We work alongside K-12 districts and higher-ed institutions to turn AI from a buzzword into a practical capability — training teachers actually use, policy leaders can defend, and curriculum that fits the way you already teach.
Each track builds on the one before it. Start with Teachers if AI is new to your building, or jump in at Building Leaders or District Operations if you already have classroom momentum and need policy, evaluation, and scale.
Practical AI literacy, prompt craft, and classroom workflows — grounded in what teaching actually looks like on a Tuesday at 10:15am.
Principals, APs, and instructional coaches learning how to observe, support, and scale AI-integrated teaching across a whole building.
Superintendents, CIOs, and curriculum directors building policy, evaluating vendors, and rolling out AI in a way the board can approve.
Universities and colleges face a different shape of the same problem: faculty autonomy, accreditation pressure, and institutional risk all in one room. We meet each audience where they are.
Course-level AI integration without gutting pedagogy. Assessment redesign in the age of generative tools. Discipline-specific prompt and workflow libraries.
Faculty development programs and cohorts. Program-level AI policy and syllabus language. Curriculum review and change management inside the department.
Institutional AI policy and governance. Accreditation-aligned guidance. Vendor evaluation and multi-year adoption strategy with measurable outcomes.
The thing that kills most AI-in-education initiatives isn't the tech — it's that nothing was built around how your people actually work. Each step below exists to close that gap.
We listen first. Where are teachers already using AI? Where are they stuck? What does leadership actually need to happen?
Curriculum, workshops, and policy documents built for your context — not a deck pulled off a shelf.
In-person PD days, virtual cohorts, asynchronous modules, or a hybrid. Whatever fits how your staff actually learns.
Ongoing coaching, office hours, and follow-up so the work survives past the first semester.
Shared indicators of progress — from teacher confidence to student outcomes — so you can show it's working.
Signals set in the Assess phase, revisited quarterly, and used to decide what gets scaled or cut.
Pre- and post-engagement surveys of staff comfort with AI in their role and subject area.
Percent of staff actively using AI in lesson prep, feedback, or instruction — not just aware of it.
Teacher hours per week returned through AI-assisted planning, grading, and communication workflows.
Observed and reported changes in student engagement, agency, and question-asking in AI-enabled lessons.
AUPs, ethics guidance, and governance documents completed and board-approved.
Building and district leaders able to sustain the work internally once our engagement ends.
