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.

📅 Book a 30-min Demo 📞 Call/text (571) 293-0242

Agentic OS (Operating System)

Unify SIS, LMS, CRM, and ERP data into a secure student memory layer—powering enrollment, financial aid, advising, and tutoring 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 Higher Education

How to connect your campus systems (LMS, SIS, CRM, degree audit) to AI agents — step by step.

Read the Guide

Runs on

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

1 / 5

Live

Enrollment AgentRecruitment campaigns and admissions inquiries Live

Application Reader AgentApplication scoring, transcript evaluation Live

Financial Aid AgentFAFSA, aid eligibility, scholarship matching Live

Academic Advisor AgentDegree planning, course registration Live

Tutoring AgentPersonalized 1-on-1 help across subjects Live

Retention AgentAt-risk identification and early intervention Live

Student Services AgentHousing, campus life, wellness support Live

Career Services AgentResume building, interview prep, job matching Live

Faculty AgentCourse creation, grading, feedback Live

Research AgentLiterature review, citations, grant support Live

Alumni AgentAlumni engagement, fundraising, events Live

IT Help Desk AgentStaff and student tech support

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 campus data into a secure student memory layer

An Ownable AI Operating System for Higher Education.

OS by ibl.ai connects SIS, LMS, CRM, and ERP systems over an MCP-based interoperability layer to assemble a secure, per-user memory. That memory gives your AI agents the right context—so every student gets a tutor, every instructor a teaching assistant, and every administrator a digital aide.

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

For Students: Context-Rich, Personal Tutors

Unified Student MemoryAdvising history, course enrollments, grades, deadlines, accommodations, and career goals—federated from your SIS/LMS/CRM and made available (with policy guardrails) to the student's tutor.

Personalized SupportProactive nudges, study plans, and citable answers grounded in course content and institutional policies.

Privacy by DesignFine-grained consent and selective disclosure (e.g., hide financial/health fields) for every interaction.

ResultFaster help, fewer drop-offs, stronger outcomes.

For Instructors & Chairs: A Real Digital TA

Teaching Context, Not GuessworkPulls rosters, outcomes, rubrics, and prior performance to draft study guides, FAQs, and interventions.

Workflow AutomationsOffice-hour triage, assignment hints, and discussion moderation—always citing the course sources you approve.

Academic ControlDepartment-level policies, versioned prompts, and oversight dashboards.

ResultMore time for teaching and mentorship, less time on repetitive support.

For Administrators & IT: Own the Stack, Control the Risk

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 & ComplianceFERPA/GDPR support, SOC 2–aligned controls, RBAC, audit logs, retention, and data residency options.

Observability & Cost ControlUsage telemetry, model costs, performance traces, and red-team/replay tools for safe iteration.

ResultMaximum privacy, predictable cost, and accelerated AI roadmaps—under your control.

What OS Connects (Examples)

SISEllucian Banner, Oracle PeopleSoft Campus Solutions, Colleague

LMSCanvas, Blackboard, Brightspace, Moodle

CRMSalesforce, Slate

ERP/Finance/HRWorkday, Oracle, Microsoft Dynamics

Identity & StorageAzure AD/Entra, Okta, Google Workspace, OneDrive/SharePoint, S3, GCS

What's Inside OS (Architecture Highlights)

MCP Integration LayerNormalizes access to SIS/LMS/CRM/ERP via secure adapters

Student Memory LayerPer-user knowledge graph + vector index with policy-aware retrieval

Policy & Guardrails EngineField-level permissions, PII redaction, consent, rate/usage limits

Agent InterfacesTutor (student), Teaching Assistant (instructor), Digital Assistant (administrator)

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

Event Bus & AutomationsTriggers for risk alerts, degree milestones, advising follow-ups

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-user 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

Higher-Ed GovernanceOS: FERPA-ready, selective disclosure | Typical: Generic role gates

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

Benefits That Drive Impact

StudentsTimely, contextual help across courses and services.

FacultyA dependable digital TA informed by the real course and roster data.

Leadership & ITA private, ownable AI foundation—no lock-in, full auditability, rapid innovation.

ibl.ai

The ibl.ai platform supplies secure memory and connectors, AI tutoring and TA experiences, and course delivery with analytics.

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

Experience OS Today

Architecture ReviewMap your SIS/LMS/CRM/ERP and security requirements

Private PilotDeploy in your cloud with your datasets and policies

Schedule a DemoSee how OS unifies data, safeguards 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.