Student-facing AI spaces run by a vendor, or the same capability running inside the district's own perimeter
On ibl.ai you own all the code and the data, run it model-agnostic across any LLM, and pay with no per-seat pricing — so you can deploy anywhere, from your own cloud to a fully air-gapped network.
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SchoolAI puts AI directly in front of students, with teacher-visible spaces so an educator can see what students asked and how the AI answered. That oversight model is the right instinct: student-facing AI without teacher visibility is not something a district should deploy.
The question a district still has to answer is where those conversations live. In a hosted product, every student message is transmitted to and stored by the vendor.
Student chat logs are among the most sensitive records a district generates. They contain minors' words, sometimes disclosures about home life or mental health, and they are subject to FERPA and COPPA regardless of how carefully the vendor handles them.
A self-hosted platform provides the same student-facing experience and the same teacher oversight, with the conversations stored in district systems — which changes what a district must trust, and who it must trust it to.
by ibl.ai
Owned agentic AI platformby SchoolAI
Hosted student-facing AI spaces| Criteria | Self-Hosted AI | SchoolAI |
|---|---|---|
| Out-of-the-Box Readiness | Production agents for tutoring, guided practice, reading support, and teacher-monitored student inquiry once deployed, configured to how your organization actually works. | Immediately useful — student-facing AI spaces with real teacher visibility and moderation built into the design. |
| Integration With Your Systems | Deep integration with Clever, ClassLink, Google Classroom, and PowerSchool over APIs and MCP, running inside your own network. | Connects to common systems, bounded by the connectors the vendor has built. |
| Extensibility | Build and own workflows the vendor has not thought of, because you hold the code. | Configurable within the product; capabilities outside it require the vendor to build them. |
| Any-LLM & Model Control | Run any open or commercial model, route by cost, latency, and capability, and switch anytime. | Runs on models SchoolAI selects and manages. |
| Criteria | Self-Hosted AI | SchoolAI |
|---|---|---|
| Self-Hosting / On-Prem / Air-Gapped | Runs on your servers, your private cloud, or fully air-gapped with zero external calls. | Runs in SchoolAI's cloud; it cannot be self-hosted or air-gapped. |
| Where the Data Lives | student conversations and minors' data never leaves your environment, and every interaction is logged for audit. | Processed and retained on the vendor's infrastructure under your agreement. |
| Source Code Ownership | You hold the full source and can audit, fork, and extend every layer. | You rent access; the platform and its roadmap belong to the vendor. |
| Fit With FERPA and COPPA | Data stays inside your perimeter, which is the simplest posture to evidence under FERPA and COPPA. | Vendor compliance coverage under shared-responsibility terms. |
| Criteria | Self-Hosted AI | SchoolAI |
|---|---|---|
| Cost at Scale | Flat license plus compute you own — extending access across K-12 districts does not multiply the bill. | per-student and district licensing, so cost grows with the size of the organization rather than the work done. |
| Time-to-Value | Requires deployment and integration, or a partner who does both for you. | Usable almost immediately with no infrastructure work. |
| Support & Maintenance | Self-managed, or fully supported with forward-deployed engineers. | Fully managed by SchoolAI. |
| What You Keep If the Relationship Ends | A working platform and all your data, still running on your own infrastructure. | Whatever the contract allows you to export. |
Self-hosting keeps those conversations in district storage, under district retention rules, reviewable by district counsel without a vendor in the loop.
SchoolAI's oversight design is genuinely good, but oversight and residency are different properties — a teacher can see the conversation and it can still be stored by the vendor.
Districts should ask both questions separately: can a teacher see it, and where does it live. Only one of those is answered by a monitoring feature.
An owned platform lets a district set its own guardrails, escalation paths, and disclosure-handling rules, and change them after an incident without waiting for a vendor release.
SchoolAI ships safety tuned for K-12, which is more than a general assistant offers and is the right default for most districts.
A vendor's defaults are usually better than a district's first attempt. A district's own rules are better than a vendor's defaults once something specific goes wrong.
A flat, self-hosted license does not change when every student in the district gets access, which is precisely the deployment districts actually want.
Per-student licensing prices exactly the thing a district is trying to do, so the cost of universal access is the cost of the enrollment.
For a classroom pilot, per-student pricing is trivially affordable. For universal access, the pricing shape is the deciding factor.
Student conversations are the most sensitive AI record a district creates, and self-hosting keeps them in district storage under district retention rules.
A hosted product with K-12 safety tuning and built-in teacher visibility is the fastest safe way to start.
Per-student licensing prices universal access at the size of the enrollment, while a flat self-hosted license does not.
Escalation paths and disclosure handling should follow district policy, which requires the ability to configure and change guardrails directly.
Timeline: Four to ten weeks depending on integration count and review requirements
Timeline: Days to a few weeks
ibl.ai is the agentic AI platform where you own all the code and the data. You self-host the entire stack inside your own perimeter, run it model-agnostic across any LLM and switch anytime, and pay by usage with no per-seat pricing — so you can deploy anywhere: your cloud, on-premise, GovCloud, or fully air-gapped.
ibl.ai runs student-facing AI inside the district's own perimeter, so conversations with minors are stored in district systems under district retention rules — reviewable by district staff and counsel without a vendor in the loop. Agentic OS applies guardrails, moderation, and PII redaction the district configures, with escalation paths that follow district safeguarding policy rather than a vendor's defaults. It connects to Clever, ClassLink, Google Classroom, and PowerSchool for rosters and context, and logs every interaction for audit. You own all the code and the data, run any model, and can deploy on any cloud, on-premise, or air-gapped — on a flat license rather than per student.
Full source code under a perpetual license, running on your infrastructure. Not API access to someone else's platform — the stack itself is yours.
Run any LLM — Claude, GPT, Gemini, Llama, Command, or your own fine-tune — and switch providers without rewriting the platform.
Usage-based billing against a budget cap you set. Cost tracks what your organization actually uses, not how many people you employ.
Your cloud, your VPC, on-premise, GovCloud, or a fully air-gapped network with no outbound connectivity.
1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University.
ibl.ai is family-owned and operated from New York, NY — a U.S.-headquartered, domestically-owned long-term partner, not a vendor that sells licenses and moves on.
See how ibl.ai deploys AI agents you own and control—on your infrastructure, integrated with your systems.