Independent AI consultancy for schools

AI Consulting for K-12 Schools

We build automation into the systems your staff already use. Not another app to log into.

ClassroomOps works with heads of school, principals, curriculum directors, IT directors, and superintendents who want AI doing real work in the building rather than sitting in a pilot deck.

Request an AI Workflow Audit See what it costs

Every engagement starts with a two-week audit at $2,500. No retainer, no software license, no per-teacher fee.

Where schools lose the most time

Three problems we solve first

High-volume, repetitive, and governed by rules your staff can already write down. That is what automates well.

Grading and feedback

Teachers write the same feedback paragraph thirty times a week, and written feedback is the first thing cut when the week gets tight.

A typical teacher spends 5 hours a week on grading and feedback — out of a 54-hour median workweek (EdWeek Research Center / Merrimack College national survey).

Grading and feedback automation →

Administrative workflows

The same information gets retyped into three systems. Attendance, enrollment, incident logs, and scheduling all move by hand.

Administrative workflow automation →

Parent communication

The families who need the most contact get the least, because personalized outreach costs the most staff time. Translation makes it rarer still.

Parent communication automation →

Planning across more than one building? See how district implementation works.

Not a menu

Those are the three most common starting points

Every engagement is scoped from your audit, not from a service list. If the hours in your building are going somewhere else, that is what gets built. Recent examples of “somewhere else”:

  • Attendance-letter generation
  • IEP meeting prep paperwork
  • Substitute coordination
  • Enrollment intake
  • Report-card comment drafting
  • Translation review queues

If your biggest time sink is not on this page, that is a normal audit finding, not an edge case.

How an engagement works

Audit, then pilot, then rollout

You do not have to commit to a rollout to find out whether this is worth doing. Each step is priced on its own.

The engagement path: audit, pilot, rollout A three-step path. Step one, an AI workflow audit: 2,500 dollars, two weeks. Step two, a single-workflow pilot: 6,000 to 9,000 dollars, four to six weeks. Step three, a department rollout: 18,000 to 30,000 dollars, about 90 days plus 90 days of support. Each step is priced on its own, and the audit fee is credited toward a rollout that proceeds. 1 AI Workflow Audit $2,500 · 2 weeks a ranked roadmap you keep either way 2 Single-workflow pilot $6,000–9,000 · 4–6 weeks one workflow, live, in your real systems 3 Department rollout $18,000–30,000 · ~90 days + 90 days of support 3–4 workflows, handover docs The audit fee is credited toward a rollout that proceeds

Each step is priced on its own and produces something you keep. Stopping after any step is a normal outcome, not a failure mode.

What moves each number, what is included at each step, and what a school should budget in year one: the pricing page answers all of it with specifics.

Why ClassroomOps

Built like production software, because it is

Most school AI pitches are a demo and a promise. This is an architecture, and you can inspect it.

How student data is de-identified before any AI call Inside the school's systems, student names are replaced with tokens. Only the de-identified record crosses to the AI model, which returns a draft. Back inside the school's systems, tokens become names again, a teacher reviews and approves, and only then does anything reach a family. INSIDE YOUR SCHOOL’S SYSTEMS Student record Jayden M. De-identify Jayden M. STU-041 names become tokens de-identified only AI model outside your systems sees STU-041 never Jayden M. Returns a draft. Nothing is stored. draft returns Re-identify STU-041 Jayden M. tokens become names Teacher reviews, edits, approves — or not Family receives it No student name ever crosses the dashed line.

The de-identification boundary. Names are tokenized before any request leaves your systems, and re-identified only after the draft is back inside them. The model works entirely on tokens.

AI drafts. Teachers decide.

Nothing reaches a student or family without a person approving it. The gate is how every workflow is built, not a setting that can be switched off.

No new logins for staff

The work lands in Google Workspace, your SIS, and the tools staff already open. A tool nobody adopts is worth zero, so adoption is an architecture decision here.

Engineering, not slideware

Error handling, retries, logging, and a plan for the day the model returns something wrong. An engineering background that runs from J.P. Morgan to production AI systems, now pointed at schools.

English and Spanish as standard

Communication workflows ship bilingual by default. Additional languages are available, each with native-speaker review and validation before anything goes home.

The principles behind this, and who does the work: why ClassroomOps works this way.

Proof, not promises

See it running

Two working systems built on the same architecture we install in schools: a rubric-to-feedback engine and a bilingual parent-communication generator. Both run on synthetic student data, and both show the de-identification layer and the approval gate live.

Watch the demos Read how the grading engine works

Start with a conversation

Tell us what is taking the most staff time. If an audit is not the right next step, we will say so.

Do not include student names or student records in this form. Replies usually go out within one business day.