What is Agentic OS and how does it differ from a traditional data warehouse?

Agentic OS is an AI operating system that creates a secure, per-user memory layer by unifying data from your systems of record — SIS/LMS, HRIS, CRM, ERP, EHR/EMR, and case or document management. Unlike traditional data warehouses, it provides policy-aware retrieval with fine-grained consent controls, so AI agents reach contextual data about a specific record — a learner, an employee, a citizen, a client, a matter, or a patient — under the regime that governs it.

Can we deploy Agentic OS in our own infrastructure?

Yes. Agentic OS can be deployed on-premise or in your cloud (AWS, Azure, GCP) using your VPC, KMS, and IAM. You receive full source code access to connectors, policy engine, and agent interfaces—no vendor lock-in.

What systems does Agentic OS integrate with?

Agentic OS connects to the systems of record an organization already runs: HRIS and ERP (Workday, Oracle, SAP, Dynamics), CRM and service desks (Salesforce, HubSpot, ServiceNow, Zendesk), EHR/EMR (Epic, Cerner, Meditech), document and case management (iManage, NetDocuments, SharePoint, Clio), SIS and LMS (Banner, PeopleSoft, Canvas, Blackboard, Brightspace, Moodle), and identity providers (Azure AD/Entra, Okta, Google Workspace). Connectors run over the Model Context Protocol, so data is read in place rather than extracted into another store.

How does Agentic OS handle privacy and regulatory compliance?

Agentic OS includes privacy by design with field-level permissions, PII redaction, consent receipts, and selective disclosure. Each user controls what data is shared with AI agents, and all access is logged for audit purposes. Because the platform runs inside your own perimeter, the evidence stays with you — supporting FERPA, HIPAA/HITECH, SOX, PCI DSS, GDPR, and NIST 800-53 obligations rather than asking you to trust a vendor's attestation.

What AI agents can run on Agentic OS?

Agentic OS powers three primary agent types, whatever the industry: front-line agents for the people your organization serves, operations agents that run the work behind them, and administrative agents for oversight and reporting. In practice that means knowledge search, IT help desk, and customer support in the enterprise; citizen services, compliance, and procurement in government; case research, contract review, and discovery in legal; KYC/AML, fraud detection, and risk in financial services; clinical support, documentation, and prior authorization in healthcare; and enrollment, advising, and tutoring in education. All agents are LLM-agnostic and can use OpenAI, Claude, Gemini, or local models.

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Agentic OS (Operating System)

Unify SIS, LMS, rostering, and assessment data into a secure student memory layer—powering tutoring, lesson planning, assessment, and family communication agents. 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. No need to choose build vs. buy — you get both.

Sector:Higher Education Corporate Small Business K-12 Government Legal Financial Services Healthcare

Your Code. Your Data.Full ownership, zero vendor lock-in

Any LLM, Your ChoiceAir-gapped or any cloud provider's

85% Lower CostSignificantly cheaper at scale

AI TransformationPre-existing and custom agents

Want to read the source?View the code on GitHub →

1.6M+Platform Users

400+Organizations

MCP Architecture Guide for K-12

How to connect your district systems (SIS, LMS, behavior tracking, parent communication) to AI agents — with FERPA and COPPA compliance.

Read the Guide

Runs on

Air-Gapped AI Anthropic Claude Google Gemini Microsoft Copilot Amazon Bedrock OpenAI GPT NVIDIA NemoClaw OpenClaw

1 / 5

Live

Tutoring AgentAdaptive help in math, reading, and science Live

Lesson Planning AgentStandards-aligned lessons and unit plans Live

Assessment AgentQuiz generation, rubrics, auto-grading Live

Writing Feedback AgentStudent writing review and comments Live

Special Education AgentIEP, 504, and accommodation support Live

Content Creation AgentWorksheets, presentations, activities Live

Student Safety AgentContent moderation and guardrails Live

Family Communication AgentParent updates and newsletters Live

Curriculum Alignment AgentStandards mapping and compliance Live

Professional Development AgentTeacher training and coaching Live

Research AgentStudent research and source finding Live

Administration AgentScheduling, reporting, operations

How ibl.ai compares

ibl.ai

Model choice

Any LLM — Claude, GPT, Gemini, Llama or open-source. Switch anytime.

Locked to Anthropic Claude models

Autonomous agents

Production-ready agents out of the box — plus the tools to build your own.

Chat assistant — you build & host your own agents

Privacy & ownership

100% self-hosted — private LLMs included. You own all the code, data & models.

Runs on Anthropic's cloud — your data leaves your walls

Cost at scale

Up to 85% lower — intelligent routing across providers, no per-seat lock-in.

Per-seat & per-token SaaS pricing

Delivery & services

Our engineers work with you to connect your data sources and build your agents.

Self-serve docs & standard support tiers

Want the full breakdown?Self-hosted & private LLM →See build vs. buy →Book a 30-min demo →

OS (Operating System) — Unify district data into a secure student memory layer

An Ownable AI Operating System for K-12 Education.

OS by ibl.ai connects SIS, LMS, rostering, and assessment systems over an MCP-based interoperability layer to assemble a secure, per-student memory.

That memory gives your AI agents the right context—so every student gets a personalized tutor, every teacher an intelligent assistant, and every district administrator a data-driven aide.

Deployed in your infrastructure with your keys and your controls—including full code access.

For K-12 Students: Personalized, Age-Appropriate Tutors

Unified Student MemoryGrade history, course enrollments, IEP/504 plans, assessment scores, and learning goals—federated from your SIS/LMS and made available (with policy guardrails) to the student's tutor.

Personalized LearningAdaptive practice, reading-level-adjusted explanations, and citable answers grounded in approved curriculum and state standards.

Safety by DesignAge-appropriate content filters, parental consent controls, and selective disclosure for every interaction.

ResultBetter engagement, improved proficiency, stronger equity outcomes.

For Teachers: A Reliable Digital Teaching Assistant

Classroom Context, Not GuessworkPulls rosters, standards alignments, assessment data, and prior performance to draft lesson support, differentiated activities, and interventions.

Workflow AutomationsParent communication drafts, progress report summaries, and formative assessment hints—always citing approved curricular sources.

Instructional ControlSchool- and district-level policies, versioned prompts, and oversight dashboards.

ResultMore time for instruction and relationships, less time on paperwork.

For District IT: Own the Stack, Protect Student Data

Runs in Your EnvironmentDeploy on-prem or in your cloud (AWS, Azure, GCP). Your VPC, your KMS, your IAM—no external data dependencies.

Full Code Access (No One Else Offers This)You receive source access to connectors, policy engine, and agent interfaces—no vendor lock-in.

Governance & ComplianceCOPPA/CIPA/FERPA support, state student privacy laws, RBAC, audit logs, retention, and data residency options.

Observability & Cost ControlUsage telemetry, model costs, performance traces, and content-safety tools for safe deployment.

ResultMaximum student privacy, predictable cost, and responsible AI adoption—under your control.

What OS Connects (Examples)

SISPowerSchool, Infinite Campus, Skyward, Aeries

LMSGoogle Classroom, Canvas, Schoology, Brightspace

RosteringClever, ClassLink, OneRoster

AssessmentsNWEA MAP, Renaissance Star, iReady, state testing platforms

Identity & StorageGoogle Workspace for Education, Microsoft 365 Education, Clever SSO

What's Inside OS (Architecture Highlights)

MCP Integration LayerNormalizes access to SIS/LMS/rostering/assessment systems via secure adapters

Student Memory LayerPer-student knowledge graph + vector index with policy-aware, age-appropriate retrieval

Policy & Guardrails EngineField-level permissions, PII redaction, parental consent, content-safety filters

Agent InterfacesTutor (student), Teaching Assistant (teacher), Admin Assistant (district staff)

Model Hub (LLM-Agnostic)OpenAI, Gemini, Anthropic, Llama, local/NPU options—hot-swappable

Event Bus & AutomationsTriggers for attendance alerts, grade milestones, intervention referrals

Audit & TelemetryEnd-to-end logs, prompt/response archives, cost and latency meters

Admin ConsoleConnectors, schemas, dataset scopes, memory visibility, and policy editing

Why OS Outperforms Typical Integration Hubs

Student Memory LayerOS: Policy-aware, per-student context | Typical: No unified memory

Runs in Your InfraOS: Your VPC, keys, IAM | Typical: Vendor cloud only

Full Code AccessOS: Source delivered, extensible | Typical: Black box / SDK limits

LLM-AgnosticOS: Swap models freely (incl. local) | Typical: Single-model dependency

K-12 GovernanceOS: COPPA/CIPA/FERPA-ready, parental consent | Typical: Generic role gates

Agent-ReadyOS: Standard tutor/TA/admin interfaces | Typical: DIY agent plumbing

Benefits That Drive Impact

StudentsPersonalized, age-appropriate help across subjects and grade levels.

TeachersA dependable teaching assistant informed by real student data and curriculum standards.

District Leaders & ITA private, ownable AI foundation—no lock-in, full auditability, student-safe by design.

ibl.ai

The ibl.ai platform supplies secure memory and connectors, AI tutoring experiences, and adaptive practice with analytics.

It designs standards-aligned curricula and issues portable, verifiable proof of learning — an ownable AI operating system for K-12 education.

Experience OS Today

Architecture ReviewMap your SIS/LMS/rostering and security requirements

Private PilotDeploy in your cloud with your datasets and policies

Schedule a DemoSee how OS unifies district data, protects student privacy, and powers agents—with code you own.

What our partners say about us

Case Studies

Chris Gabriel | Google

Case Studies

Lorena Barba | George Washington University

Case Studies

Dr. Juana Mendenhall | Morehouse College

Juile Diop | MIT

Adam Tetelman | Nvidia

Jason Dom | American Public University System

Benjamin Breyer | Columbia University

Ken Fujiuchi | SUNY

Erika Digirolamo | Monroe College

David Flaten | SUNY

David Vise | Modern States Education Alliance

Linda Wood | ARM Institute (U.S. Department of Defense)

Case Studies

Chris Gabriel | Google

Case Studies

Lorena Barba | George Washington University

Case Studies

Dr. Juana Mendenhall | Morehouse College

Juile Diop | MIT

Adam Tetelman | Nvidia

Jason Dom | American Public University System

Benjamin Breyer | Columbia University

Ken Fujiuchi | SUNY

Erika Digirolamo | Monroe College

David Flaten | SUNY

David Vise | Modern States Education Alliance

Linda Wood | ARM Institute (U.S. Department of Defense)

Frequently Asked Questions

Unify your data first — then deploy agents

Agentic OS reasons over a unified knowledge layer. Here's why that ontology comes first, and how it's built.