Teacher-facing AI · Grades 5-11 · Private schools and tutoring programs

    AI shouldn't think for students.
    It should help teachers understand how students think.

    New York City just paused student-facing AI for 600,000 kids. Norway banned it for ages 6-13. The schools that win the next five years won't put AI in front of students. They'll put it behind the teacher.

    1. Assess
    2. Identify gaps
    3. Detect misconceptions
    4. Reteach
    5. Verify mastery

    Live at GrowWise School since 2026 · 50 students · 4 teachers · Fully built, not a prototype.

    The number you're not tracking

    $237,000

    That's what the average private school loses to attrition every year. And you don't see it coming.

    Average school: ~180 students. Average attrition: ~10%. That's 18 families a year × $13,183 average tuition. Gone.

    Why families actually leaveShare of departing families
    Academic dissatisfaction17%
    Wanted more personalization11%

    Nearly a third leave for a reason you could have fixed, if you'd known which student was stuck, on what, before the family decided.

    By the time a teacher discovers a gap today, it's already compounded across three weeks of instruction. By the time a parent finds out, they're touring the school down the road.

    Sources: Private School Review 2024-25 (tuition); Finalsite (size, attrition); Qualtrics parent survey (reasons for leaving); Cato Institute 2025: 32% of private schools reported enrollment decline in 2024-25.

    Why every AI pitch you've heard went nowhere

    They all put AI in front of your students. That's the part that gets banned.

    Student-facing AI triggers the safety review, the parent consent forms, the board conversation, and now the moratoriums. It also doesn't work: Stanford researchers describe a "performance cliff" when the tool is taken away. The gain was on the screen, not in the student.

    Student-facing AI

    • Does the thinking for the child
    • Blocked by NYC, Norway, most policies
    • Requires consent, training, policy change
    • Homework stops being evidence

    Teacher-facing AI

    • Student still reads, writes, solves, struggles
    • Compatible with every student-facing ban
    • No student rollout. No consent forms.
    • Teacher knows exactly who's stuck and why

    Omnix360 never talks to a student. It runs on the assessment evidence your program already produces and hands each teacher one thing: the specific misconception blocking each student, and what to teach next.

    What you get

    Everything a program needs to stop losing families to "we didn't know."

    • The instructional loop

      Assess, identify gaps, detect misconceptions, recommend intervention, reteach, verify mastery. Runs every cycle, on every student, without a teacher building a spreadsheet.

      Catches gaps in the same lesson cycle, not at report cards

    • Misconception-level diagnosis

      Not "62% on fractions." Which fraction error. Whether it's actually a place-value gap from two grades back. Which four students share it and should be regrouped.

      Every teacher override makes the next diagnosis sharper

    • Live parent dashboard

      Topic-level strengths and weaknesses, updated continuously. Parents stop being the last to know. The 17% who leave over "academics" see the work happening.

      Recover ~$118,000/year at a 5-point attrition reduction

    • Teacher hours back

      Manual tracking, gap diagnosis, and parent updates come off the teacher's plate. Teachers average 49 hrs/week; 53% report burnout; replacing one costs $12K-$25K.

      Est. 6-10 hours/week per teacher · one retained teacher = $12K-$25K

    • Plugs into what you already run

      LTI 1.3 + OneRoster connector for Canvas, Google Classroom, Schoology, and the rest. No migration, no new procurement.

      No LMS switch · hours to connect, not weeks

    • No LMS? We bring one.

      Built-in LMS fallback, so "we'd need to buy a system first" is never the blocker.

      Zero infrastructure prerequisite

    • Founder-led onboarding

      One session with your teaching team. That's the whole rollout, because there is nothing to roll out to students.

      One session · live in days

    The math

    What you gain vs. what it costs you to try.

    Gain · every year, compounding

    Attrition recovery (5-pt reduction)$118,000
    One teacher retained$12K-$25K
    Teacher hours freed (4 teachers)~1,900 hrs
    Conservative total~$130,000/yr

    Pain · one time

    LMS migration$0
    Student rollout / consent$0
    Hardware / servers$0
    Teacher onboarding1 session
    SubscriptionPer student
    You're already spending $237,000 a year on attrition you can't see. This costs less than one student's tuition to implement. The gain is permanent. The pain is one-time. The ratio is more than ten to one.

    The 30-Day Pilot

    Run it on your real students for 30 days. Then decide.

    Connect your LMS (or use ours). One onboarding session. Your teachers run their normal assessments. In 30 days, you'll know exactly what the loop sees that you couldn't.

    The "name the blocker" guarantee

    If, at the end of 30 days, your teachers can't name the specific misconception blocking every student in the pilot cohort, you owe nothing and we remove the connector ourselves.

    Three pilot programs this fall.

    The founders run every onboarding personally. That caps how many programs we can take before January. When the three are filled, the next cohort opens in 2027.

    Proof, not promises

    We didn't build this in a pitch deck. We built it in a school.

    50

    students on the platform at GrowWise School, Dublin, CA

    4

    teachers running the loop in grades 5-11, classes of 10-12

    GrowWise School is our live lab. Omnix360 has run there every day since early 2026. Every assessment and every teacher override has made the diagnosis sharper. When you plug in, you're plugging into something that already works, not a prototype.

    Urgency you already feel: NAEP 2024 put 33% of 8th graders below basic in reading (worst in 30 years) and 39% below basic in math. Grades 3-8 students average half a grade level behind in both. Gaps compound every term.

    Read the NYC AI article

    What directors ask us

    The objections, answered.

    We've looked at AI tools before and they never stuck.

    Every one of them put AI in front of your students. This one doesn't. The safety objection that killed those conversations doesn't apply, and there's nothing to roll out to a classroom.

    What if it doesn't work for us?

    That's what the 30-day pilot is for. Your students, your assessments, your teachers. You'll see what it surfaces before you commit to anything.

    We don't have budget.

    You're losing ~$237,000 a year to attrition. Omnix360 costs less than one student's annual tuition to implement, per-student, no capital expense.

    Our teachers don't have time for another platform.

    It's not another platform. Teachers keep using the LMS they already use. Omnix360 sits behind it and takes work off their plate: tracking, gap diagnosis, parent updates.

    Does this comply with NYC-style AI restrictions?

    Yes. Those policies restrict student-facing generative AI. Omnix360 never interacts with a student. It's the design those policies explicitly leave room for: AI for instructional planning, behind the teacher.

    We don't have an LMS.

    Then we bring one. The built-in LMS fallback means there's no prerequisite purchase.

    Stop finding out at report-card time.

    Thirty days. One onboarding session. Your teachers will know, for every student, what's blocking them and what to teach next.

    Omnix360 is instructional infrastructure by GrowWise. Teacher-facing only; the AI never interacts with students. Figures: Private School Review 2024-25; Finalsite; Qualtrics; Cato Institute 2025; Learning Policy Institute 2024; RAND 2025; NAEP 2024; Education Recovery Scorecard 2025; NYC Mayor's Office, Sept 2, 2026; Reuters, June 19, 2026 (Norway); Christian Science Monitor, Aug 7, 2026 (Stanford "performance cliff"). Attrition-recovery and hours-saved figures are modeled estimates.