Advisory
We look at the work your team actually does before recommending anything. Most of the value in an AI assessment is in what it rules out.
An advisory engagement starts with observation, not a workshop. We sit with the people doing the work, read the artifacts they produce, and time the loops they repeat. That produces a short list of candidate workflows ranked by how much of the task is genuinely language-shaped and how much is data plumbing wearing a costume.
You get a written recommendation with the losers named as clearly as the winners. If the honest answer is that a scheduled report and a cleaner join key would solve the problem, we will say so and it will cost you a fraction of a model deployment.
What you get
- Workflow inventory with time-on-task measured, not estimated
- Ranked opportunity list with expected effort and failure modes
- Explicit do-not-build list with reasoning
- Reference architecture for the top one or two candidates
- Cost model covering inference, storage, and the people who keep it running
Call us when
- A board or agency head has asked what the AI plan is
- A pilot worked in a demo and stalled on contact with real data
- Several vendors are quoting wildly different numbers for the same problem
Talk to us about advisory
Describe the situation in a paragraph. We will reply with what we would look at first and what it would cost to find out.