Every engagement names its deliverable up front — then ships it. This is the arc we run whether the scope is a two-week readiness assessment or a production build your team will operate for years.
01
Assess
Every engagement starts with what you have: data estate, policy environment, risk posture. We map where AI creates value in your institution — and where it should wait — against FERPA, HIPAA, and board expectations.
You get: a readiness assessment and a governance framework your general counsel can sign.
02
Govern
Adoption fails in the cabinet room before it fails anywhere else. We brief presidents, provosts, and boards in their language, and build the decision structures that keep AI accountable to the institution.
You get: an executive briefing series and a standing AI oversight charter.
03
Enable
Tools don’t upskill people; practice does. Role-based curricula for staff, faculty, and administrators — from prompt literacy to data stewardship — taught by people who run these systems daily.
You get: a role-based curriculum with certification checkpoints.
04
Build
We ship. Production GenAI, workflow automation, and agentic systems — built and operated on whatever cloud you run, inside your compliance boundary, with the monitoring and rollback discipline of teams who carry the pager.
You get: a production system on your cloud, with runbooks.
05
Measure
If you can’t measure it, you bought a demo. We instrument adoption from day one — usage, outcomes, cost — and report return in terms a procurement evaluator will accept.
You get: an adoption dashboard and a defensible ROI model.
01
Two to four weeks of discovery: your data estate, your policies, and the decision that is actually stuck.
02
One sentence, agreed by both sides, before any work begins. It is the only definition of done.
03
Principals do the work. You see progress weekly — not at a final readout.
04
Runbooks, training, and a measurement plan your team owns. We leave when you can run it.
Three engagements led by the principals. Institutions are unnamed by agreement; references are available on request.
Assess → Measure
Situation
A system-wide restructuring decision with no shared data model across campuses and a board deadline.
What we did
Built the unified analytic model, ran the scenario analysis, and briefed the board of trustees directly.
What changed
$22M
restructuring analysis adopted by the board; the model became the system’s standing planning tool.
Build
Situation
[A manual, document-heavy workflow inside a strict compliance boundary; pilots had stalled at security review.]
What we did
[Designed and shipped a production GenAI/agentic system on the client’s cloud with monitoring, audit trail, and rollback; operated it post-launch.]
What changed
[8+]
[systems in production; e.g. cycle time from X days to Y hours, zero compliance findings across N audits.]
Govern → Enable
Situation
Fifteen disconnected survey instruments across advising, climate, employees, and outcomes — no shared cadence, no governance, no one number leadership trusted.
What we did
Stood up a single institutional research program: annual, one-time, and ongoing instruments on one calendar, one data model, and a review cadence the cabinet owns.
What changed
15
instruments under one governance model; [response rate / turnaround / decisions informed — add one hard number].
A priced deliverable with a date. The most common first engagement — and sized for simplified acquisition thresholds.
A principal on call for your cabinet: board preparation, vendor review, and the questions that don’t wait for a statement of work.
We build on your cloud and run it in production until your team is ready to take the pager.