language-heavy work between systems. That includes reading and classifying documents, drafting first replies, summarising long threads and routing requests. The judgment stays with your team.
Is AI reliable enough for production?
Yes, when the system around it is built for production. That means monitoring, fallback paths for uncertain answers and clear limits on what the model may do.
Do we control the prompts and the logic?
Yes. You own the prompts, the logic and the cost monitoring. Nothing sits in a black box that you cannot inspect or change.