Service
AI and machine learning
Applied to the work itself. A narrow agent that reliably does one job beats a broad one that demos well and is switched off within a month.
The seam this closes
Between the model and the business data it needs. Most AI projects stall on retrieval and permissions long before the model is the problem.
What gets built
- Retrieval over your own documents and records, with sources shown
- Agents scoped to a single task, with a defined failure mode
- Evaluation before rollout, so you know what it is right about
- Monitoring after rollout, because model behaviour drifts
What this is not
We do not build website chatbots. If a workflow change solves it, that is the cheaper answer and we will give it.
Start with the seam that is costing you the most.
A first call is a scoping conversation. If there is no system worth building, we will say so.