Own the models, data, and code behind your k-12 AI on your own infrastructure — vs. a per-seat assistant running in Anthropic's cloud
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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K-12 organizations adopting AI face one hard constraint before any feature: minors' student data must stay protected under FERPA and COPPA. Where the AI runs — and who controls it — matters as much as what it does.
Claude is a managed assistant from Anthropic, billed at roughly $30 per user per month and running in Anthropic's cloud on Anthropic's Claude models. Its strength is strong long-context reasoning and safety with little setup, but it is locked to Anthropic's models and your data is processed in the vendor's cloud.
Self-hosted AI runs on infrastructure you control — on-premise, in your private cloud, or fully air-gapped. You own the code, the data, and the models, run any LLM, and keep minors' student data inside your perimeter, integrated with PowerSchool, Clever, ClassLink, and Google Classroom. This comparison covers safe tutoring, lesson planning, and parent communication for k-12 — and when each option is the right call.
by ibl.ai
Owned agentic AI platformby Anthropic
Per-seat AI assistant| Criteria | Self-Hosted AI | Claude |
|---|---|---|
| Out-of-the-Box Productivity | Strong agent capability once deployed; you configure the workflows your teams need. | Polished assistance from day one with strong long-context reasoning and safety. |
| K-12 System Integration | Deep integration with PowerSchool, Clever, ClassLink, and Google Classroom via APIs and MCP, built around your data. | Connects to common tools, but integration with sector systems is limited. |
| Custom Agents & Workflows | Build and own production agents for safe tutoring, lesson planning, and parent communication. | A few prebuilt agents; customization is bounded by the platform. |
| Any-LLM & Model Control | Run any open or commercial model, route by cost/latency/capability, and switch anytime. | Runs on Anthropic's Claude models; locked to Anthropic's models. |
| Criteria | Self-Hosted AI | Claude |
|---|---|---|
| Self-Hosting / On-Prem / Air-Gapped | Run on your servers, private cloud, or fully air-gapped with zero external calls. | Runs in Anthropic's cloud; cannot be self-hosted or air-gapped. |
| Data Stays in Your Perimeter | minors' student data never leaves your environment; every interaction is logged for audit. | Vendor controls help, but data is processed in the provider's cloud. |
| Model Choice | Any LLM — open-source or commercial — under your control. | Locked to Anthropic's Claude models. |
| Source Code & Platform Ownership | Own the full platform code; no lock-in to a vendor's roadmap. | You rent access; the platform and roadmap belong to the vendor. |
| Criteria | Self-Hosted AI | Claude |
|---|---|---|
| Cost at Scale | Flat, usage-based cost on owned compute — no per-seat fees. | roughly $30 per user per month; cost rises with every seat. |
| Compliance & Audit Fit | Data stays in your perimeter, supporting FERPA and COPPA with full audit logging. | Vendor compliance coverage under shared-responsibility cloud terms. |
| Time-to-Value | Requires infrastructure and setup, or a partner to deploy it for you. | Turn it on for your users with minimal setup. |
| Support & Maintenance | Self-managed, or fully supported with forward-deployed engineers. | Fully managed by Anthropic with enterprise support. |
Self-hosted AI keeps minors' student data inside your perimeter and can run fully air-gapped — the strongest posture for FERPA and COPPA.
Claude adds capable assistance quickly, but processes data in Anthropic's cloud under shared-responsibility terms.
For k-12 workloads bound by FERPA and COPPA, owning the stack is the safer default; Claude fits lower-sensitivity productivity.
Self-hosting replaces per-seat licensing with flat cost on compute you own, so broad rollouts don't scale with headcount.
Claude is roughly $30 per user per month, predictable per user but growing with every license.
For organization-wide deployment, owned infrastructure is often far cheaper at scale.
A model-agnostic platform runs any model — including the vendor's own — and switches as the frontier moves.
Claude is locked to Anthropic's models.
If avoiding model lock-in matters, the owned, model-agnostic platform wins.
Self-hosting keeps minors' student data in your environment, supporting FERPA and COPPA and air-gap requirements a managed cloud assistant cannot meet.
Claude delivers immediate value with strong long-context reasoning and safety and minimal setup.
Flat, usage-based cost on owned compute avoids per-seat fees that scale with headcount.
Owning the platform lets you build and tune production agents for safe tutoring, lesson planning, and parent communication across any model.
Timeline: A few weeks, depending on infrastructure and MLOps maturity
Timeline: Days to a couple of 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 is a self-hosted, model-agnostic AI Operating System you own and run on your own infrastructure — on-premise, in your private cloud, or fully air-gapped — so minors' student data stays in your perimeter under FERPA and COPPA. Agentic OS orchestrates agents and workflows across any LLM for safe tutoring, lesson planning, and parent communication, integrated with PowerSchool, Clever, ClassLink, and Google Classroom via APIs and MCP; Agentic LMS delivers training; Agentic Course generates materials. You own the code, data, and models — SOC 2, HIPAA, and FERPA compliant by design, with no per-seat fees.
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.