Does student or family data leave the school's systems?
No. Systems are built in accounts the school owns, on tools it already pays for. FERPA-covered records stay in the school's own systems; an AI tool receives only the fields a specific workflow needs, never a student's full record, and the school's own records officer signs off on each workflow before it runs. A staff member reviews every output before it reaches a family or a trustee, and every engagement includes a written AI use policy the board can adopt.
Which school platforms does LUR Growth work with?
Blackbaud Raiser's Edge NXT and Education Management, Veracross, FACTS, and Google Workspace are the usual set. The build connects to what the school runs rather than asking it to move. Integration goes through each platform's own door: the Blackbaud SKY API, the Veracross API, FACTS exports, and Google Workspace. The LUR Growth technical lead on the engagement builds those connections with Latoya, inside accounts the school owns, and the school's own Blackbaud or Veracross administrator approves every permission before it is granted.
Has LUR Growth worked with a school before?
The closest engagement is a bilingual after-school and tutoring program for Latino students and families: curriculum, family engagement, evaluation, and funder reporting. The same four jobs a school carries, at a smaller scale. A school engagement would be the first of its kind, and the page says so plainly. Latoya has not yet built inside Blackbaud, Veracross, or FACTS for a school. That is why every school starts with the diagnostic: it names the platforms, the family-data rules, and the one job to fix first before anything is priced, and the first build is scoped to that one job.
Can the work support strategic-plan execution and accreditation?
Yes. The diagnostic can map each priority or standard to an owner, measure, source of evidence, review date, and communication rhythm. A later build can make progress and missing evidence visible without creating a second reporting system staff have to maintain.
Can LUR Growth help a school create faculty AI guidance?
Yes. The work can define approved uses, student and family data boundaries, human review expectations, documentation, and escalation paths. Faculty guidance is built with academic leadership and the people expected to use it, so it supports professional judgment rather than replacing it.
Where does a school start?
The Capacity Diagnostic. Two to three weeks, $2,400, and a board-ready read of which of the four jobs to fix first. It stands on its own and it does not commit the school to the next step. After that, one job on one platform is the $6,500 Focused Build. A school-scale build, all four jobs across the school's platforms, starts at the $24,000 three-workflow tier and is quoted exactly after the diagnostic names the platforms and the family-data rules. The diagnostic fee credits in full toward it.