can your team use ai on real work — safely, on data it can trust? eight weeks. up to fifteen people. one tool shipped into production. we teach it because we build it.
no generic curriculum. we read your workflows and your data estate, pick the tool the team will ship, and write the eight-week syllabus from what your people actually do on a tuesday.
the team builds the tool with us, on governed data. every session works on live material; everything that ships passes a qa gate. by week five the tool is doing real work in a sandbox.
the tool ships. the hand-over is a working paper — runbook, prompts, evaluation criteria — and the test is simple: would the team notice if you took the tool away on a tuesday morning?
ai fails on data nobody trusts. the programme runs on governed data and real workflows, which is why the tool still gets used in month six. if your estate isn't ready, the assessment finds that out first — two weeks, fixed price.
would the team notice if you took the tool away on a tuesday morning? a test for whether ai enablement landed — and the design choices that decide it in advance.
a team that uses ai on its own work, on its own data, with qa gates it understands. that is the deliverable.